Search

The work presented in this paper concerns a switching-based control formulation for multi-intersection and multiphase traffic light systems. A macroscopic traffic flow modeling approach is first presented, which is instrumental to the development of a model-based and switching-based optimization method for traffic signal operation, in the framework of adaptive dynamic programming (ADP). The main advantage of the switching-based formulation is its capability to determine both “when”’ to switch and “which” mode to switch on without the need to use the cycle-based average flow approximation typical of state-of-the-art formulations. In addition, the framework can handle different cycle times across intersections without the need for synchronization constraints and, moreover, minimum dwell-time constraints can be directly enforced to comply with minimum green/red times in each phase. The simulation experiments on a multi-intersection and multiphase traffic light systems are presented to show the effectiveness of the method. [ABSTRACT FROM AUTHOR]

In the system and control community, the sliding mode control technology has been known as a tool which is able to handle system uncertainties and external disturbances. Simplicity in implementation and good stability performance are the other interesting features of the sliding modes. However, traditional sliding mode controllers exhibit two weaknesses, as follows: 1) generally, they have asymptotic stability in sliding mode dynamics which results in a slow speed system and 2) the so-called chattering phenomenon exists, which produces undesirable high frequency oscillations in the control signal. In this paper, the former problem is solved using a twofold terminal sliding manifold displaying desired transient and steady state behavior. The latter issue is responded to by a twofold sliding mode technology which leads to a continuous sliding control rule instead of a discontinuous switching control. The effects of uncertain terms as well as external perturbations with unknown bounds are fully compensated using updated parameters. The values of the updated parameters approach fixed values as the system trajectories converge to the equilibrium states. The analytical results of this paper are theoretically proved using the Lyapunov technique and the finite-time control strategy. Comparative computer simulations on a robotic manipulator confirm the fast convergence attribute and robust performance of the introduced adaptive robust nonsingular terminal sliding control algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the robust containment control problem of multiagent systems with heterogeneous uncertainty and nonlinearity while the nonlinear parts have to satisfy the Lipschitz condition. In this paper, both input time-delay and data transmission time-delay between the agents are considered simultaneously and communication topology of the multiagent systems may switch in the steady-state condition. Under the mentioned conditions, the objective of this paper is to make all the followers’ states converge to the convex hull shaped by the leaders’ states with an expected exponential rate. To this end, an appropriate smooth protocol is proposed. Then, a Lyapunov–Krasovskii functional composed of five terms is proposed and the stability condition is denoted by two linear matrix inequalities (LMIs). In addition to the stability assurance, solving the LMIs would obtain the suitable gains for the protocol. Finally, some numerical simulations are given to verify the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of reliable sliding mode control for descriptor systems with semi-Markov parameters using the Takagi–Sugeno fuzzy model, in which an average dwell time approach is utilized to tackle generic uncertain transition rates (TRs). From the analysis of the inner mechanism of switching singular system, a continuous sliding surface function is proposed. Different from continuity with probability one for stochastic systems, the absolute continuity of system solution is a key point in this paper being ensured for application of the average dwell time approach. Then, the mean-square exponential stability of the obtained sliding mode is analyzed based on two types of uncertain TRs. Moreover, a sliding mode controller is constructed to ensure the reachability condition in finite time. Lastly, the method is verified numerically by a single-link robot arm model. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of controller design for normal nonlinear switched systems with unknown dynamics. The situation assumes that the nonlinear component of the system dynamics is unknown and there are extra uncertain terms and external perturbations affecting the system responses. Unlike previous methods that usually apply artificial neural networks to obtain an approximate model for an unknown dynamics, we use simple adaptive laws to surmount such fluctuations as well as to circumvent the steady state errors in the approaches provided by neural networks or fuzzy logics. No information on the bounds and parameters of the uncertain parts is needed. We design a twofold sliding mode control methodology to stabilize the whole switched system with arbitrary switching signals. To handle the consequences of the inherent chattering, a smooth integral type control signal is constructed. It is proved that once the system states attain the developed sliding manifold, the system becomes insensitive to both the lumped uncertainties and the dynamics of the switched system. The common assumption of a known Lyapunov functions for the subsystems is relaxed and the derived adaptive approach provides nonconservative circumstances for guaranteeing the global stability of the equilibrium state. The theoretical results of this paper are generalized for the canonical nonlinear systems with mismatched uncertainties and a novel adaptive sliding manifold is proposed to suppress the effects of the system mismatching uncertain parts. A comparative computer simulation is developed to examine the effective performance of the introduced controllers. [ABSTRACT FROM AUTHOR]

