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This paper is devoted to the problem of quantized control for Markovian jump systems with general transition rates. Meanwhile, the considered system suffers from sensor attack, actuator attack and multiple disturbances. With the help of mode-dependent intermediate observer, the system states and the total disturbances involving both sensor attack and actuator attack are estimated. A mode-dependent composite controller design is constructed to stabilize the overall controlled system. Based on the technique of vertex separators, sufficient conditions are developed in the form of linear matrix inequalities to guarantee the uniformly ultimate boundedness of the closed-loop system. Finally, an application example illustrates the feasibility of the method. [ABSTRACT FROM AUTHOR]

This paper proposes a quantized model-free adaptive iterative learning control (MFAILC) algorithm to solve the bipartite containment tracking problem of unknown nonlinear multi-agent systems, where the interactions between agents include cooperation and antagonistic interactions. To design the controller, the agent’s dynamics is transformed into the linear data model based on the dynamic linearization method, and then a quantized MFAILC algorithm is established based on the quantized values of the relative output measurements. The designed controller only depends on the input and output data of the agent. We prove that under the quantized MFAILC algorithm, the multi-agent systems can achieve the bipartite containment, that is, the output trajectories of followers converge to the convex hull formed by the leaders’ trajectories and the leaders’ symmetric trajectories. Finally, we provide simulations to illustrate the effectiveness of our theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we ponder a kind of discrete-time fractional-order complex-valued fuzzy BAM neural network. Firstly, in order to guarantee the quasi-projective synchronization of the considered networks, an original quantitative control strategy is designed. Next, by virtue of the relevant definitions and properties of the Mittag-Leffler function, we propose a novel discrete-time fractional-order Halanay inequality, which is more efficient for disposing of the discrete-time fractional-order models with time delays. Then, based on the new lemma, fractional-order h-difference theory, and comparison principle, we obtain some easy-to-verify synchronization criteria in terms of algebraic inequalities. Finally, numerical simulations are provided to check the accuracy of the proposed theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, the predefined-time synchronization of inertial memristive neural networks (IMNNs) is explored. Firstly, based on differential inclusion theory, the system with discontinuous connection weights is transformed into a differential inclusion. Secondly, two more general theorems are given to ensure that the zero solution of the error system is stable within a predefined time. Then, four quantized controllers with state variable and its first-order derivative are designed, which effectively avoids the complex analysis caused by reduced-order method and saves communication resources. Furthermore, some criteria of predefined-time synchronization for IMNNs are derived by using non-reduced order method and the new predefined-time stability theorem. Finally, the effectiveness of the obtained results is verified by a numerical simulation. [ABSTRACT FROM AUTHOR]

This paper addresses stability analysis and quantized stabilization of discrete‐time state‐dependent switching affine systems with quantized control inputs and state measurements. The employed controller is in a mode‐dependent affine form to improve the adaptation to the mode of the controlled system and then to acquire less conservative results. The quantization scheme is considered to be logarithmic and synchronized with the mode switching of the switching affine system and the controller. Aiming at achieving lower conservative criteria, a mode‐dependent Lyapunov function incorporating quantization uncertainties is constructed. Correspondingly, the stability analysis and the stabilizing control synthesis are implemented. In the end, the proposed quantized control strategy is applied to a vehicle path‐following problem to exemplify its effectiveness and robustness against data quantization in control inputs and state measurements. [ABSTRACT FROM AUTHOR]

Copyright of Control Theory & Applications / Kongzhi Lilun Yu Yinyong is the property of Editorial Department of Control Theory & Applications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper investigates the problem of quantized cooperative output regulation of linear multi-agent systems with switching graphs. A novel dynamic encoding-decoding scheme with a finite communication bandwidth is designed. Leveraging this scheme, a distributed protocol is proposed, ensuring asymptotic convergence of the tracking error under both bounded and unbounded link failure durations. Compared with the existing quantized control work of MASs, the semi-global assumption of initial conditions is not required, and the communication graph is only required to be jointly connected. Finally, two simulation examples demonstrate the effectiveness of the proposed distributed protocol for bounded and unbounded link failure durations. [ABSTRACT FROM AUTHOR]

