Adaptive Fixed-Time Control of Error-Constrained Pure-Feedback Interconnected Nonlinear Systems

2020 ◽  
pp. 1-12 ◽  
Author(s):  
Qi Zhou ◽  
Peihao Du ◽  
Hongyi Li ◽  
Renquan Lu ◽  
Jun Yang
Keyword(s):  
Nonlinear Systems ◽  
Fixed Time ◽  
Time Control ◽  
Control Of Error ◽  
Interconnected Nonlinear Systems

Adaptive Fuzzy Inverse Optimal Fixed-Time Control of Uncertain Nonlinear Systems

2021 ◽  
pp. 1-1
Author(s):  
Kaixin Lu ◽  
Zhi Liu ◽  
Haoyong Yu ◽  
C. L. Philip Chen ◽  
Yun Zhang
Keyword(s):  
Nonlinear Systems ◽  
Fixed Time ◽  
Uncertain Nonlinear Systems ◽  
Adaptive Fuzzy ◽  
Time Control

scholarly journals Adaptive Fixed-Time Control of Strict-Feedback High-Order Nonlinear Systems

Entropy ◽  
2021 ◽  
Vol 23 (8) ◽  
pp. 963
Author(s):  
Yang Li ◽  
Jianhua Zhang ◽  
Xiaoyun Ye ◽  
Cheng Siong Chin
Keyword(s):  
Nonlinear Systems ◽  
Fixed Time ◽  
High Order ◽  
Convergence Time ◽  
Feedback Form ◽  
Time Control ◽  
Control Scheme ◽  
Lyapunov Stability Criterion ◽  
The Stability ◽  
Strict Feedback

This paper examines the adaptive control of high-order nonlinear systems with strict-feedback form. An adaptive fixed-time control scheme is designed for nonlinear systems with unknown uncertainties. In the design process of a backstepping controller, the Lyapunov function, an effective controller, and adaptive law are constructed. Combined with the fixed-time Lyapunov stability criterion, it is proved that the proposed control scheme can ensure the stability of the error system in finite time, and the convergence time is independent of the initial condition. Finally, simulation results verify the effectiveness of the proposed control strategy.

scholarly journals Event-Triggered Fixed-time Adaptive Fuzzy Control for State-constrained Stochastic Nonlinear Systems Without Feasibility Conditions

2021 ◽  
Author(s):  
Yangang Yao ◽  
Jieqing Tan ◽  
Jian Wu ◽  
Xu Zhang
Keyword(s):  
Nonlinear Systems ◽  
Adaptive Fuzzy Control ◽  
Fixed Time ◽  
Dynamic Surface Control ◽  
Control Technique ◽  
Stochastic Nonlinear Systems ◽  
Stable Theory ◽  
Dynamic Surface ◽  
Time Control ◽  
Event Triggered

Abstract The problem of event-triggered fixed-time control for state-constrained stochastic nonlinear systems is discussed in this article. Different from the Barrier Lyapunov Function (BLF)-based and Integral BLF-based schemes which rely on feasibility conditions (FCs), by introducing nonlinear state-dependent functions , the asymmetric time-varying state constraints are handled without FCs .Combining with the fixed-time stable theory and dynamic surface control technique with fixed-time filter, the fixed-time stability in probability of the closed-loop system is ensured and the problems of “explosion of complexity” and “singularity” are overcome. Furthermore, the novel fixed-time error compensation signals are designed to compensate filtering errors, and event-triggered control technique is used to save network resources. Simulations also illustrate the effectiveness of the proposed method.

scholarly journals Adaptive Fixed-time Control for Nonlinear Systems Against Time-varying Actuator Faults

2021 ◽  
Author(s):  
Yu Mei ◽  
Jing Wang ◽  
Ju H. Park ◽  
Kaibo Shi ◽  
Hao Shen
Keyword(s):  
Nonlinear Systems ◽  
Fault Tolerant ◽  
Tracking Error ◽  
Small Neighborhood ◽  
Fixed Time ◽  
Time Interval ◽  
Time Varying ◽  
Actuator Faults ◽  
Time Control ◽  
Control Scheme

Abstract The adaptive fixed-time control problem for nonlinear systems with time-varying actuator faults is investigated in this paper. A novel adaptive fixed-time controller is designed via combining the Lyapunov stability theory with the backstepping method. It can be adapted to both system uncertainties and unknown actuator faults. Compared with the existing fault-tolerant control schemes subject to actuator faults, the adaptive fixed-time neural networks control scheme can make sure that the tracking error is convergent in a small neighborhood of the origin within a fixed-time interval, and it does not depend on the original states of the system and actuator faults. In light of the control scheme proposed in this paper, the fixed-time stability of the closed-loop system can be guaranteed by theoretical analysis, and a numerical example is provided to verify the effectiveness of obtained theoretical results.

scholarly journals Event-driven NN adaptive fixed-time control for nonlinear systems with guaranteed performance

2021 ◽  
Author(s):  
Xiaona Song ◽  
Peng Sun ◽  
Shuai Song
Keyword(s):  
Neural Network ◽  
Nonlinear Systems ◽  
Tracking Error ◽  
Fixed Time ◽  
Dynamic Surface Control ◽  
Dynamic Surface ◽  
Filter Performance ◽  
Time Control ◽  
The Impact ◽  
Compensation Signal

Abstract This article investigates the adaptive neural network fixed-time tracking control for a class of strict-feedback nonlinear systems with prescribed performance demands, in which radial basis function neural network (RBFNN) is utilized to approximate the unknown items. First, an improved fractionalorder dynamic surface control (FODSC) technique is incorporated to address the issue of the iterative derivation, where a fractional-order filter is adopted to improve the filter performance. What's more, the error compensation signal is established to remove the impact of filter error. Furthermore, a fixed-time adaptive event-triggered controller is constructed to reduce the communication burden, where the Zeno-behavior can also be excluded. Stability results prove that the designed controller not only guarantees all the signals of the closedloop systems (CLS) are practically fixed-time bounded, but also the tracking error can be regulated to a predefined boundary. Finally, the feasibility and superiority of the designed control algorithm are verified by two simulation examples.

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