This paper is concerned with the consensus problem of general linear dynamic multiagent systems with stochastic sampling. In this paper, the sampling intervals randomly switch between two different values. The communication topology between agents is fixed and directed. Full- and reduced-order observers are designed based on neighbor agents’ relative output information. The algorithms to construct such observers are also provided. By using the estimated states of the agents, the observer-based consensus protocol with stochastic sampling are presented. Sufficient conditions to ensure consensus in mean square are derived by using Lyapunov stability theory. Finally, simulations are given to examine the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-triggered finite-time control problem for networked switched linear systems by using an asynchronous switching scheme. Not only the problem of finite-time boundedness, but also the problem of input-output finite-time stability is considered in this paper. Compared with the existing event-triggered results of the switched systems, a new type of event-triggered condition is proposed. Sufficient conditions are established to guarantee the event-based asynchronous closed-loop systems are both finite-time bounded and input-output finite-time stable. A set of event-triggered finite-time bounded and input-output finite-time stabilizing controllers are designed under the asynchronous control scheme. It is revealed that the triggered thresholds determine the number of sampling points transmitted to the controller, and the smaller triggered parameters indicate the less-sampled data needed to be transmitted to the controller under the event-triggered scheme. Finally, a boost converter circuit is applied to bring out the advantages of the proposed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, the stability problem of delayed neural networks is investigated by adopting some switching methods. First, the delay interval is divided into many smaller variable intervals, and when the smaller variable interval is regarded as a mode of the delay, delayed neural networks are modeled as switched systems. Then, by using some switching methods, less conservative stability criteria are derived to ensure the stability of delayed neural networks. Finally, one example is provided to show the effectiveness of the obtained criteria. [ABSTRACT FROM AUTHOR]

Since the inherent nature of many applied high-technological systems and networks possesses switching behaviors, modeling, controlling, and stabilizing problems of the switching plants are becoming as the important research scenarios in the current literature. Moreover, consideration of the effects of mismatching uncertainties along with matching uncertain parts as well as unknown dynamics is a significant topic in the control engineering community. As a result, this paper is dedicated to the controlling problem of partially unknown nonlinear switched systems whose dynamics are perturbed by both matched and mismatched uncertainties. In addition, since the existence of gain deviations in real-world implementations of physical actuators can lessen the control act of the switching system, this paper handles the corresponding gain variations in the control inputs via some adaptation variables. In the design procedure, no limiting supposition is made for the switch signal of the switched plant. The proposed control algorithm is based on the variable structure control theory in which the selected sliding surface is able to deal with mismatching uncertainties and the deriving control law is robust against the lumped uncertain components. As a contribution, the Lyapunov functions are built such that not only to provide an asymptotic stable system but also to assure the global (practical) finite-time stability of the equilibrium state of the final closed-loop cascade switched plant. The robust performance of the developed control strategy is confirmed via two illustrative examples. [ABSTRACT FROM AUTHOR]

This paper is concerned with the problem of finite-time H∞ synchronization for a class of discrete-time switched neural networks with quantized feedback controllers. First, we take advantage of mode-dependent average dwell time approach and semi-time-dependent (STD) Lyapunov function method to establish new criteria for the finite-time synchronization. Based on the newly developed criteria, a finite-time bounded real lemma is presented and further, the quantized state feedback controller is designed to ensure the finite-time H∞ synchronization of the underlying neural networks. The conservatism is further reduced by the proposed mode-dependent and STD controller. Finally, we use two illustrative examples to show the effectiveness and superiority of the results obtained in this paper. [ABSTRACT FROM AUTHOR]

This paper includes some results of switched Boolean control networks. The switched signals considered in this paper is time variant and it follows a certain probabilistic distribution vector. Given a concept of stabilization with stochastic switched signals, we obtained a necessary and sufficient condition for stabilization. Then a state feedback control depending on switched signals is designed to stabilize the system considered. Later we investigate a case when the switched signal $\theta (t)$ is unknown at time $t$ , and what we have is the prediction switched signal $\hat {\theta }(t)$. For a given prediction matrix, a necessary and sufficient condition is given to preserve the stabilization. Except state feedback control, asynchronous pinning control for switched Boolean networks (BNs) is also considered. A necessary and sufficient condition is extended for the stability of BNs with stochastic switched signals. Moreover, algorithms are presented to find the minimal number of pinned nodes based on controlling minimal number of subsystems. Examples are shown to illustrate the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper investigates the integral sliding mode control problem of T–S fuzzy interconnected descriptor system based on a reduced-order compensator. A canonical equivalent form for T–S fuzzy interconnected descriptor system is first introduced to facilitate the reduced-order compensator design. In terms of the measurable output variables of the T–S fuzzy interconnected descriptor system and the state variables of the proposed reduced-order compensator, an integral sliding mode control scheme is then developed for the T–S fuzzy interconnected descriptor system. The sliding motion is defined in the augmented space formed by the state variables of the original T–S fuzzy interconnected descriptor system and the resulting error system. It is shown that the designing parameters in the switching function can be simultaneously solved and the original T–S fuzzy interconnected descriptor system has no requirement to be relative degree one. Since the estimate error is bounded by an auxiliary dynamical system, when ideal sliding mode occurs, the resulting closed-loop system is asymptotically stable rather than uniformly ultimately bounded. Finally, a double-inverted pendulum system and a ball and beam system are numerically simulated to demonstrate the effectiveness and merits of the method proposed. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of adaptive observer-based stabilization for a more general class of uncertain switched stochastic nonlower triangular nonlinear systems with average dwell-time (ADT) switching. The completely unknown nonlinear functions possessing the entire states are handled using the neural networks universal approximation property and the variable separation technique. The main novelty of this paper is that it presents a universal formula for constructing an adaptive output-feedback controller of the considered system with only one adaptive parameter by designing a switched state observer. The theoretical analysis shows that the Lyapunov stability of the overall closed-loop system is ensured in the presence of ADT switching. Finally, the effectiveness and practicability of the obtained design scheme are illustrated by two simulation examples. [ABSTRACT FROM AUTHOR]

