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This paper investigates the adaptive control for a class of uncertain nonlinear systems under denial-of-service (DoS) attacks. We analyze the closed-loop system stability under DoS attacks in terms of attack duration, attack frequency and resting time duration respectively. Three scenarios of DoS attacks against the system stability are considered. Firstly, it is shown that if the duration of each attack is less than a given constant, asymptotical convergence of system output is still preserved. Secondly, if the bounds on the frequency and duration of attacks with respect to overall intervals meet certain conditions, the proposed event-triggered control scheme guarantees that all the closed-loop signals are globally bounded and the stabilization error converges to a ball with a radius arbitrarily small. Thirdly, if resting time duration meets certain conditions after an arbitrarily long attack, closed-loop boundedness is still preserved. Simulation results are shown to illustrate the effectiveness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

Typical communication and detection issues in a nonideal information environment, such as sensing failure, communication and sensing delay, and packet loss, further aggravate the adverse impacts of human-driven vehicle (HV) uncertainty on a mixed vehicle platoon. To guarantee the performance of the mixed vehicle platoon featuring HVs and connected and automated vehicles under the nonideal information environment, this article proposes a platoon control strategy integrating a combined longitudinal and lateral control and message recovery. Specifically, by building the dataset associated with HV behaviors, a long short-term memory (LSTM) predictor is established to recover the problematic HV messages (i.e., position, velocity, and heading) caused by the nonideal information environment. Furthermore, based on the boundary of the HV states, an evaluation and correction (EC) method is presented to suppress the adverse impacts of prediction failures. Then, a combined longitudinal and lateral controller cooperating with the LSTM predictor and EC method is developed to enhance the stability and safety of the mixed vehicle platoon under the nonideal information environment. In a theoretical analysis, the relatedness between the asymptotic stability and string stability of the platoon and predictor accuracy is strictly proved. Finally, comparative experiments verify the effectiveness of the proposed control strategy by employing driver-in-the-loop simulations. [ABSTRACT FROM AUTHOR]

This article proposes a novel fixed-time converging forward-backward-forward neurodynamic network (FXFNN) to deal with mixed variational inequalities (MVIs). A distinctive feature of the FXFNN is its fast and fixed-time convergence, in contrast to conventional forward-backward-forward neurodynamic network and projected neurodynamic network. It is shown that the solution of the proposed FXFNN exists uniquely and converges to the unique solution of the corresponding MVIs in fixed time under some mild conditions. It is also shown that the fixed-time convergence result obtained for the FXFNN is independent of initial conditions, unlike most of the existing asymptotical and exponential convergence results. Furthermore, the proposed FXFNN is applied in solving sparse recovery problems, variational inequalities, nonlinear complementarity problems, and min–max problems. Finally, numerical and experimental examples are presented to validate the effectiveness of the proposed neurodynamic network. [ABSTRACT FROM AUTHOR]

In practice, there are many physical systems that can have only positive inputs, such as physiological systems. Most conventional control methods cannot ensure that the main system input is positive. A positive input observer‐based controller is designed for an intravenous glucose tolerance test model of type 1 diabetes mellitus (T1DM). The backstepping (BS) approach is employed to design the feedback controller for artificial pancreas (AP) systems, based on the Extended Bergman's Minimal Model (EBMM). The EBMM represents the T1DM in terms of the blood glucose concentration (BGC), insulin concentration, and plasma level and the disturbance of insulin during medication due to either meal intake or burning sugar by doing some physical exercise. The insulin concentration and plasma level are estimated using observers, and these estimations are applied as feedback to the controller. The asymptotic stability of the observer‐based controller is proved using the Lyapunov theorem. Moreover, it is proved that the system is bounded input‐bounded output (BIBO) stable in the presence of uncertainties generated by uncertain parameters and external disturbance. For realistic situations, we consider only the BGC to be available for measurement and additionally inter‐and intra‐patient variability of system parameters is considered. [ABSTRACT FROM AUTHOR]