Quantized feedback control is fundamental to system synthesis with limited communication capacity. In sharp contrast to the existing literature on quantized control which requires an explicit dynamical model, the authors study the quadratic stabilization and performance control problems with logarithmically quantized feedback in a direct data-driven framework, where the system state matrix is not exactly known and instead, belongs to an ambiguity set that is directly constructed from a finite number of noisy system data. To this end, the authors firstly establish sufficient and necessary conditions via linear matrix inequalities for the existence of a common quantized controller that achieves our control objectives over the ambiguity set. Then, the authors provide necessary conditions on the data for the solvability of the LMIs, and determine the coarsest quantization density via semi-definite programming. The theoretical results are validated through numerical examples. [ABSTRACT FROM AUTHOR]

We investigate the quasi-synchronization of fractional-order complex networks (FCNs) with random coupling via quantized control. Firstly, based on the logarithmic quantizer theory and the Lyapunov stability theory, a new quantized feedback controller, which can make all nodes of complex networks quasi-synchronization and eliminate the disturbance of random coupling in the system state, is designed under non-delay conditions. Secondly, we extend the theoretical results under non-delay conditions to time-varying delay conditions and design another form of quantization feedback controller to ensure that the network achieves quasi-synchronization. Furthermore, the error bound of quasi-synchronization is obtained. Finally, we verify the accuracy of our results using two numerical simulation examples. [ABSTRACT FROM AUTHOR]

This paper considers the fixed-time synchronization of complex-valued coupled networks (CVCNs) with hybrid perturbations (nonlinear bounded external perturbations and stochastic perturbations). To accomplish the target of fixed-time synchronization, the CVCNs can be separated into their real and imaginary parts and establish real-valued subsystems, a novel quantized controller is designed to overcome the difficulties induced by complex parameters, variables, and disturbances. By means of the Lyapunov stability theorem and the properties of the Wiener process, some sufficient conditions are presented for the selection of control parameters to guarantee the fixed-time synchronization, and an upper bound of the setting time is also obtained, which is only related to parameters of both systems and the controller, not to the initial conditions of the systems. Finally, a numerical simulation is given to show the correctness of theoretical results and the effectiveness of the control strategy. [ABSTRACT FROM AUTHOR]

This brief discusses the use of quantized control with actuator saturation to achieve the local synchronization of master–slave fractional-order neural networks (FONNs). A refined sector condition (RSC) is proposed that addresses the issue of the simultaneous quantizer effects and actuator constraints. The RSC is used in the theoretical analysis of local synchronization in drive-response systems. The analysis employs inequality techniques on the Mittag–Leffler function and fractional-order Lyapunov theory. Additionally, this paper presents two convex optimization algorithms that aim to minimize the actuator's costs and expand the admissible initial area (AIA). Finally, this paper employs a three-neuron FONN to demonstrate the efficacy of the proposed methods. [ABSTRACT FROM AUTHOR]

This article considers the bipartite event‐triggered consensus problem for linear multi‐agent systems based on periodic sampling data. The cooperative and antagonistic communications are considered at the same time. The bipartite time‐triggered consensus with maximum sampling period is first addressed. Then, the bipartite periodic event‐triggered control strategy with two event‐triggered mechanisms is designed. Compared with previous control schemes, the proposed control method can realize intermittent communication, intermittent controller update and intermittent triggering condition monitoring. Moreover, considering the constraint of limited data rate, a quantized consensus with both state and input quantization is taken into account. The Zeno behavior is completely avoided due to the fact that the sampling time can be taken as the lower bound of trigger interval. Finally, three illustrative examples are provided to demonstrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

