Event-triggered distributed self-learning robust tracking control for uncertain nonlinear interconnected systems

Cui, Lili; Zhang, Yong; Wang, Xiaowei; Xie, Xiangpeng

doi:10.1016/j.amc.2020.125871

Cited by 14 publications

(11 citation statements)

References 36 publications

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“…which have e c = Ĥ by ( 24), (29). Define the weight estimate error Wc = W c − Ŵc , one may conclude that e c = e cH − WT c ∇𝜙 c ( ̇e)ë by combining ( 24), ( 28) with (29).…”

Section: Approximate Solution Of Multiplayer Zero-sum Game Via the Im...mentioning

confidence: 99%

“…which have e c = Ĥ by ( 24), (29). Define the weight estimate error Wc = W c − Ŵc , one may conclude that e c = e cH − WT c ∇𝜙 c ( ̇e)ë by combining ( 24), ( 28) with (29). According to gradient descent approach with objective function E c = 1 2 e 2 c , the update law of the critic NN weights is:…”

Section: Approximate Solution Of Multiplayer Zero-sum Game Via the Im...mentioning

confidence: 99%

“…For zero‐game theory problem, Rizvi et al 28 addressed the problem of finding optimal output feedback strategies for solving linear differential zero‐sum games using a model‐free approach based on ADP. Cui et al 29 proposed self‐learning method to deal with uncertain condition 30 . developed single echo state network to deal with

{H}_{\infty }

control problem.…”

Section: Introductionmentioning

confidence: 99%

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Multiplayer zero‐sum games optimal control for modular robot manipulators with interconnected dynamic couplings

Zhu

Dong

2022

Adaptive Control & Signal

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This article presents a multiplayer zero-sum game optimal control for modular robot manipulators (MRMs) via adaptive dynamic programming (ADP).The dynamic model of MRMs with interconnected dynamic couplings (IDCs) is formulated. The control law and IDC effect are regarded as players in each module. The optimal tracking control problem of the MRM system can be transformed into a multiplayer zero-sum game. Base on ADP algorithm, the Hamilton-Jacobi-Issacs (HJI) equation is solved via critic neural network. Then, the optimal control law can be derivated. The closed-loop robotic system is proved to be asymptotic stable and experiments are conducted to verify the effectiveness of the control method.

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“…which have e c = Ĥ by ( 24), (29). Define the weight estimate error Wc = W c − Ŵc , one may conclude that e c = e cH − WT c ∇𝜙 c ( ̇e)ë by combining ( 24), ( 28) with (29).…”

Section: Approximate Solution Of Multiplayer Zero-sum Game Via the Im...mentioning

confidence: 99%

Section: Approximate Solution Of Multiplayer Zero-sum Game Via the Im...mentioning

confidence: 99%

{H}_{\infty }

control problem.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Multiplayer zero‐sum games optimal control for modular robot manipulators with interconnected dynamic couplings

Zhu

Dong

2022

Adaptive Control & Signal

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“…In recent years, there has been a main focus on nonlinear systems while designing ETC [23][24][25][26][27][28][29][30][31][32]. In [23], a user-adjustable event-triggered mechanism based on the sampled state vectors and backstepping techniques for a nonlinear system was developed to determine the sampling state instants using the negative definite property of the derivatives of Lyapunov functions.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In [29], an ETC scheme with nonlinear model predictive control was designed for an unmanned aerial vehicle. In [30], a self-learning robust ETC scheme was proposed for nonlinear interconnected systems subject to uncertainty. A fuzzy logic-based ETC-SMC was designed for a nonlinear system in [31].…”

Section: Literature Reviewmentioning

confidence: 99%

An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems

et al. 2021

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This paper presents an optimized algorithm for event-triggered control (ETC) of networked control systems (NCS). Initially, the traditional backstepping controller is designed for a generalized nonlinear plant in strict-feedback form that is subsequently extended to the ETC. In the NCS, the controller and the plant communicate with each other using a communication network. In order to minimize the bandwidth required, the number of samples to be sent over the communication channel should be reduced. This can be achieved using the non-uniform sampling of data. However, the implementation of non-uniform sampling without a proper event triggering rule might lead the closed-loop system towards instability. Therefore, an optimized event triggering algorithm has been designed such that the system states are always forced to remain in stable trajectory. Additionally, the effect of ETC on the stability of backstepping control has been analyzed using the Lyapunov stability theory. Two case studies on an inverted pendulum system and single-link robot system have been carried out to demonstrate the effectiveness of the proposed ETC in terms of system states, control effort and inter-event execution time.

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Data‐based robust optimal control of discrete‐time systems with uncertainties via adaptive dynamic programming

Liu

Xing

Chen

et al. 2021

Optim Control Appl Methods

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In this article, a new data-based adaptive dynamic programming algorithm is proposed to solve the optimal control policy for discrete-time systems with uncertainties. Firstly, for uncertain systems, the corresponding Hamiltonian function is designed, and then the robust adaptive dynamic programming algorithm is obtained. Next, by using the input and output data of the system, the data-based Bellman equation is constructed, and the data-based robust adaptive dynamic programming algorithm is derived, which does not require the accurate model of the system. Finally, a simulation example shows the effectiveness of the proposed algorithm.

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Event-triggered distributed self-learning robust tracking control for uncertain nonlinear interconnected systems

Cited by 14 publications

References 36 publications

Multiplayer zero‐sum games optimal control for modular robot manipulators with interconnected dynamic couplings

Multiplayer zero‐sum games optimal control for modular robot manipulators with interconnected dynamic couplings

An Optimized Triggering Algorithm for Event-Triggered Control of Networked Control Systems

Data‐based robust optimal control of discrete‐time systems with uncertainties via adaptive dynamic programming

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