Switched-observer-based adaptive output-feedback control design with unknown gain for pure-feedback switched nonlinear systems via average dwell time

Chang, Ya Ping; Zhou, Peng; Niu, Ben; Wang, Huanqing; Xu, Ning; Alassafi, Madini O.; Ahmad, Adil M.

doi:10.1080/00207721.2020.1863503

Cited by 64 publications

(36 citation statements)

References 42 publications

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“…During the past decades, switched systems have received much attentions since they are widely applied in engineering practices (see References 1‐6 and the references therein). As a special kind of hybrid systems, switched system consists of a group of subsystems and a switching signal which specifies an active subsystem at each time instant.…”

Section: Introductionmentioning

confidence: 99%

Command filtering‐based adaptive neural network control for uncertain switched nonlinear systems using event‐triggered communication

Chen

Niu

Zhang

et al. 2022

Intl J Robust & Nonlinear

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In this article, a command filtering‐based adaptive event‐triggered neural network control scheme is proposed for a class of uncertain switched nonlinear systems with unknown control coefficient and input saturation. First, radial basis function neural networks are used as function approximators to estimate unknown nonlinear functions. Then, an event‐triggering mechanism based on the tracking error is introduced to avoid the over‐consumption of communication resources. Furthermore, command filters are employed to solve the problem of complexity explosion that exists in conventional backstepping control design, and the error compensation signals are designed to reduce the errors caused by the filters. Considering that the unknown control gain and input saturation exist in many practical applications, a Nussbaum‐type function is thus introduced into the controller design to address these challenging issues. Finally, stability of the closed‐loop system is strictly proven under a standard Lyapunov stability analysis framework. The effectiveness of the proposed control scheme is illustrated by a simulation example.

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Section: Introductionmentioning

confidence: 99%

Command filtering‐based adaptive neural network control for uncertain switched nonlinear systems using event‐triggered communication

Chen

Niu

Zhang

et al. 2022

Intl J Robust & Nonlinear

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“…Nevertheless, control tasks of NCSs often have to be executed over unreliable networks for information transmission. 4 Therefore, solving the problem of limited communication resources and packet dropouts is one of the major concerns in this field of NCSs.…”

Section: Introductionmentioning

confidence: 99%

“…Compared with the conventional point‐to‐point system connection, the NCSs have the advantages of low cost, easy installation and maintenance, which have been applied in many fields, such as electronic information and industrial manufacturing. Nevertheless, control tasks of NCSs often have to be executed over unreliable networks for information transmission 4 . Therefore, solving the problem of limited communication resources and packet dropouts is one of the major concerns in this field of NCSs.…”

Section: Introductionmentioning

confidence: 99%

Output‐based event‐triggered control of networked systems subject to bilateral packet dropouts

Abozinadah

et al. 2022

Math Methods in App Sciences

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In this paper, an output-based event-triggered control problem of discrete-time networked control systems (NCSs) subject to bilateral packet dropouts is investigated. In view of stochastic sequences of packet dropouts in the measurement channels (from sensors to controller) and the control channels (from controller to actuators), the NCS is converted into a closed-loop stochastic parameter system. In the aid of a Lyapunov functional based on stochastic variables, the sufficient conditions on design of a dynamic output feedback control law and bilateral event-triggering conditions are derived to guarantee the exponentially mean-square stability for NCSs. Furthermore, an improved iterative algorithm is given to obtain the output-based control law and event-triggering parameters from a set of nonconvex inequalities. Finally, a numerical example and the corresponding simulation results are given to illustrate the validity and applicability of the developed techniques.

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“…With the developments of networked control systems, 17 more and more attention has been paid to the utilization efficiency of network resources. For this reason, the quantization control and event‐based sampling and transmission have been used widely 18‐22 . The event‐triggered‐based control scheme and the quantization control scheme for networked systems have been considered together in Reference 23.…”

Section: Introductionmentioning

confidence: 99%

“…For this reason, the quantization control and event-based sampling and transmission have been used widely. [18][19][20][21][22] The event-triggered-based control scheme and the quantization control scheme for networked systems have been considered together in Reference 23. For switched systems with quantization, the problem of filter design has been solved.…”

Section: Introductionmentioning

confidence: 99%

Quantized optimal output feedback control and optimal triggering signal co‐design for unknown discrete‐time nonlinear systems

Han

Hao

et al. 2022

Optim Control Appl Methods

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A problem of optimizing the cost function incorporated into the transmission cost is proposed for completely unknown discrete-time systems in this article. At first, a switched system containing two modes is formulated based on whether the triggering is executed or not, and the corresponding cost function and output feedback control law are also derived. By giving the formulated switched system, the triggering signal turns into the switching signal and the proposed problem is converted into an optimal control problem for the formulated discrete-time switched system. Secondly, a model network is presented to approximate the system dynamic since the dynamic model is completely unknown. Thirdly, in view of ADP-based optimal control methods of switched systems, critic and actor networks are applied respectively to approximate the optimal cost function and the optimal output feedback control law, and a PI-based online learning method is proposed. When weights of critic and actor networks are obtained and implemented through the proposed online learning method, the optimal triggering signal is derived. Fourthly, the convergent property is given to guarantee the obtained results are optimal. At last, the validity of the proposed method is shown by simulation results of two examples.

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Switched-observer-based adaptive output-feedback control design with unknown gain for pure-feedback switched nonlinear systems via average dwell time

Cited by 64 publications

References 42 publications

Command filtering‐based adaptive neural network control for uncertain switched nonlinear systems using event‐triggered communication

Command filtering‐based adaptive neural network control for uncertain switched nonlinear systems using event‐triggered communication

Output‐based event‐triggered control of networked systems subject to bilateral packet dropouts

Quantized optimal output feedback control and optimal triggering signal co‐design for unknown discrete‐time nonlinear systems

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