An adaptive neural network backstepping quantized control of fractional-order nonlinear systems with asymmetric actuator dead-zone and unknown external disturbance is investigated in this paper. An adaptive NN mechanism is designed to estimate uncertain functions. A command filter is introduced to estimate the virtual control variable as well as its derivative, so that the "explosion of complexity" problem existed in the classical backstepping method can be avoided. To handle the unknown external disturbance, a fractional-order disturbance observer is developed. Moreover, a hysteresis-type quantizer is used to quantify the final input signal to overcome the system performance damage caused by the actuator dead-zone. The quantized input signal can ensure that all the involved signals stay bounded and the tracking error converges to an arbitrarily small region of the origin. Finally, two examples are presented to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents a distributed adaptive quantized bipartite containment neural network control strategy for nonlinear multi-agent systems with sensor faults. The radial basis function neural network is introduced to compensate the uncertainties. The saturation function is employed to achieve the asymmetric hysteresis quantization control, which can effectively eliminate the assumption that the quantizer parameters are bounded. In addition, an adaptive compensation technique is employed to handle the difficulty of sensor faults. Moreover, the second-order tracking differentiator is used to eliminate the repeated differential problem existed in the backstepping technique. Under the proposed control scheme, all signals of the closed-loop multi-agent systems are cooperatively semi-globally uniformly ultimately bounded, and the containment control performance is gained. Finally, two simulation examples are listed to demonstrate the validity of the presented control strategy. [ABSTRACT FROM AUTHOR]

This paper deals with the problems of quasi‐projective synchronization (QPS) and finite‐time synchronization (FTS) for a kind of delayed fractional‐order BAM neural networks (DFOBAMNNs). In order to reach the goals of synchronization and more accurately gauge of settling time and error level, several fresh quantized controllers are structured to make the utmost of confined communication resources. Then, based on the finite‐time theorem, quantized control strategy, Lyapunov function theory and properties of Mittag–Leffler function as well as inequality analysis techniques, some plentiful criteria are formed to set up a relation between control gains and quantization parameters. In addition, the corresponding error bound of QPS and guages of the settling time on FTS are also given. Finally, a few numerical examples are introduced to validate the effectiveness of the presented control protocols. [ABSTRACT FROM AUTHOR]

This paper is devoted to investigating the synchronization of fractional-order output-coupling multiplex networks (FOOCMNs). Firstly, a type of fractional-order multiplex network is introduced, where the intra-layer coupling and the inter-layer coupling are described separately, and nodes communicate with each other by their outputs, which is more realistic when the node states are unmeasured. By using the Lyapunov method and the fractional differential inequality, sufficient conditions are provided for achieving asymptotic synchronization based on the designed adaptive control, where the synchronized state of each layer is different. Furthermore, a quantized adaptive controller is developed to realize the synchronization of FOOCMNs, which effectively reduces signal transmission frequency and improves the effective utilization rate of network resources. Two numerical examples are given at last to support the theoretical analysis. [ABSTRACT FROM AUTHOR]

In this paper, the synchronization of multi-order fractional neural networks (MoFNNs) with time-varying delays is investigated. Two kinds of controls, namely continuous control and quantized control, are introduced respectively to implement the synchronization. Moreover, by virtue of vector Lyapunov functions, sufficient criteria for realizing the synchronization of the MoFNNs with time-varying delays are deduced. The results of this paper cover the synchronization of traditional fractional neural networks with identical derivative order as a special case. Finally, a numerical example with two cases is given to verify the theoretical results. [ABSTRACT FROM AUTHOR]

The finite-time synchronization of fractional-order multi-weighted complex networks (FMCNs) with uncertain parameters and external disturbances is studied. Firstly, based on fractional calculus characteristics and Lyapunov stability theory, quantized controllers are designed to guarantee that FMCNs can achieve synchronization in a limited time with and without coupling delay, respectively. Then, appropriate parameter update laws are obtained to identify the uncertain parameters in FMCNs. Finally, numerical simulation examples are given to validate the correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

This article studies the quantized control problem of a scalar continuous‐time linear system over a digital network. The network is subject to bounded transmission delay and independent and identically distributed packet dropouts. Event‐triggered sampling is implemented in the system. We first derive a lower bound on the necessary bit rate for any event‐triggered strategy by analyzing the evolution of the uncertainty set of the system state. Then we propose a control strategy which combines both event‐triggering and time‐triggering to stabilize the system. Note that our control strategy implements a dynamic encoding policy, under which the number of quantization bits is dependent on dropouts. Although the average bit rate occupied by our control strategy is higher than the obtained lower stabilizing bit rate bound, their gap can arbitrarily approach zero by relaxing the integer requirement of the number of quantization bits. Numerical examples are given to illustrate the derived results. [ABSTRACT FROM AUTHOR]