In this paper, we address the adaptive neural tracking control problem for a class of uncertain switched stochastic nonlinear pure-feedback systems with nonlower triangular form. The significant design difficulty is the completely unknown nonlinear functions with all state variables that can neither be directly estimated by radial basis function (RBF) neural networks (NNs) nor be eliminated by the traditional backstepping technique. To achieve the control objective of this paper, a common state-feedback controller for all subsystems is first systematically constructed by using the common coordinate transformation, the variable separation technique, and the universal approximation capability of RBF NNs. Then the stability analysis shows that the semi-global bounded in probability of the whole closed-loop switched system can be obtained and the desired tracking performance can also be insured under a class of switching signals with the average dwell time property. Finally, simulation results are given to demonstrate the effectiveness of the obtained control scheme. [ABSTRACT FROM AUTHOR]

This paper presents voltage regulation and current tracking control strategies for three phase two-level grid-connected power converters. By using power-invariant Park’s transformation, an averaged mathematical model of power converters is obtained in dq synchronous reference frame. Then a novel control strategy using adaptive control and ${H}_{\infty }$ technique is proposed to regulate the dc-link output voltage as well as track a desired current reference for three-phase power rectifiers. More specifically, an efficient adaptive controller is established in the external loop for regulating dc-link output voltage in the presence of external disturbances. A set of ${H}_{\infty }$ controllers are designed in the internal loop to force the input currents track their desired values. Finally, simulation results obtained from the proposed control method are presented, analyzed, and compared with that of sliding mode control, and the superiority of the proposed control laws is verified. [ABSTRACT FROM AUTHOR]

This paper studies the stability analysis of the input saturated discrete-time switched systems with average dwell-time based on the parametric discrete-time Riccati equation. The state feedback controller and the observer-based output feedback controller are designed to guarantee the exponential stability of the closed-loop system. The proposed method is simple and easy to operate in practice. The designed controllers can be computed easily by solving the parametric discrete-time Lyapunov equation. The main advantages of this paper are that the stability analysis is based on the properties of the saturation function and limited structure information of the actuator saturation and that the designed controllers have good robustness to the structure uncertainty of the input saturation. The simulation results illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper mainly investigates the problem of extended dissipative filter design for switched discrete-time systems where the variation of switching signals among subsystems is governed by the persistent dwell-time strategy. Considering that in practical applications, the congestion of the communication channels between systems and filters may cause data loss, therefore the packet dropouts are taken into account to make the issue under consideration more general. Meanwhile, it is generally known that the mode information of the system may sometimes not be accessed, so we consider the design of a unified filter including mode-dependent and mode-independent filters simultaneously. A white sequence that obeys the Bernoulli distribution is used to express the random switching of the filters. The main purpose of this paper is to find a suitable filter design method which ensures that the resulting error system is exponentially mean-square stable and extended dissipative. Sufficient conditions are established to make sure the solvability of the addressed problem. By using appropriate decoupling method, some conditions that could be readily solved are obtained. In order to explain the correctness and effectiveness of the proposed method, two illustrated examples are given in the final part of this paper. [ABSTRACT FROM AUTHOR]

This paper deals with a state-feedback control scheme for nonlinear stochastic systems with Markovian switching. First, we present the results on the practically $ {p}$ -moment exponential stability with respect to an additional disturbance and the practically $ {p}$ -moment asymptotic stability relying on a specific event. However, elements in this event are hard to be observed directly. The main aim of this paper is to develop a self-triggered sampling rule to overcome this difficulty. By applying the improved monotone growth condition, Itô’s formula, Fubini’s theorem, Gronwall inequality, and comparison lemma, we establish a novel lemma to estimate the lower bound and upper bound of second-moment for state and error, respectively. Moreover, we also establish the practically asymptotic stability in mean square with the help of Jensen’s inequality technique, properties of $ {\mathcal {K}}$ -function and result on $ {p}$ -moment input-to-state stability. Furthermore, from Lipschitz continuity and monotonicity of functions, we obtain the value of the maximum triggering interval based on lasted-observed state. Finally, we give some remarks and discussions to show the significance of our results by comparing with those in the previous literature. [ABSTRACT FROM AUTHOR]

