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
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Journal ArticleDOI
Robust Adaptive Neural Network Control of Time-Varying State Constrained Nonlinear Systems
Pankaj Mishra,Nishchal K. Verma +1 more
TL;DR: A design strategy for tracking control of time-varying state constrained nonlinear systems in an adaptive framework using the backstepping method and a disturbance observer is proposed to cope with the disturbance along with neural network approximation error and the time derivative of virtual control input.
Journal ArticleDOI
Command-Filtered Backstepping Repetitive Control for a Class of Uncertain Nonlinear Systems Based on Additive State Decomposition
TL;DR: In this article , a command-filtered backstepping repetitive control (RC) method for a class of uncertain nonlinear systems with multiple disturbances, which is based on additive-statedecomposition technique and active disturbance rejection approach, is presented.
Proceedings ArticleDOI
Adaptive Tracking Control for Robotic Manipulators with Time-Varying State Constraints
TL;DR: By employing the backstepping procedure and Lyapunov stability theory, the system stability and desired performance are guaranteed in finite time.
Journal ArticleDOI
Dynamic event-triggered adaptive output feedback control of uncertain nonlinear systems with intermittent observations
TL;DR: In this article , the output feedback adaptive control problem of uncertain nonlinear system with event-sampled states is studied and a novel intermittent state observer is designed to estimate the unmeasurable states.
References
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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.
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