This brief proposes an antisaturation adaptive fixed-time sliding mode controller for a class of second-order nonlinear systems with the saturation constraint. Based on the developed fixed-time stable system, a novel nonsingular fast fixed-time sliding mode surface is designed to circumvent the singularity and acquire a faster convergence rate. To avoid choosing inappropriate control gain, an adaptive mechanism is designed. Furthermore, an auxiliary compensation system is developed to solve the saturation constraint. It is rigorously proved that the system is practical fixed-time stable and the tracking error will fast converge to bounded regions within a fixed time. Finally, the obtained results are employed to realize the quadrotor attitude stabilization, and superior control performance can be illustrated via simulations and experiments. [ABSTRACT FROM AUTHOR]

This article considers the decentralized stabilization problem of continuous-time nonlinear systems subject to unmatched interconnections and asymmetric input constraints. Initially, with the nonquadratic value functions being introduced to constrained auxiliary subsystems, the decentralized stabilization problem is converted into an array of nonlinear optimal control problems. It is proved that all solutions of these nonlinear optimal control problems together assure asymptotic stability of the entire system. Then, in the framework of adaptive critics, the critic-only architecture is built to solve the Hamilton–Jacobi–Bellman equations associated with these solutions. The critic-only architecture is implemented via critic neural networks (NNs) with their weight vectors being tuned through an improved gradient descent method. A remarkable feature of the present gradient descent approach is that it simultaneously utilizes previously stored and instantaneous state data, which makes the persistence of excitation conditions relaxed. After that, with Lyapunov’s techniques being employed, asymptotic stability of the closed-loop auxiliary subsystems and uniform ultimate boundedness of the critic NNs’ weight estimation errors are demonstrated. Finally, simulations of an unmatched interconnected nonlinear plant are provided to validate the present decentralized control method. [ABSTRACT FROM AUTHOR]

This article investigates the $\eta$ -exponential stabilization and positivity of the controlled discrete-time polynomial fuzzy model (DPFM) system with time delay. $\eta$ -exponential polynomial copositive Lyapunov candidate is proposed to detect the system stability under the convergence (decay) rate. Static output feedback fuzzy controller is then synthesized to assure the DPFM closed-loop system with time delay. We propose Chebyshev membership functions (CMFs) to approach the primary membership function and attenuate the conservativeness of $\eta$ -exponential stability formulation and positivity analysis. Chebyshev norm approximation error is utilized to introduce the error between CMFs and primary membership functions using slack matrices. A numerical example is presented to validate the proposed methods. [ABSTRACT FROM AUTHOR]

In order to improve the robust stability of the grid-connected inverter of wind power or photovoltaic power generation while connected to a weak power-grid, the robust model of grid-connected inverter under weak power-grid is established, and the influence mechanism of power-grid impedance and voltage distortion on the stability and current quality of grid-connected inverter is analyzed. On this basis, an adaptive robust H∞ control method is proposed, in which there is no need to online measure the power-grid impedance, and the control parameters do not change with the change of the power-grid impedance. Then, the calculation method of each reference quantity and the design method of control parameters are introduced. Finally, an experimental platform is built, and the correctness and effectiveness of the theoretical analysis and the proposed control method are verified by experiments. Compared with other control methods, the adaptive robust H∞ control method realizes the stability of the system when the power-grid impedance varies in a wide range, which optimally restrains the power-grid voltage distortion and improves the quality of grid-connected current. [ABSTRACT FROM AUTHOR]

Unmatched disturbances affect most of the mechanical systems, and finding conditions in the controllers for its attenuation still represent a challenge. We present sufficient conditions to guarantee asymptotic stability of single-input single-output systems driven by integral fuzzy-based sliding-mode control. The stability analysis made in the Lyapunov framework gives the tuning conditions of the fuzzy system to preserve the robustness against bounded persistent, matched, and unmatched disturbances. The theoretical results are numerically and experimentally validated in a one-link pendulum. [ABSTRACT FROM AUTHOR]

