Journal ArticleDOI
Adaptive Controller Design-Based ABLF for a Class of Nonlinear Time-Varying State Constraint Systems
TLDR
The time-varying asymmetric barrier Lyapunov functions (TABLFs) are employed in each step of the backsstepping design and a novel control TABLF scheme is established to ensure the asymptotic output tracking performance.Abstract:
In this paper, we address an adaptive control problem for a class of nonlinear strict-feedback systems with uncertain parameter. The full states of the systems are constrained in the bounded sets and the boundaries of sets are compelled in the asymmetric time-varying regions, i.e., the full state time-varying constraints are considered here. This is for the first time to control such a class of systems. To prevent that the constraints are overstepped, the time-varying asymmetric barrier Lyapunov functions (TABLFs) are employed in each step of the backsstepping design and we also establish a novel control TABLF scheme to ensure the asymptotic output tracking performance. The performances of the adaptive TABLF-based control are verified by a simulation example.read more
Citations
More filters
Journal ArticleDOI
Adaptive Neural Networks Control Using Barrier Lyapunov Functions for DC Motor System with Time-Varying State Constraints
TL;DR: An adaptive neural network (NN) control approach for a direct-current (DC) system with full state constraints and using Lyapunov analysis, all signals in the closed-loop system are proved to be bounded and the constraints are not violated.
Journal ArticleDOI
Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model
TL;DR: The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.
Journal ArticleDOI
Removing Feasibility Conditions on Tracking Control of Full-State Constrained Nonlinear Systems With Time-Varying Powers
TL;DR: It is rigorously proved that all the signals of the closed-loop system are bounded, full-state constraints are not violated, and the tracking error converges to a compact set around the origin in a finite-time.
Journal ArticleDOI
Neural Networks-Based Active Fault-Tolerant Control for a Class of Switched Nonlinear Systems With Its Application to RCL Circuit
TL;DR: The active fault-tolerant control (FTC) problem for a class of switched nonlinear systems is investigated by using average dwell time method, and the effectiveness of the proposed method is applied to the switched RCL circuit system.
References
More filters
Journal ArticleDOI
Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
TL;DR: This paper presents control designs for single-input single-output (SISO) nonlinear systems in strict feedback form with an output constraint, and explores the use of an Asymmetric Barrier Lyapunov Function as a generalized approach that relaxes the requirements on the initial conditions.
Journal ArticleDOI
Systematic design of adaptive controllers for feedback linearizable systems
TL;DR: A systematic procedure for the design of adaptive regulation and tracking schemes for a class of feedback linearizable nonlinear systems is developed, which substantially enlarges the class of non linear systems with unknown parameters for which global stabilization can be achieved.
Proceedings ArticleDOI
Systematic Design of Adaptive Controllers for Feedback Linearizable Systems
TL;DR: In this paper, a systematic procedure is developed for the design of adaptive regulation and tracking schemes for a class of feedback linearizable nonlinear systems, which are transformable into the so-called pure-feedback form.
Journal ArticleDOI
Adaptive tracking control of uncertain MIMO nonlinear systems with input constraints
TL;DR: The auxiliary design system is introduced to analyze the effect of input constraints, and its states are used to adaptive tracking control design, and the closed-loop semi-global uniformly ultimate bounded stability is achieved via Lyapunov synthesis.
Journal ArticleDOI
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Function
TL;DR: A barrier Lyapunov function (BLF) is introduced to address two open and challenging problems in the neuro-control area: for any initial compact set, how to determine a priori the compact superset on which NN approximation is valid; and how to ensure that the arguments of the unknown functions remain within the specified compact supersets.
Related Papers (5)
Barrier Lyapunov Functions for the control of output-constrained nonlinear systems
Barrier Lyapunov functions for Nussbaum gain adaptive control of full state constrained nonlinear systems
Yan-Jun Liu,Shaocheng Tong +1 more
Barrier Lyapunov Functions-based adaptive control for a class of nonlinear pure-feedback systems with full state constraints
Yan-Jun Liu,Shaocheng Tong +1 more