A novel adaptive quantized predefined-time control scheme is proposed in this brief for a class of uncertain nonlinear strict-feedback systems. Composite state tracking errors and a composite estimation error are utilized in backstepping design with introducing two time-varying tuning functions. It is shown that the output tracking error can be steered to an arbitrarily small neighborhood of the origin within a user-predefined time, which is an exact design parameter. The provided upper bound of settling time is less conservative compared with related studies. A simulation example shows the effectiveness of the control strategy. [ABSTRACT FROM AUTHOR]

In this article, we investigate the quantized control problem of the continuous‐time linear system with performance barrier. The performance of the system is specified by a continuous decaying function. Considering the state quantization in the feedback, a dynamic quantization scheme and a control law with limited bandwidth are developed, such that the closed‐loop system is asymptotically stable and the specified performance barrier is satisfied. Based on the theory of control barrier function (CBF), the analysis on the performance guarantee of the closed‐loop system under quantization is established. Furthermore, the minimal bandwidth for the quantized system with the performance barrier is explicitly given. Finally, the effectiveness of the obtained result is illustrated by an example. [ABSTRACT FROM AUTHOR]

This article studies the $H_{\infty }$ exponential synchronization problem for complex networks with quantized control input. An aperiodic sampled-data-based event-triggered scheme is introduced to reduce the network workload. Based on the discrete-time Lyapunov theorem, a new method is adopted to solve the sampled-data problem. In view of the aforementioned method, several sufficient conditions to ensure the $H_{\infty }$ exponential synchronization are acquired. Numerical simulations show that the proposed control schemes can significantly reduce the amount of transmitted signals while preserving the desired system performance. [ABSTRACT FROM AUTHOR]

This article investigates the problem of quantized fuzzy control for discrete-time switched nonlinear singularly perturbed systems, where the singularly perturbed parameter (SPP) is employed to represent the degree of separation between the fast and slow states. Taking a full account of features in such switched nonlinear systems, the persistent dwell-time switching rule, the technique of singular perturbation and the interval type-2 Takagi–Sugeno fuzzy model are introduced. Then, by means of constructing SPP-dependent multiple Lyapunov-like functions, some sufficient conditions with the ability to ensure the stability and an expected $H_{\infty }$ performance of the closed-loop system are deduced. Afterward, through solving a convex optimization problem, the gains of the controller are obtained. Finally, the correctness of the proposed method and the effectiveness of the designed controller are demonstrated by an explained example. [ABSTRACT FROM AUTHOR]

Summary: The issue of fast finite‐time adaptive control is studied for quantized stochastic nonlinear systems. Unlike the existing works about fast finite‐time control, the input signals are quantized, and the stochastic disturbances and nonlinear functions are unknown. According to universal approximation capacity of fuzzy logic system, combined with backstepping technique, a novel fast finite‐time adaptive fuzzy control strategy of quantized stochastic nonlinear system is proposed. The nonlinear decomposition method is introduced to set up the relationship among the control signals and the quantization signals, which overcomes the technical difficulties result from the piecewise quantization input. The proposed tactics can assure the tracking error situate in a neighborhood of the origin point and the closed‐loop system signals keep bounded. Finally, an algorithm simulation is conducted to test the validity of the method. [ABSTRACT FROM AUTHOR]

This article studies the $\mathcal {H}_{\infty }$ control problem for linear networked and quantized control systems (NQCSs) with both communication delays and random packet losses. To deal with network-induced constraints and random packet dropouts, a novel discrete-time stochastic system model is developed for continuous-time networked control systems, and further overapproximated to a polytopic system with norm-bounded uncertainty. Based on the overapproximated system model, sufficient conditions are established for linear NQCSs in different cases to guarantee both input-to-state stability and $\mathcal {H}_{\infty }$ performance with respect to the network-induced errors. Furthermore, we propose an algorithm to minimize the stability gain and the $\mathcal {H}_{\infty }$ attenuation level simultaneously. Finally, a numerical example is given to illustrate the developed results. [ABSTRACT FROM AUTHOR]

In this article, some new results of quantized discrete feedback control are revealed for stochastic delay systems via discrete-time state and mode observations (DSMO). Particularly, the coefficients of considered hybrid stochastic systems do not satisfy the linear growth condition (LGC). The main emphasis is to design a quantized feedback control law that ensures H ∞ stable and exponentially stable of the integrated systems. Based on DSMO, the desired controller can be fairly constructed. Finally, the correctness of presented results is testified by a numerical case. [ABSTRACT FROM AUTHOR]

