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
Adaptive Fuzzy Control for Coordinated Multiple Robots With Constraint Using Impedance Learning
TL;DR: This paper investigates fuzzy neural network (FNN) control using impedance learning for coordinated multiple constrained robots carrying a common object in the presence of the unknown robotic dynamics and the unknown environment with which the robot comes into contact.
Journal ArticleDOI
Removing the Feasibility Conditions Imposed on Tracking Control Designs for State-Constrained Strict-Feedback Systems
Kai Zhao,Yongduan Song +1 more
TL;DR: This work constructs a nonlinear state-dependent function that purely depends on constrained states to cope with full state and asymmetric constraints directly and introduces a new coordinate transformation that integrates into each step of dynamic surface control based backstepping design, completely circumventing the demanding feasibility conditions on virtual controllers.
Journal ArticleDOI
Barrier Lyapunov Function Based Learning Control of Hypersonic Flight Vehicle With AOA Constraint and Actuator Faults
TL;DR: This paper investigates a fault-tolerant control of the hypersonic flight vehicle using back-stepping and composite learning and results show that the controller obtains good system tracking performance in the presence of AOA constraint and actuator faults.
Journal ArticleDOI
Adaptive neural network-based control for a class of nonlinear pure-feedback systems with time-varying full state constraints
TL;DR: An adaptive neural network control approach is proposed for nonlinear pure-feedback systems with time-varying full state constraints and all closedloop signals are uniformly ultimately bounded and the output tracking error converges to the neighborhood of zero, which can be verified by using the Lyapunov stability theorem.
Journal ArticleDOI
Adaptive Fuzzy Tracking Control of Flexible-Joint Robots With Full-State Constraints
TL;DR: By combining the method of backstepping design with adaptive fuzzy control approaches, a novel simpler controller is successfully constructed to ensure that the output tracking errors converge to a sufficiently small neighborhood of the origin, while the constraints on the system states will not be violated during operation.
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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