Event-triggered-based adaptive decentralized asymptotic tracking control scheme for a class of nonlinear pure-feedback interconnected systems

2021 ◽  
Author(s):  
Xiaoan Wang ◽  
Kun Jiang ◽  
Guangju Zhang ◽  
Ben Niu
Keyword(s):  
Tracking Control ◽  
Interconnected Systems ◽  
Control Scheme ◽  
Asymptotic Tracking ◽  
Event Triggered

Event-triggered-based adaptive command-filtered asymptotic tracking control for flexible robotic manipulators

2021 ◽  
Author(s):  
Tingting Cheng ◽  
Ben Niu ◽  
Guangju Zhang ◽  
Zhenhua Wang ◽  
Peiyong Duan
Keyword(s):  
Tracking Control ◽  
Robotic Manipulators ◽  
Asymptotic Tracking ◽  
Event Triggered

Event-triggered adaptive asymptotic tracking control of uncertain nonlinear systems with unknown dead-zone constraints

2020 ◽  
Vol 386 ◽  
pp. 125528
Author(s):  
Li-Bing Wu ◽  
Ju H. Park ◽  
Xiang-Peng Xie ◽  
Ya-Juan Liu ◽  
Zhi-Chun Yang
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Dead Zone ◽  
Uncertain Nonlinear Systems ◽  
Asymptotic Tracking ◽  
Event Triggered

Asymptotic tracking control scheme for mechanical systems with external disturbances and friction

2010 ◽  
Vol 73 (7-9) ◽  
pp. 1293-1302 ◽  
Author(s):  
Lili Cui ◽  
Huaguang Zhang ◽  
Bing Chen ◽  
Qingling Zhang
Keyword(s):  
Tracking Control ◽  
Mechanical Systems ◽  
External Disturbances ◽  
Control Scheme ◽  
Asymptotic Tracking

scholarly journals Event-Triggered Compound Learning Tracking Control of Nonstrict-Feedback Nonlinear Systems in Sensor-to-Controller Channel

2021 ◽  
Author(s):  
Yingjie Deng ◽  
Tao Ni ◽  
Jiantao Wang
Keyword(s):  
Tracking Control ◽  
Learning Algorithm ◽  
Approximation Error ◽  
Learning Performance ◽  
Time Varying ◽  
Adaptive Model ◽  
Control Laws ◽  
Virtual Control ◽  
Control Scheme ◽  
Event Triggered

Abstract This paper investigates the event-triggered tracking control of the nonstrict-feedback nonlinear system with the time-varying disturbances. While the fuzzy logic systems (FLSs) serve as the approximators to the unknown dynamics, the compound disturbance is comprised of the time-varying disturbance and the approximation error of the FLS. An event-triggered compound learning algorithm is originally developed to accurately estimate the total uncertainties. By referring to an event-triggered adaptive model, the control laws are derived without provoking the problem of "algebraic loop", seeing Remark 3. The command filters are employed to generate the continuous substitutes for both the virtual control laws and their derivatives, so as to solve the recently proposed problem of "jumps of virtual control laws" arising in the backstepping-based event-triggered control (ETC) that functions in the channel of sensor to controller. The triggering condition is constructed to guarantee the similarity between the adaptive model and the original system. While the satisfactory learning performance of the FLSs and the compound disturbances estimation are maintained, the proposed control scheme can guarantee the semi-globally uniformly ultimate boundedness (SGUUB) of all the tracking errors. Finally, a numerical experiment is carried out to exemplify the effectiveness of the proposed control scheme.

Event-Triggered Control of Large-Scale Fuzzy Interconnected Systems

2017 ◽  
pp. 127-175
Keyword(s):  
Control Problem ◽  
Design Problem ◽  
Fuzzy Systems ◽  
Large Scale ◽  
Interconnected Systems ◽  
Sampled Data ◽  
Network Delay ◽  
Transmission Delays ◽  
Control Scheme ◽  
Event Triggered

This chapter studies the event-triggered control problem for large-scale networked fuzzy systems with transmission delays and nonlinear interconnections. Our considered scheme is decentralized event-triggered control in the sense that each subsystem is able to make broadcast decisions by using its locally sampled data when a prescribed event is triggered. We propose two different approaches to solve the co-design problem consisting of the controller gains, sampled period, network delay, and event-triggered parameter in terms of a set of LMIs. Also, we consider a self-triggered control scheme in which the next triggered time is precomputed. Finally, two simulation examples are provided to validate the advantage of the proposed methods.

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