This article focuses on static output feedback control for fuzzy Markovian switching singularly perturbed systems (FMSSPSs) with deception attacks and asynchronous quantized measurement output. Different from the previous work, both the logarithmic quantizer and the static output feedback controller are dependent on the operation system; by means of hidden Markov models, their modes run asynchronously with that of FMSSPSs. Additionally, the deception attacks are guided by a Bernoulli variable, and nonlinear characteristics are modeled by the Takagi–Sugeno fuzzy model. By resorting to a mode-dependent Lyapunov functional, several criteria are acquired and strictly $(\mathscr {Q},\mathscr {S},\mathscr {R})\text{--}\gamma$ -dissipative of FMSSPSs can be ensured. Finally, a dc motor model is expressed to illustrate the effectiveness of the asynchronous control scheme. [ABSTRACT FROM AUTHOR]

There is a great potential in small satellite technology for testing new sensors, processes, and technologies for space applications. Antennas need careful design when developing a small satellite to establish stable communication between the ground station and the satellite. This work is motivated by the design of an antenna array for a future rotatorless base station for the VZLUSAT group of Czech nano-satellites. The realized antenna array must cover a relatively broad range of elevation and azimuth angles, and the control must be fast enough to track the satellite in low Earth orbits. The paper deals with possibilities of synthesis of quantized control of the antenna array. It compares quantization influence for well-known deterministic synthesis methods. It shows the method for decreasing computational cost of synthesis using optimization approach and presents the multi-criteria optimization as a tool for reaching required radiation pattern shape and low sensitivity to quantization at the same time. [ABSTRACT FROM AUTHOR]

This article investigates the coordination of a class of underactuated systems subject to limited energy supply and channel bandwidth and aims to stabilize system states and exclude Zeno behaviors simultaneously. First, by means of event-triggered (E-T) and quantized techniques, several novel quantized sampled-data-based E-T schemes are constructed, which only require discrete-time controller updates and partial quantized states, and thus efficiently mitigate the control and communication workloads. Then, in order to further lower the communication consumptions, several new triggered sampled-data-based communication rules under fixed and switched networks are established, where the communications are performed only at some specific instants and, thus, the ideally continuous-time signal transmission among neighbors can be avoided. Note that sufficient criteria for achieving the coordination of the underactuated systems are derived in terms of the Lyapunov–Krasovskii functional method. Finally, numerous simulations are carried out to demonstrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

The quantized feedback control for a type of delayed Markovian jumping singular systems driven by fractional Brownian motions is investigated. Firstly, the input is quantized by a uniform operator consisting of a linear part to deal with system stochastic stability and a nonlinear part to deal with the error caused by the quantizer. Secondly, to deal with the boundedness of fractional Brownian motions, a new type of Lyapunov function dependent of Hurst index is constructed. Then, utilizing generalized Finsler lemma and Gronwall inequality, some new criteria on the singular stochastic finite‐time boundedness are obtained for the considered systems with the designed quantized input. Finally, a numerical example and a DC motor example are presented to verify the effectiveness of the proposed methods and results. [ABSTRACT FROM AUTHOR]

A novel quantization‐based switched second‐order sliding mode control design is considered for nonlinear uncertain systems. A new quantization strategy associated with state‐space partition is utilized to accommodate the control amplitude to different uncertainty levels then the conservatism of the control gain is thus attenuated. Investigating each quantized region, it is obtained that all regions are globally invariant sets which offers a monotonously consecutive decrease of the quantized control amplitude when sliding variable converging to the origin through considered uncertainty levels. To deal with different control objectives, the closed‐loop system performance can be enhanced via adapting the quantization parameters. The finite‐time stability analysis and the effect assessment of quantization parameter on the total convergence time are provided. Simulation shows the efficacy and superiority compared with referenced methods. [ABSTRACT FROM AUTHOR]

A novel integrated quantized- and event-based control (IQEC) scheme for intra-spacecraft with communication-saving ability is proposed to address the attitude tracking control problem. The IQEC scheme reduces the control updating frequency and the data length per transmission based on the event-based control and quantized communication techniques, thus reducing the system communication occupation. By suitable control system configuration, the purpose of communication-saving is achieved, from sensors to the computing unit and from the computing unit to actuators. The proposed algorithm’s effectiveness is verified via numerical simulation that uses a general actuator model with second-order dynamics. [ABSTRACT FROM AUTHOR]