This paper investigates an event-based tracking problem of networked second-order systems with unknown inertias and switching networks, where the leader’s trajectory is dynamic and is available to only a subset of followers. Besides, the followers have only local interactions. A new class of distributed event-triggered control protocols with and without velocity measurements are designed to guarantee the tracking performance. Furthermore, it is strictly proved that the proposed algorithms guarantee a fully Zeno-free triggering for all the agents. Finally, simulation results are provided to demonstrate the effectiveness of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the stability problem of sampled data Takagi–Sugeno fuzzy control systems with packet dropouts is investigated. A sampling-dependent time-varying Lyapunov function (SDTVLF) is constructed to analyze the stability problem of the system and a switched system approach is proposed to model the packet dropouts phenomenon. On this basis, by dividing the sampling input available interval and unavailable interval into several segments, the matrix functions of the SDTVLF are chosen to be continuous piecewise linear. Then, by using the proposed SDTVLF approach, computable convex conditions are obtained for the sampling input unavailable interval and the sampling input available interval in framework of dwell time. By confining the sampling input unavailable interval with an upper bound and confining the sampling input available interval with a lower bound, the SDTVLF is always decreasing in all sampling input available and unavailable interval, which can make the sampled control system tolerate a larger packet dropout rate. A numerical example is provided to show the efficiency of the proposed results. [ABSTRACT FROM AUTHOR]

This paper considers the global stabilization for a class of uncertain nonlinear systems with unknown powers, unknown control directions, and unknown nonlinearities. Mainly due to the presence of the unknown powers which have not known upper bound, no existing methods are applicable to the control problem to be solved. In this paper, to compensate the serious system uncertainties and particularly to overcome the major obstruction from unknown powers, we appeal to the mechanism of switching adaptive feedback. By flexibly combining the domination and the method of adding a power integrator, we propose a new adaptive controller design, whose design parameters are tuned online based on a switching logic. The designed controller will become operative as long as finite switchings happen and will not lead to Zeno phenomenon, and can guarantee the global boundedness as well as ultimate convergence of the resulting closed-loop system. Two numerical examples are given to demonstrate the effectiveness of the developed design scheme. [ABSTRACT FROM AUTHOR]

This paper solves the adaptive consensus problem for first-order linearly parameterized agents with completely nonidentical unknown high-frequency gain signs under directed graphs. A new class of Nussbaum-type function-based algorithms are proposed to handle the unknown high-frequency gain signs adaptively and cooperatively. It is shown that if the underlying topology is a fixed graph with strongly connected or switching topologies having a jointly strongly connected basis, the first-order linearly parameterized agents with nonidentical unknown high-frequency gain signs can achieve asymptotic consensus. Finally, the effectiveness of proposed algorithms are verified by one simulation example. [ABSTRACT FROM AUTHOR]

In this paper, the problems of nonfragile and nonsynchronous synthesis for Bernoulli switched systems are studied. The disturbances in the systems are assumed to have bounded peak in the sense of mean square. With the interval additive gain variations consideration, a nonfragile and nonsynchronous controller is designed subject to a nonsynchronous assumption that the switching signals of the system are not accurately gained for synthesis. A sufficient condition that is dependent on the known sojourn probabilities of switching signals is proposed to ascertain the reachable set of the closed-loop system, which is a hidden Bernoulli model, mean square contained in an ellipsoid-like set. Several nonfragile and nonsynchronous controllers are parameterized to guarantee the corresponding requirements to be satisfied for the closed-loop systems. The effectiveness and advantages of the proposed new design techniques are illustrated by a numerical simulation example. [ABSTRACT FROM AUTHOR]

This paper is concerned with quasi-synchronization of delayed memristive neural networks (MNNs) with switching jumps mismatches via aperiodically intermittent control. The issue is presented for three reasons: 1) the existing controllers for synchronization may be too complicated and not economical; 2) under the influence of switching jumps mismatches, synchronization of MNNs may fail to achieve; and 3) matrix measure method is less conservative but cannot be applied directly to synchronization of MNNs. To overcome these difficulties, the concept of asynchronously switching time interval is proposed to describe the phenomenon when the drive-response MNNs switch their connection weights asynchronously. Then, aperiodically intermittent control is designed and quasi-synchronization analysis is carried out based on a combined method that compromises the merits of interval matrix method and matrix measure method. A quasi-synchronization criterion, expressed in terms of the mixture of ${p}$ -norm and matrix measure of the memristive connection weights, is established. Meanwhile, the fundamental reason for the failure of complete synchronization is revealed. Moreover, an explicit expression of the error level is obtained and the design of the controller under a predetermined error level is presented. The obtained results in this paper reduce the conservativeness and provide a novel insight into the research of synchronization of MNNs. [ABSTRACT FROM AUTHOR]

