Learning observer based and event-triggered control to spacecraft against actuator faults

2018 ◽  
Vol 78 ◽  
pp. 522-530 ◽  
Author(s):  
Chengxi Zhang ◽  
Jihe Wang ◽  
Dexin Zhang ◽  
Xiaowei Shao
Keyword(s):  
Actuator Faults ◽  
Event Triggered

Adaptive neural fault-tolerant control for course tracking of unmanned surface vehicle with event-triggered input

2021 ◽  
pp. 095965182110131
Author(s):  
Guoqing Zhang ◽  
Shen Gao ◽  
Jiqiang Li ◽  
Weidong Zhang
Keyword(s):  
Neural Control ◽  
Fault Tolerant ◽  
Lyapunov Stability Theory ◽  
Actuator Faults ◽  
Closed Loop System ◽  
External Disturbances ◽  
Unmanned Surface Vehicle ◽  
Adaptive Parameters ◽  
Control Gain ◽  
Event Triggered

This study investigates the course-tracking problem for the unmanned surface vehicle in the presence of constraints of the actuator faults, control gain uncertainties, and environmental disturbance. A novel event-triggered robust neural control algorithm is proposed by fusing the robust neural damping technique and the event-triggered input mechanism. In the algorithm, no prior information of the system model about the unknown yawing dynamic parameters and unknown external disturbances is required. The transmission burden between the controller and the actuator could be relieved. Moreover, the control gain-related uncertainties and the unknown actuator faults are compensated through two updated online adaptive parameters. Sufficient effort has been made to verify the semi-global uniform ultimate bounded stability for the closed-loop system based on Lyapunov stability theory. Finally, simulation results are presented to illustrate the effectiveness and superiority of the proposed algorithm.

scholarly journals Event-Triggered Stability Analysis of Semi-Markovian Jump Networked Control System with Actuator Faults and Time-Varying Delay via Bessel–Legendre Inequalities

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16 ◽  
Author(s):  
Hongqian Lu ◽  
Chaoqun Guo ◽  
Yue Hu ◽  
Wuneng Zhou
Keyword(s):  
Control System ◽  
Stability Analysis ◽  
Networked Control System ◽  
Time Varying ◽  
Actuator Faults ◽  
Markovian Jump ◽  
Time Varying Delay ◽  
The Stability ◽  
Varying Delay ◽  
Event Triggered

This paper discusses the stability of semi-Markovian jump networked control system containing time-varying delay and actuator faults. The system dynamic is optimized while the network resource is saved by introducing an improved static event-triggered mechanism. For deriving a less conservative stability criterion, the Bessel–Legendre inequalities approach is employed to the stability analysis and plays a major role. By constructing the enhanced Lyapunov–Krasovskii functional (LKF) relevant to the Legendre polynomials, a stability criterion with lower conservativeness indexed by N is derived, and the conservativeness will decrease as N increases. In addition, a controller is designed. To prove the validity of this paper, numerical examples are provided at the last.

Event-triggered asynchronous H∞ fault-tolerant control for discrete-time Markov jump system with actuator faults

2020 ◽  
pp. 095965182096573
Author(s):  
Ai-Min Wang ◽  
Jian-Ning Li
Keyword(s):  
Markov Models ◽  
Fault Tolerant ◽  
Actuator Faults ◽  
Closed Loop System ◽  
Network Resources ◽  
Markov Jump ◽  
External Disturbances ◽  
Controlled System ◽  
Markov Jump System ◽  
Event Triggered

This article focuses on the design of event-triggered asynchronous [Formula: see text] fault-tolerant controller for Markov jump system subject to actuator faults and external disturbances. The asynchronization phenomenon not only occurs between the controlled system and controller but also exists between the controlled system and faulty actuator, which are portrayed as two corresponding hidden Markov models. Moreover, a mode-dependent event-triggered mechanism is introduced to facilitate network resources utilization. Then, by introducing mode-dependent Lyapunov-Krasovskii functional, a sufficient condition is obtained to guarantee that the closed-loop system is randomly mean square stable with [Formula: see text] performance. Finally, two numerical examples are employed to illustrate the effectiveness of the proposed synthesis scheme.

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