This article studies the quantized feedback stabilization problem for nonlinear control systems with external disturbance. To ensure the transmission data rate as minimal as possible, a coarse quantizer is applied, and the quantization procedure has two stages: zooming‐out stage and zooming‐in stage. To detect the effects of the disturbance and to utilize quantization regions as less as possible, both zooming‐out stage and zooming‐in stage are divided into two substages. Based on the quantization mechanism with four substages, a new control strategy is proposed. Using the proposed control strategy and the state trajectory based method, the state feedback stabilization is studied, and sufficient conditions are established to guarantee input‐to‐input stability of the closed‐loop system. Finally, two numerical examples are presented to illustrate the derived results. [ABSTRACT FROM AUTHOR]

Summary: This article studies the adaptive fuzzy finite‐time quantized control problem of stochastic nonlinear nonstrict‐feedback systems with full state constraints. During the control design process, fuzzy logic systems are used to identify the unknown nonlinear functions, integral barrier Lyapunov functions are employed to solve the state constrained problem. In the frame of backstepping design, an adaptive fuzzy finite‐time quantized control scheme is developed. Based on the stochastic finite‐time Lyapunov stability theory, it can be guaranteed that the closed‐loop system is semiglobal finite‐time stable in probability, and the tracking errors converge to a small neighborhood of the origin in a finite time. Finally, two simulation examples are provided to testify the effectiveness of the developed control scheme. [ABSTRACT FROM AUTHOR]

In this paper, the quantized control of networked control systems under stochastic clock offsets is considered. We assume that the clock offsets are caused by asynchronous clocks between sensors and controllers. A stochastic variable with a specific probability density function is used to describe the stochastic clock offsets. A quantized controller is designed to deal with quantization error such that the corresponding systems are stochastically stable. Finally, two numerical examples are used to show the validity of the proposed design method. [ABSTRACT FROM AUTHOR]

In this paper, the problem of fault tolerant control for spacecraft attitude tracking control system in the presence of actuator faults/failures, quantized control torque and measurement, uncertain inertial matrix and external disturbances is taken into account. The dynamical uniform quantizers are developed to quantize the signals of control torque and measurement, which can reduce the data transmission rate. In combination with the CA and FTC technique, a robust adaptive fault tolerant control scheme is proposed to cope with the effects of quantization errors in control torque and measurement, the unknown actuator faults/failures, uncertain inertial matrix and external disturbances. The developed control strategy combined with quantized control torque and measurement can guarantee the stability of overall closed-loop system and achieve satisfactory attitude tracking performance. Finally, simulation results are presented to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Summary: This article investigates the robust output regulation problem of a class of minimum‐phase linear uncertain systems subject to limited measurement information. A novel dynamic quantized output feedback control law together with a hybrid quantized feedback control policy is developed. By means of Lyapunov analysis, it is shown that the tracking error tends to zero asymptotically in spite of system uncertainties, disturbances, and limited measurement information. In addition, a special case of the main result leads to the solution of the robust stabilization problem of minimum‐phase linear systems subject to system uncertainties, disturbances, and the quantized output. [ABSTRACT FROM AUTHOR]

This research addresses the synchronization of delayed fractional-order memristive neural networks (DFMNNs) via quantized control. The motivations are twofold: (1) the transmitted information may be constrained by limited bandwidths; (2) the existing analysis techniques are difficult to establish LMI-based synchronization criteria for DFMNNs within a networked control environment. To overcome these difficulties, the logarithmic quantization is adopted to design two types of energy-saving and cost-effective quantized controllers. Then, under the framework of sector bound approach, the closed-loop drive-response DFMNNs can be represented as an interval system with uncertain feedback gains. By utilizing appropriate fractional-order Lyapunov functional and some inequality techniques, two LMI-based synchronization criteria for DFMNNs are derived to establish the relationship between the feedback gain and the quantization parameter. Finally, two illustrative examples are presented to validate the effectiveness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