In this article, direct adaptive actuator failure compensation control is investigated for a class of noncanonical neural-network nonlinear systems whose relative degrees are implicit and parameters are unknown. Both the state tracking and output tracking control problems are considered, and their adaptive solutions are developed which have specific mechanisms to accommodate both actuator failures and parameter uncertainties to ensure the closed-loop system stability and asymptotic state or output tracking. The adaptive actuator failure compensation control schemes are derived for noncanonical nonlinear systems with neural-network approximation, and are also applicable to general parametrizable noncanonical nonlinear systems with both unknown actuator failures and unknown parameters, solving some key technical issues, in particular, dealing with the system zero dynamics under uncertain actuator failures. The effectiveness of the developed adaptive control schemes is confirmed by simulation results from an application example of speed control of dc motors. [ABSTRACT FROM AUTHOR]

Normally, achieving asymptotic convergence in the presence of unknown arbitrarily bounded external disturbance requires noncontinuous control signals. In this article, an adaptive backstepping controller for a class of incommensurate fractional-order nonlinear systems with parametric uncertainties and external time-varying disturbance is proposed to realize asymptotic perfect output tracking. Appropriate adaptive laws are designed to deal with the uncertainties and unknown bounded disturbance. In the designed adaptive backstepping control scheme, an auxiliary function is adopted to obtain a smooth control signal. It is theoretically shown that asymptotic output tracking to a given reference signal is achieved while ensuring global system stability in the sense that all the closed-loop signals are bounded. Simulation and experimental studies demonstrate the effectiveness of the proposed backstepping control scheme. [ABSTRACT FROM AUTHOR]

This article focuses on the conservativeness issue of the existing Lyapunov method for linear time-invariant (LTI) nabla fractional-order systems and proposes a converse Lyapunov theorem to overcome the conservative problem. It is shown that the LTI nabla fractional-order system is asymptotically stable if and only if there exist a positive-definite Lyapunov function whose first-order difference is negative definite. After developing a systematic scheme to construct such Lyapunov candidates, the Lyapunov indirect method is derived for the nonlinear system. Finally, the effectiveness and practicability of the proposed methods are substantiated with four examples. [ABSTRACT FROM AUTHOR]

Virtual synchronous machines are inverters with a control algorithm that causes them to behave towards the power grid like synchronous generators. A popular way to realize such inverters are synchronverters. Their control algorithm has evolved over time, but all the different formulations in the literature share the same “basic control algorithm”. We investigate the equilibrium points and the stability of a synchronverter described by this basic algorithm, when connected to an infinite bus. We formulate a fifth order model for a grid-connected synchronverter and derive a necessary and sufficient condition for the existence of equilibrium points. We show that the set of equilibrium points with positive field current is a two-dimensional manifold that can be parametrized by the corresponding pair $(P,Q)$ , where $P$ is the active power and $Q$ is the reactive power. This parametrization has several surprizing geometric properties, for instance, the prime mover torque, the power angle and the field current can be seen directly as distances or angles in the $(P,Q)$ plane. In addition, the stable equilibrium points correspond to a subset of a certain angular sector in the $(P,Q)$ plane. Thus, we can predict the stable operating range of a synchronverter from its parameters and from the grid voltage and frequency. Our stability result is based on the intrinsic two time scales property of the system, using tools from singular perturbation theory. We illustrate our theoretical results with two numerical examples. [ABSTRACT FROM AUTHOR]

In this article, a new approach is proposed for stability analysis and controller design of nonlinear discrete-time positive systems by means of the Takagi–Sugeno fuzzy model. The closed-loop stability and the positivity constraint are guaranteed by synthesizing a linear co-positive Lyapunov function and by applying the parallel distributed compensation controller. In contrast to the state-of-the-art approaches for ensuring the $\ell _{1}$ -stability of the positive system which are based on bilinear matrix inequalities, the proposed optimal robust control design under $\ell _{1}$ -induced performance is derived based on linear programming framework. It has been shown that the computational complexity of the proposed optimization problem can be effectively reduced. Finally, a numerical example and the Leslie population model are adopted to show the capabilities of the proposed method. [ABSTRACT FROM AUTHOR]