This paper considers the global stabilization problem via sampled-data control for a class of switched nonlinear systems meanwhile taking into account asynchronous switching. First of all, a state feedback sampled-data controller is constructed by backstepping design method. Then, a relationship between the sampling period and the average dwell time is derived, which can guarantee that the closed-loop system is globally asymptotically stable. Finally, two simulation examples are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This correspondence paper is concerned with observer design problems for a class of unknown input switched descriptor systems under average dwell time switching signals. The switched descriptor system under consideration is first transformed into a general switched linear system, and then a switched reduced-order observer that can asymptotically estimate the system state without suffering the influence from the unknown inputs is developed. Besides, a high-order sliding mode observer is introduced to obtain the estimations of the output derivatives by using the system measured outputs. On the basis of estimations of the states and output derivatives, an unknown input reconstructing method is provided. Finally, two examples are presented to verify the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

This paper considers trajectory tracking control for a one-degree of freedom (DoF) manipulator system driven by pneumatic artificial muscles. A switched sliding mode controller is accordingly designed. In the proposed scheme, a novel extended state observer based on a generalized super-twisting algorithm is first designed to deal with internal uncertainties and external disturbances in the one-DoF manipulator system. Second, the finite time convergence of the closed-loop system with the proposed sliding mode technique is analyzed. Lastly, some experimental results are presented to show the validity and advantages of the proposed approach. [ABSTRACT FROM AUTHOR]

In this paper, the stabilization problems for singular Markovian systems with Brownian motion are studied by use of sliding mode control (SMC) with the jumping transfer matrix known, unknown, or partly unknown. At first, a new stochastic sliding mode surface (SSS) is introduced. The problem of state trajectories moving among several sliding mode surfaces can be settled perfectly. By use of the proposed SSS, the sliding mode dynamics of singular Markovian systems with Brownian motion is asymptotically mean square admissible and sufficient design conditions are derived in linear matrix inequalities. Second, by use of a new approach different from the normal Lyapunov method, an SMC law is provided to avoid the state trajectories escaping from the sliding mode surface. Finally, three numerical simulations and one practical simulation are provided to illustrate the validity of the proposed method. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of robust stabilization for a class of uncertain nonlinear pure-feedback switched time-delay systems with quantized input signal. In order to overcome the design difficulty caused by the quantization and unpredictable switchings, a nonlinear decomposition strategy for quantizer is employed in advance. In the controller design procedure, the unknown time-delay terms are compensated by utilizing Lyapunov–Krasovskii functionals, the desired virtual stabilizing functions and desired actual control input are approximated by applying radial basis function neural networks, and dynamic surface control technology are used to handle the issue of “explosion of complexity” in the traditional backstepping procedure. Furthermore, it is shown that the resulting closed-loop system are stable in the sense of semi-global uniformly ultimately bounded. Finally, to verify the effectiveness and applicability of the presented control scheme, an example is given to construct an adaptive neural controller for an electromechanical system. [ABSTRACT FROM AUTHOR]

Prognostics predictions estimate the remaining useful life (RUL) of assets. This information enables the implementation of condition-based maintenance strategies by scheduling intervention when failure is imminent. Circuit breakers (CBs) are key assets for the correct operation of the power network, fulfilling both a protection and a network reconfiguration role. Certain breakers will perform switching on a deterministic schedule, while operating stochastically in response to network faults. Both types of operation increase wear on the main contact, with high fault currents leading to more rapid aging. This paper presents a hybrid approach for prognostics of CBs, which integrates deterministic and stochastic operation through piecewise deterministic Markov processes. The main contributions of this paper are: 1) the integration of hybrid prognostics models with dynamic reliability concepts for a more accurate RUL forecasting and 2) the uncertain failure threshold modeling to integrate and propagate uncertain failure evaluation levels in the prognostics estimation process. Results show the effect of dynamic operation conditions on prognostics predictions and confirm the potential for its use within a condition-based maintenance strategy. [ABSTRACT FROM AUTHOR]

This paper investigates the cluster event-triggered tracking cooperative and formation control for multivehicle systems with nonlinear vehicles dynamics under switching directed communication topologies and safety missions. By employing the cluster event-triggered control strategy, the assumption of continuous feedback control gains and the condition of information exchange limited in a small domain can be relaxed. By constructing an appropriate tracking cooperative condition, a class of cluster event-triggered tracking cooperative control law with an extended magnification region condition is proposed based on bounded parameters and intermittent event samples. When the safety tasks are activated, it is displayed in terms of linear matrix inequalities that the tracking cooperative control for closed-loop multivehicle systems subject to nonlinear vehicles dynamics will be achieved, if the constructed sampling condition and the dwell time constraint of switching communication scenarios can be held. Furthermore, the proposed method is extended to formation control problem for the multivehicle systems. Simulations are presented to demonstrate the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

