Adaptive Fuzzy Output Feedback Control for a Class of Nonlinear Systems With Full State Constraints

Summary This article investigates the issue of adaptive finite‐time tracking control for a category of output‐constrained nonlinear systems in a non‐strict‐feedback form. First, by utilizing the structural characteristics of radial basis function neural networks (RBF NNs), a backstepping design method is extended from strict‐feedback systems to a kind of more general systems, and NNs are employed to approximate unknown nonlinear functions. In addition, the system output is constrained to the specified region by applying the barrier Lyapunov function (BLF) technique. Furthermore, the finite‐time stability of the system is proved by employing the Bhat and Bernstein theorem. As a result, an adaptive finite‐time tracking control scheme for the output‐constrained nonlinear systems with non‐strict‐feedback structure is proposed by applying RBF NNs, BLF, finite‐time stability theory, and adaptive backstepping technique. It is demonstrated the finite‐time stability of the system, the prescribed convergence of the system output and tracking error, the boundedness of adaptive parameters and state variables. Finally, a simulation example is implemented to illustrate the effectiveness of the presented neural control scheme.

Section: Problem Formulations and Preliminariesmentioning

confidence: 99%

Section: Problem Formulations and Preliminariesmentioning

confidence: 99%

Section: System Descriptions and Assumptionsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Adaptive finite‐time tracking control for output‐constrained nonlinear systems with non‐strict‐feedback structure

Yan

Wang

Zhang

2020

“…In the works of Li et al,() for a class of strict‐feedback nonlinear systems with state constraints and input delay, an adaptive neural controller was presented by employing an appropriate BLF and an opportune backstepping design to avoid the constraint violation. An adaptive output‐feedback controller for a class of uncertain nonlinear systems with full sate constraints was proposed by utilizing a BLF to handle the sate constraints and FLSs to model the uncertain nonlinearities in the work of Liu et al However, in the aforementioned works, the research results were obtained under the condition that the considered systems were nonswitched nonlinear systems. There are scarce existing research results for unknown nonlinear switched systems with output constraints.…”

Section: Introductionmentioning

confidence: 99%

Asymmetric prescribed performance‐barrier Lyapunov function for the adaptive dynamic surface control of unknown pure‐feedback nonlinear switched systems with output constraints

Chen

2018

An adaptive dynamic surface control scheme for a class of pure-feedback nonlinear switched systems possessing completely unknown nonlinearities and output constraints is proposed in this paper. By enabling the barriers to vary with prescribed performance functions in time, an asymmetric prescribed performance-barrier Lyapunov function (APP-BLF) is developed to guarantee the prescribed tracking performance simultaneously with constraint satisfaction under arbitrary switching, while the initial conditional requirements are relaxed. To handle the nonaffine problem, an affine variable is constructed to transform pure-feedback systems into a strict-feedback form with the nonaffine and switching properties existing in time-varying bounded parameters by utilizing the mean value theorem at each step of the backstepping design procedure. Next, by incorporating the supremum norm theory, dynamic surface control, and the Nussbaum gain technique, a novel adaptive approach is presented to overcome unknown nonlinearities, unknown control coefficients, and the explosion of complexity. At last, by using the common Lyapunov function approach in combination with the decoupled backstepping method, a common approximation-free adaptive controller is constructed to guarantee that all the signals in the closed-loop system are semiglobally uniformly bounded.Moreover, the proposed controller alleviates the problems of overparameterization and the computational burden. Two simulation studies are conducted to demonstrate the effectiveness, robustness, and applicability of the proposed approach. KEYWORDS adaptive dynamic surface control, asymmetric barrier Lyapunov function (ABLF), common Lyapunov function (CLF), prescribed performance control (PPC), pure-feedback nonlinear switched systems Int

Adaptive fuzzy control for nontriangular form systems with time‐varying full‐state constraints

Zhang

Jiao

2020

SummaryThis article investigates an adaptive fuzzy tracking control problem for a class of nontriangular form systems with asymmetric time‐varying full state constraints. Unknown functions are approximated by the fuzzy logic systems. A domination approach is employed to tackle the nontriangular form structure. Time‐varying asymmetric barrier Lyapunov functions (ABLFs) are adopted to ensure full‐state constraints satisfaction. Based on the backstepping technique and time‐varying ABLFs, an adaptive controller is proposed and guarantees that all the signals in the closed‐loop system are ultimately bounded and the time‐varying full state constraints are met. Simulation examples are presented to further demonstrate the effectiveness of the proposed approach.