This article addresses the problem of global stabilization of continuous-time linear systems subject to control constraints using a model-free approach. We propose a gain-scheduled low-gain feedback scheme that prevents saturation from occurring and achieves global stabilization. The framework of parameterized algebraic Riccati equations (AREs) is employed to design the low-gain feedback control laws. An adaptive dynamic programming (ADP) method is presented to find the solution of the parameterized ARE without requiring the knowledge of the system dynamics. In particular, we present an iterative ADP algorithm that searches for an appropriate value of the low-gain parameter and iteratively solves the parameterized ADP Bellman equation. We present both state feedback and output feedback algorithms. The closed-loop stability and the convergence of the algorithm to the nominal solution of the parameterized ARE are shown. The simulation results validate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

Virtual Coupling (VC) is regarded as a breakthrough to the traditional train operation and control for improving the capability and flexibility in railways. It brings benefits as trains under VC are allowed to operate much closer to one another, forming a virtually coupled train set (VCTS). However, the safe and stable spacing between trains in the VCTS is a problem since there are no rigid couplers to connect them into a fixed formation, especially in high-speed scenarios. Due to the close spacing, the interference between trains becomes non-negligible as various maneuvers of the preceding train can significantly affect driving behaviors of the following train; this results in fluctuating spacing and therefore an unstable VCTS. Aiming at minimizing the interference and maintaining constantly safe spacing between trains in the VCTS, this paper presents a distributed model predictive control (DMPC) approach for solving the high-speed VCTS control problem. Particularly, the proposed control method focuses on the feasibility and stability of this problem, with considerations of the coupled constraint of safety braking distance and the individual constraints of speed limit variations and restricted traction/braking performance. To guarantee feasibility and stability, the terminal controller and invariant set of the DMPC are designed. For rigor, sufficient conditions of feasibility and stability are mathematically proved and derived. Based on the data of the Beijing-Shanghai high-speed railway line, numerical experiments are conducted to verify the correctness of derived sufficient conditions and the effectiveness of the proposed control method under interference and disturbances. [ABSTRACT FROM AUTHOR]

An approach is presented to analytically characterize the asymptotic stability of a linearized large-scale connected vehicle-velocity dynamics in ring configuration and with communication, sensor, and human reaction delays. Insights are obtained on how certain eigenvalues associated with the model affect stability on the plane of model parameters. Comparing with the traditional model where connectedness between vehicles is removed except between consecutive vehicles, one renders larger stability regions, which can be matched by using weaker gains in the connected vehicle model. Results can inform future studies regarding trade-offs between the advantages that the connected vehicles offer and the use of high/weak gains to render certain degree of stability robustness in model parameters against time delays. [ABSTRACT FROM AUTHOR]

This article considers local stability analysis and local stabilization of discrete-time nonlinear systems represented by Takagi–Sugeno fuzzy models. Conditions are established using Lyapunov functions and controller gains that depend also on past samples. Together with the stability and design conditions, an estimate of the region of attraction is also determined. The developed conditions are discussed and illustrated on several examples. [ABSTRACT FROM AUTHOR]

Sampled-data state feedback control with stochastic sampling periods for Boolean control networks (BCNs) is investigated in this article. First, based on the algebraic form of BCNs, stochastic sampled-data state feedback control is applied to stabilize the considered system to a fixed point or a given set. Two kinds of distributions of stochastic sampling periods are considered. First, the distribution of sampling periods is assumed to be independent identically distributed (i.i.d.) in the range of any positive integers and the second distribution of sampling periods is assumed to follow an infinite Markov process. A BCN with infinite stochastic sampling periods proves to be equivalent to a finite stochastic switched system, based on which, necessary and sufficient conditions are given to guarantee the stabilization and set stabilization of the BCN with stochastic sampling periods. For the first one, two algorithms are given to guarantee the stabilization and set stabilization of the considered system. For the second one, necessary and sufficient conditions are all presented in the linear programming form. Examples are listed to show the effectiveness of our results. [ABSTRACT FROM AUTHOR]