This paper studies the quantized cooperative control problem for multiagent systems with unknown gains in the prescribed performance. Different from the finite-time control, a speed function is designed to realize that the tracking errors converge to a prescribed compact set in a given finite time for multiagent systems. Meanwhile, we consider the problem of unknown gains and input quantization, which can be addressed by using a lemma and Nussbaum function in cooperative control. Moreover, the fuzzy logic systems are proposed to approximate the nonlinear function defined on a compact set. A distributed controller and adaptive laws are constructed based on the Lyapunov stability theory and backstepping method. Finally, the effectiveness of the proposed approach is illustrated by some numerical simulation results. [ABSTRACT FROM AUTHOR]

This paper investigates finite-time (FET) and fixed-time (FDT) synchronization of discontinuous complex networks (CNs) via quantized controllers. These control schemes can take full advantage of limited communication resources. By designing Lyapunov function and using different control schemes, several sufficient conditions are proposed such that the dynamical CNs are able to realize synchronization within a settling time. The settling time is related to the initial values of the considered systems using FET control, while it is regardless of the initial values when a special case of FET control named FDT control is utilized. Moreover, FET and FDT synchronization of discontinuous CNs are also considered via some existing controllers without logarithmic quantization, respectively. Numerical simulations are presented to demonstrate the theoretical results. [ABSTRACT FROM AUTHOR]

The present study proposes a new dynamic two-level quantizer, called as hybrid delta modulator ( Δ H -M), which combines the features of both delta-modulator and delta-sigma modulator. In the transient state, the Δ H -M exhibits the dynamical behaviour of delta modulator (Δ-M) while in steady state, its behaviour is similar to delta-sigma modulator ( Δ Σ -M). This study investigates about various dynamics of the proposed Δ H -M in both continuous and discrete-time domains. The stability conditions of Δ H -M are derived using the theory of sliding and quasi-sliding mode. The theoretical results are validated through extensive simulations. Abbreviations: Δ-M: delta modulator; Δ H -M: hybrid delta modulator; Δ Σ -M: delta sigma modulator; ADC: analogue to digital converter; CT: continuous-time; DAC: digital to analogue converter; DT: discrete-time; NCS: networked control system; QSM: quasi-sliding model; QSMD: quasi-sliding mode domain; SS: steady state; TP: transient process [ABSTRACT FROM AUTHOR]

Copyright of Journal of Zhengzhou University (Natural Science Edition) is the property of Journal of Zhengzhou University (Natural Science Edition) Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Summary: This paper investigates the quantized sliding mode control of Markov jump systems with time‐varying delay. A dynamical adjustment law is explored to quantize the system output. By constructing an observer‐based integral sliding surface, a sliding mode controller is designed to take over the dynamical motion of state estimation and ensure the reachability of sliding surface. A new scaling manner is developed to build the bound between the system output and quantized error. With the help of separation strategies for controller synthesis and general transition probabilities and a lower bound theorem for nonlinear integral terms, a new synthesis method to ensure the required stability and meet the required H∞ performance is proposed in the form of linear matrix inequalities. The validity of the proposed control method is illustrated by a numerical example. [ABSTRACT FROM AUTHOR]

Summary: This paper focuses on the problem of neuroadaptive quantized control for heterogeneous vehicular platoon when the follower vehicles suffer from external disturbances, mismatch input quantization, and unknown actuator deadzone. The PID‐based sliding‐mode (PIDSM) control technique is used due to its superior capability to reduce spacing errors and to eliminate the steady‐state spacing errors. Then, a neuroadaptive quantized PIDSM control scheme with minimal learning parameters is designed not only to guarantee the string stability of the whole vehicular platoon and ultimate uniform boundedness of all adaptive law signals but also to attenuate the negative effects caused by external disturbance, mismatch input quantization, and unknown actuator deadzone. Furthermore, optimizing the interspacing between consecutive vehicles is very important to reduce traffic congestion on highways, and a new modified constant time headway policy is proposed to not only increase traffic density but also address the negative effect of nonzero initial spacing, velocity, and acceleration errors. Compared with most existing methods, the proposed method does not linearize the system model and neither requires precise knowledge of the system model. Finally, the effectiveness and advantage of the proposed method are demonstrated by comparative simulation studies. [ABSTRACT FROM AUTHOR]