Existing results for cooperative control of high-order agents mainly employ the Nussbaum-type function to cope with unknown control directions and mostly require an assumption that the control directions are identical and unknown. This paper proposes a class of algorithms with nonlinear PI functions to relax such an assumption and make them suitable for nonidentical unknown control directions. It is proven that if the distributed nonlinear PI functions are suitably selected, the proposed algorithms can achieve consensus for high-order agents under strongly connected topologies and switching topologies with a jointly strongly connected basis (JSCB). Furthermore, we extend the consensus results to the case of time-varying topologies described by $\delta $ -connected, continuous graphs. As a special case, the consensus of high-order agents under the directed graph having a spanning tree is also investigated. Finally, illustrative simulations are presented to indicate the efficiency of the proposed algorithms. [ABSTRACT FROM AUTHOR]

Asynchronous switching between the controller and the active subsystems in multiphase batch processes may cause the systems to be unstable around the switching instants. In view of this, an average dwell-time method-based iterative learning control (ILC) scheme is proposed in this paper. First, the multiphase process is represented as an equivalent closed-loop two-dimensional (2-D) switched system composed of stable and unstable subsystems, based on which new relevant concepts on the stability of the switched system are given. Second, using an average dwell-time method, the ILC law is designed to guarantee the system exponentially stable. Minimum running time for the stable subsystems and maximum running time for the unstable ones are obtained. Lastly, depending on the maximum time for the unstable subsystems, the idea of putting the controller switching step forward is proposed. In this way, the asynchronous switching is removed such that the unstable subsystem can be avoided. The case study on an injection molding process demonstrates the effectiveness and superiority of the proposed method in comparison with the existing 2D-MPC and one-dimensional traditional control methods. [ABSTRACT FROM AUTHOR]

This paper considers the leader-following consensus of multiagents with one-sided Lipschitz nonlinear dynamics by considering switching topologies. For the suitable selection of the consensus control gain matrix and coupling weight, a new condition for consensus is achieved for switching communication links with a directed spanning tree in the topology by constraining the dwell time. Employing a communication restoration mechanism allows a method to be obtained for the case in which a topology violates a permanent directed spanning tree. Computationally straightforward consensus controller design conditions that are necessary and sufficient for the former conditions are also developed for both cases. These simpler conditions can be used to obtain consensus protocol gains directly through convex routines. An algorithm is also provided to solve nonlinear constraints using the cone complementary linearization approach by considering a nonlinear objective function optimization problem. A numerical simulation is provided for multiagents that demonstrates the proposed control schemes’ efficiency. [ABSTRACT FROM AUTHOR]

In this paper, we address the finite-time and fixed-time synchronization of a general class of switched neural networks (SNNs) with time delays subject to stochastic disturbances. Considering two types of switching in this class of SNNs: 1) intra-SNN state-dependent switching and 2) inter-SNN Markovian switching, we develop three control laws and derive three sets of sufficient conditions for both finite-time and fixed-time synchronization of SNNs subject to stochastic disturbances. We make two remarks on the effects of control-law parameters on synchronization settling time. Moreover, we derive several upper bounds of synchronization settling time and evaluate their pros and cons. Finally, we elaborate on two numerical examples to illustrate the viability of the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we analyze dynamic switching networks, wherein the networks switch arbitrarily among a set of topologies. For this class of dynamic networks, we derive an epidemic threshold, considering the susceptible-infected-susceptible epidemic model. First, an epidemic probabilistic model is developed assuming independence between states of nodes. We identify the conditions under which the epidemic dies out by linearizing the underlying dynamical system and analyzing its asymptotic stability around the origin. The concept of joint spectral radius is then used to derive the epidemic threshold, which is later validated using several networks (Watts–Strogatz, Barabasi–Albert, MIT reality mining graphs, Regular, and Gilbert). A simplified version of the epidemic threshold is proposed for undirected networks. Moreover, in the case of static networks, the derived epidemic threshold is shown to match conventional analytical results. Then, analytical results for the epidemic threshold of dynamic networks are proved to be applicable to periodic networks. For dynamic regular networks, we demonstrate that the epidemic threshold is identical to the epidemic threshold for static regular networks. An upper bound for the epidemic spread probability in dynamic Gilbert networks is also derived and verified using simulation. [ABSTRACT FROM PUBLISHER]