Signed networks admitting antagonistic interactions among agents may polarize, cluster, or fluctuate in the presence of time-varying communication topologies. Whether and how signed networks can be stabilized regardless of their sign patterns is one of the fundamental problems in the network system control areas. To address this problem, this paper targets at presenting a self-appraisal mechanism in the protocol of each agent, for which a notion of diagonal dominance degree is proposed to represent the dominant role of agent’s self-appraisal over external impacts from all other agents. Selection conditions on diagonal dominance degrees are explored such that signed networks in the presence of directed time-varying topologies can be ensured to achieve the uniform asymptotic stability despite any sign patterns. Further, the established stability results can be applied to achieve bipartite consensus tracking of time-varying signed networks and realize state-feedback stabilization of time-varying systems. Simulations are implemented to verify our uniform asymptotic stability results for directed time-varying signed networks. [ABSTRACT FROM AUTHOR]

We present a reset control approach to achieve setpoint regulation of a motion system with a proportional-integral-derivative (PID)-based controller, subject to Coulomb friction and a velocity-weakening (Stribeck) contribution. While classical PID control results in persistent oscillations (hunting), the proposed reset mechanism induces asymptotic stability of the setpoint and significant overshoot reduction. Moreover, robustness to an unknown static friction level and an unknown Stribeck contribution is guaranteed. The closed-loop dynamics are formulated in a hybrid systems framework, using a novel hybrid description of the static friction element, and the asymptotic stability of the setpoint is proven accordingly. The working principle of the controller is demonstrated experimentally on a motion stage of an electron microscope, showing superior performance over classical PID control. [ABSTRACT FROM AUTHOR]

A well-known problem with distance-based formation control is the existence of multiple equilibrium points not associated with the desired formation. This problem can be potentially mitigated by introducing an additional controlled variable. In this article, we generalize the distance + angle-based scheme for 2-D formations of single-integrator agents by using directed graphs and triangulation of the n-agent formation. We show that under certain conditions on the control gains and desired formation shape, our controller ensures the asymptotic stability of the correct formation for almost all initial agent positions. [ABSTRACT FROM AUTHOR]

This article proposes a new implicit function-based adaptive control scheme for the discrete-time neural-network systems in a general noncanonical form. Feedback linearization for such systems leads to the output dynamics nonlinear dependence on the system states, the control input, and uncertain parameters, which leads to the nonlinear parametrization problem, the implicit relative degree problem, and the difficulty to specify an analytical adaptive controller. To address these problems, we first develop a new adaptive parameter estimation strategy to deal with all uncertain parameters, especially, those of nonlinearly parameterized forms, in the output dynamics. Then, we construct a key implicit function equation using available signals and parameter estimates. By solving the equation, a unique adaptive control law is derived to ensure asymptotic output tracking and closed-loop stability. Alternatively, we design an iterative solution-based adaptive control law which is easy to implement and ensure output tracking and closed-loop stability. The simulation study is given to demonstrate the design procedure and verify the effectiveness of the proposed adaptive control scheme. [ABSTRACT FROM AUTHOR]

The ongoing efforts by many countries worldwide to increase the share of renewable energy sources in power generation has changed the nature of existing power grids and introduced numerous stability-related issues. To address these problems, more extensive and detailed stability analysis studies are therefore needed. Driven by this need, in this article, we present a passivity-based framework for stability analysis and control design that allows more accurate modeling of both the network and the power system components while facilitating the derivation of completely decentralized stability results. In particular, the proposed approach relies on the formulation of the network as a dynamical multivariable system, which is shown to be passive, even when the network’s dynamic and lossy nature are taken into account. The application of decentralized passivity conditions on bus dynamics is then further exploited, together with the incorporation of more accurate dynamical models for the power system components, to guarantee the asymptotic stability of the interconnected system. Moreover, we discuss the opportunities provided by the proposed approach regarding the incorporation of higher order dynamics, the derivation of significant stability results in a completely decentralized manner and the design of effective distributed control mechanisms. These opportunities are finally verified through the design of a demand-side voltage droop controller and several dynamic simulations on two typical test systems. [ABSTRACT FROM AUTHOR]