This paper investigates the leader–follower robust ${H_\infty }$ consensus of heterogeneous multiagent systems with denial of service attack, where different attack intensities are considered. A switched system model is introduced to model such an attack phenomenon. Then, sufficient conditions to guarantee the solvability of the robust output consensus problem are obtained, and the quantitative relationship between the consensus performance and attack parameter is established. It is shown that the consensus protocol design problem can be transformed into two static output feedback (SOF) control problems. It is also shown that the SOF controller gains can be determined by solving some linear matrix inequalities without the knowledge of the probability information of each attack. Finally, the effectiveness of the control protocol is demonstrated by a simulation study. [ABSTRACT FROM AUTHOR]

The global output feedback stabilization problem is investigated in this paper via sampled-data control for switched nonlinear systems in the $p$ -normal form. First, a reduced-order state observer is designed. Then, an output feedback sampled-data controller is constructed with the relaxation of some restrictions of switched nonlinear systems. The proposed controller can ensure that all states of the corresponding closed-loop system can converge to the origin. Simulation results are given to show the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

This paper addresses the admissible consensus problem for homogenous descriptor multiagent systems with undirected graphs and disturbances. First, to achieve the consensus objective and attenuate the effects of disturbances, the distributed controllers are formulated and the admissible consensus problems are formulated. Another improvement emphasizes that the proposed approach can simplify the complexity of the admissible consensus analysis by using the state transformation during the admissible analysis and disturbances suppression analysis. Moreover, based on Riccati inequalities and linear matrix inequalities, two necessary and sufficient conditions are presented to ensure the admissible consensus and disturbances suppression objectives. Finally, two simulation examples are provided to demonstrate the effectiveness of the proposed approaches. [ABSTRACT FROM AUTHOR]

This paper proposes a unified framework to design sliding-mode control for stabilization of delayed memristive neural networks (DMNNs) with external disturbances. Under the presented framework, finite-time stabilization, and fixed-time stabilization of the controlled DMNNs can be, respectively, obtained by choosing different values for a specific control parameter. It is proved that the system responses can be made reaching the designed sliding-mode surface in finite and fixed time, and then stay on it. Moreover, it also illustrates that the inevitable external disturbances can be rejected by the designed sliding-mode control. Finally, the efficiency and superiority of the obtained main results are verified by comparisons with related works and numerical simulations. [ABSTRACT FROM AUTHOR]

The communication cost is generally higher for the consensus of high-order multiagent systems than that for low-order multiagent systems. In this paper, two novel distributed protocols are proposed to address the consensus of high-order discrete-time multiagent systems. By the proposed consensus protocols, each agent only needs to transmit the value of a variable to neighbor agents regardless of the order of agent dynamics. Theoretical analysis shows that the proposed protocols guarantee asymptotic consensus of the agent states in different cases of communication graphs, including jointly connected ones. Simulative examples verify the theoretical results and the efficacy of the proposed protocols. [ABSTRACT FROM AUTHOR]

This paper concerns with the stability analysis for a class of discrete-time switched Takagi–Sugeno (T–S) fuzzy systems. By establishing a semitime-dependent Lyapunov function and exploring the property of mode-dependent average dwell-time switching, improved stability criteria are provided for switched T–S fuzzy systems containing both stable and unstable modes. Then, slow and fast switching strategies are designed, which are adopted for stable and unstable subsystems, respectively. Especially, we also provide the stability conditions for switched systems with all modes stable and unstable. Finally, the validities and advantages of provided techniques are illustrated by some simulation examples. [ABSTRACT FROM AUTHOR]

The second-order sliding mode (SOSM) controller design problem for a class of sliding mode dynamics subject to an upper-triangular structure has been discussed in this paper. The proposed SOSM controller design involves two steps. First, a Lyapunov-based SOSM controller is developed by using the adding a power integrator technique to locally finite-time stabilize the sliding variables. Second, by combining the local SOSM controller with a saturation function, a novel SOSM controller with a saturation level is constructed. The feature of the new SOSM controller lies in that the saturation level can be tuned not only to guarantee the global convergence but also to improve the dynamic performance. Lyapunov analysis has been utilized to test the finite-time stability of the closed-loop sliding mode dynamics. The proposed method is eventually demonstrated by simulation results. [ABSTRACT FROM AUTHOR]

This paper considers the problems on the mean square exponential synchronization and the almost surely exponential synchronization for neutral stochastic dynamical delay networks with Markovian switching via the single pinning impulsive control. By using a unified approach incorporating the concept of average impulsive interval and Lyapunov function, and the Borel–Cantelli lemma, two criteria on the mean square exponential stability and the almost surely exponential stability for impulsive neutral stochastic delay systems with Markovian switching are derived. It is shown that the impulsive control with a suitable impulsive strength can stochastically stabilize the underlying systems. With the symmetry and irreducibility of the switching topologies, and the obtained stochastic stability criteria, sufficient conditions are derived to determine the mean square exponential synchronization of the underlaying networks via the single pinning impulsive controller, which are given with algebraic inequalities and ${\mathcal {M}}$ -matrix. The almost surely exponential synchronization is also analyzed. Two examples are given to verify the validity of the theoretic results presented. [ABSTRACT FROM AUTHOR]