This article addresses the problem of finite-time stabilization for a class of high-order nonlinear stochastic systems with asymmetric output constraints. A novel barrier Lyapunov function (BLF) is first presented to handle such asymmetric constraints. Further, based on the proposed BLF and the adding a power integrator technique, a controller design approach is developed by the backstepping method. It can be rigorously proved that the designed controller can not only make the system states finite-time converge to the origin in probability but also ensure that the constraint on system output is not violated. Another novelty of this approach is that it is a unified tool owing to its simultaneous application to the systems without output constraints. Finally, the validity of the proposed scheme can be verified by a simulation example. [ABSTRACT FROM AUTHOR]

Rectified linear unit (ReLU) networks have become widely used in machine learning and automated inference using neural networks. Various forms of hardware accelerators based on ReLU networks have also been under development. In this brief, the stability problem in analog ReLU networks is addressed. Using the Lyapunov stability theory, it is shown that the origin of an unforced, analog ReLU dynamical system is globally asymptotically stable if the induced Euclidean norm of its connectivity matrix is less than one. An example is given to demonstrate that this upper bound is the best that can be achieved. In particular, the stability result holds for the case of a nonsymmetric connectivity matrix as may occur in some mathematical models of neurobiology. [ABSTRACT FROM AUTHOR]

In this article, a novel nonlinear droop control method is proposed for three-phase grid-supporting inverters that rigorously guarantee limited rms value of the inverter current and closed-loop system stability under both normal grid conditions and balanced voltage sags. Contrary to the traditional dq frame approaches that align the inverter output voltage with the d-axis, the proposed controller aligns the inverter current with the d-axis resulting in the desired current limitation and detailed closed-loop system stability conditions. Inspired by the recently presented state-limiting PI controller and using nonlinear invariant set theory, it is rigorously proven that the rms value of the inverter current is always limited below a given value, even during transients or faults, without requiring additional adaptive saturation units, as commonly applied in conventional approaches. Furthermore, analytic conditions for the controller parameter selection are provided to ensure asymptotic stability for the entire closed-loop grid supporting inverter for the first time without depending on particular values of the filter and line parameters. To verify the effectiveness of the proposed controller compared to existing current-limiting control methods, extensive simulation and experimental results of a three-phase inverter are provided under a normal grid and under different balanced voltage sag scenarios. [ABSTRACT FROM AUTHOR]

This article contains a novel approach to dc–dc converter nonlinear control design, working on continuous conduction mode. In particular, the problem of instability induced by constant power loads is addressed. The proposed setting is based on the use of lifted models in terms of power and energy, obtained from voltage/current observable nonlinear transformations. We show that stability can be imposed on lifted models via control design in a much more direct fashion than in traditional current/voltage coordinates. To illustrate the versatility of this approach, we propose three different nonlinear controllers with stabilization capabilities, which exploit the advantages of lifted dynamics in a different way. These strategies are experimentally validated and tested under abrupt and intermittent input voltage and load variations. [ABSTRACT FROM AUTHOR]

This article study the asynchronous control problem for a class of discrete-time Markovian jumping Lur’e systems (MJLSs) over the finite-time interval. The partial accessibility of system modes with respect to the designed controller is described by a hidden Markov model (HMM). The asynchronous control law consists of two parts, i.e., the states and the nonlinearities involved in the dynamics of the controlled system. By selecting the appropriate Lyapunov functional and applying the modified sector condition, the finite-time stabilization conditions under the control constraints are derived. Finally, the effectiveness of the designed method is verified by an illustrative simulation. [ABSTRACT FROM AUTHOR]

This article considers admissibility analysis and stabilization for implicit Markovian jump systems (IMJSs) with retarded discrete-distributed delays. Admissibility analysis is investigated for the unforced delay IMJSs by virtue of reciprocally convex integral inequality technique and Barbalat’s lemma. State feedback controller is designed via the matrix transformation technique to realize the stabilization of the delayed closed-loop IMJSs. By selecting comprehensive L-K functional with modes and delays information, admissibilization conditions are presented in terms of LMIs. Two illustrative examples including an inverted pendulum controlled by a direct current motor (DCMCIP) system are utilized to certify the effectiveness and practicality of the admissibilization technique. [ABSTRACT FROM AUTHOR]

This article investigates the stability analysis problem for cyber-physical systems (CPSs) under denial-of-service (DoS) attacks. Based on the real-time data characterizing the suffered DoS attack, a necessary and sufficient condition for the closed-loop stability in the presence of DoS attacks is provided. Besides, by transforming stability analysis the system under DoS into stability analysis of an auxiliary system, novel sufficient conditions for the closed-loop stability, which can be verified more easily than the necessary and sufficient condition, are provided. Based on the proposed conditions, an online stability monitoring strategy, which triggers an alarm if the closed-loop stability is not guaranteed, is proposed. Finally, two examples are given to illustrate the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

An observer-based dissipativity control for Takagi–Sugeno (T–S) fuzzy neural networks with distributed time-varying delays is studied in this article. First, the network channel delays are modeled as a distributed delay with its kernel. To make full use of kernels of the distributed delay, a Lyapunov–Krasovskii functional (LKF) is established with the kernel of the distributed delay. It is noted that the novel LKF and delay-dependent reciprocally convex inequality plays an important role in dealing with global asymptotical stability and strict $(\mathcal{Q}, \mathcal{S},\mathcal{R})$ - $\alpha $ -dissipativity of the T–S fuzzy delayed model. Through the constructed LKF, a new set of less conservative linear matrix inequality (LMI) conditions is presented to obtain an observer-based controller for the T–S fuzzy delayed model. This proposed observer-based controller ensures that the state of the closed-loop system is globally asymptotically stable and strictly $(\mathcal{Q}, \mathcal{S},\mathcal{R})$ - $\alpha $ -dissipative. Finally, the effectiveness of the proposed results is shown in numerical simulations. [ABSTRACT FROM AUTHOR]

In this article, the control problem for the underactuated dynamic system, which consists of a quadrotor unmanned aerial vehicle and a suspended payload is investigated under the effects of unknown exogenous disturbances. A novel nonlinear controller based on the robust integral of the sign of the error is developed to deal with the position trajectory tracking control and the antiswing control of the suspended payload with the presence of unknown air turbulence. The Lyapunov-based stability analysis is employed to prove the asymptotic stability of the closed-loop system. The real-time experimental results are presented to verify the performance of the proposed control design. [ABSTRACT FROM AUTHOR]

In this paper, a distributed observer-based approach is proposed to control the longitudinal motion of car-like vehicle platoon moving in an urban environment. To the best of our knowledge, this is the first work presenting an observer-based platoon controller that combines the advantages of high traffic capacity and a minimum number of communication links. To achieve a high traffic flow, a constant-spacing policy is used. However, for that policy, to make platoon string stable, the leader information must be broadcast to all the vehicles. Therefore, we propose a control law in which the predecessor position information is acquired by a sensor-based link while a communication-based link is used to obtain the leader information. Then, an observer is designed and integrated into the control law such that the velocity information of the predecessor can be estimated without the need to communicate with the preceding vehicle. For navigation in urban environments, we present a third order platoon model represented in the curvilinear coordinates. Conditions for asymptotic stability and string stability are given considering the vehicle actuator dynamics and the induced network/sensor time delay. Finally, we provide both simulation and real-time results to validate our approach feasibility and to corroborate our theoretical findings. [ABSTRACT FROM AUTHOR]