Supply chain systems are network systems with several subchains each of which consists of facilities and distribution entities (suppliers, manufacturers, distributors, and retailers), and thus such systems can be viewed as multiagent systems. Consensus or coordination of multiple subchains is crucial for a stable market supply, especially in the case of some subchains suffering from production interruption, or losing connection with others, which become isolated subchains in some time period due to irresistible reasons. Once some unspecified isolated subchains appear, the topology structure of the system will be changed, and thus the multiagent-based supply chain system can be modeled as a switched system. This paper aims to investigate the problem of ${H_\infty }$ consensus for multiagent-based supply chain systems under switching topology and uncertain demands. To achieve the consensus of the system, switching controller is designed in which both production rate and distributed consensus protocol are considered. Sufficient conditions are given such that the whole system reaches consensus and desirable attenuation of bullwhip effect with an average dwell time approach, which allows some subchains to be isolated in some time periods. Finally, a simulation example is presented to illustrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper is concerned with the consensus issue for a class of multiagent systems with Markovian switching topology under aperiodic sampled data measurements. By constructing a novel piecewise stochastic Lyapunov-Krasovskii functional, some novel conditions with less conservative are established such that the consensus is achieved in the mean square sense. In contrast to some previous publications, the sample period is no longer fixed and the transition probability matrix of Markovian switching topology is uncertain. This issue which is of practical and theoretical significance is further investigated when the sampled data controller of each agent is suffered from distinct time-varying input delay. Quite different with the related studies, a maximally allowable input delay upper bound is replaced by the permissible input delay interval. Furthermore, the corresponding consensus is elegantly obtained in terms of linear matrix inequalities. Finally, the effectiveness and practicability of our consensus criteria are well illustrated by the numerical examples. [ABSTRACT FROM AUTHOR]

In this paper, a quasi-optimal higher order sliding mode control (HOSMC) scheme is designed using disturbance observer (DOB) and adaptive techniques. The overall HOSMC scheme is constituted by three portions: 1) a switch-based quasi-optimal control law that ensures rapid finite-time stabilization of the origin, producing a nominally uncertainty-free system, based on a perturbed chain of integrators; 2) a DOB which estimates the lumped uncertainties with lower frequencies; and 3) an adaptive controller designed to deal with the fast-varying terms of these lumped uncertainties over the pass-band of the DOB. Since the adaptive controller and the DOB work in a cooperative manner, the only requirement is that the switching gain be greater than the bound of the DOB estimation error, instead of the bound of the lumped uncertainties. As a consequence, overestimation in the adaptive controller can be avoided by resorting to the equivalent control. Simulation results confirm the capabilities of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper considers two firms that compete on both advertising and pricing. Each firm decides whether to use mass advertising to cover the entire market or adopt targeted advertising to inform only the switching shoppers. We capture this problem through a dynamic game model in which each firm can endogenously choose its advertising strategy. Our results reveal a number of interesting findings. We show that the two firms would not choose mass advertising simultaneously but might adopt targeted advertising at the same time. Targeted advertising can hurt both firms even if it is more cost-efficient than mass advertising: when the marginal cost of advertising is moderate, the two firms may fall into the well-known trap of the prisoners’ dilemma. In another interesting finding, symmetric firms may employ asymmetric advertising strategies in equilibrium: when the advertising cost is sufficiently low, one firm chooses targeted advertising, while the other adopts mass advertising. In addition, while a fixed cost associated with acquiring the targeting capability weakens firms’ incentives to adopt targeted advertising, a large fixed cost might benefit firms in equilibrium. [ABSTRACT FROM AUTHOR]

This paper presents new theoretical results on the multistability of switched recurrent neural networks with radial basis functions and state-dependent switching. By partitioning state space, applying Brouwer fixed-point theorem and constructing a Lyapunov function, the number of the equilibria and their locations are estimated and their stability/instability are analyzed under some reasonable assumptions on the decomposition of index set and switching threshold. It is shown that the switching threshold plays an important role in increasing the number of stable equilibria and different multistability results can be obtained under different ranges of switching threshold. The results suggest that switched recurrent neural networks would be superior to conventional ones in terms of increased storage capacity when used as associative memories. Two examples are discussed in detail to substantiate the effectiveness of the theoretical analysis. [ABSTRACT FROM AUTHOR]

This paper addresses the control problem of the switched system with bounded actuators and average dwell-time. We present the switching rules for the designed controllers based on two kinds of parametric algebraic Riccati equation. The exponential stability of the switched system under the average-dwell time is ensured by the designed controllers and the switching rules. The dynamic performance of the control system is enhanced greatly by the proposed method. The simulation results illustrate the effectiveness and the usefulness of the obtained theoretical results. [ABSTRACT FROM AUTHOR]