Adaptive optimal dynamic surface control of strict‐feedback nonlinear systems with output constraints

Abstract

Summary In this paper, an adaptive optimal control strategy is proposed for a class of strict‐feedback nonlinear systems with output constraints by using dynamic surface control. The controller design procedure is divided into two parts. One is the design of feedforward controller and the other is the design of optimal controller. To guarantee the satisfaction of output constraints in feedforward controller, nonlinear mapping is utilized to transform the constrained system into an unconstrained system. Neural‐network based adaptive dynamic programming algorithm is employed to approximate the optimal cost function and the optimal control law. By theoretical analysis, all the signals in the closed‐loop system are proved to be semi‐globally uniformly ultimately bounded and the output constraints are not violated. A numerical example illustrates the effectiveness of the proposed scheme.

Fuzzy Observer-Based Dynamic Surface Control for Input-Saturated Nonlinear Systems and its Application to Missile Guidance

“…Control object of this paper is to design an adaptive optimal controller for system given in (1), such that the output y can track the reference signal y d in an optimal manner. Assumption 1 ( [35]): Assume the control gain functions g i (x) = 0, and existing two constants which satisfy 0 < g min < g max , such that g min < g i (x) < g max . Assumption 2: Assume that y d and its time derivativeẏ d satisfy |y…”

“…Noting that (64) contains the term of F , which is different from [20,35,38]. On the one hand, this makes the stability analysis be more challenging; On the other hand, it increases the complexity of the FLS of the adaptive observer.…”

“…3) In this paper, the strict-feedback system is transformed into an output feedback system firstly, then an adaptive observer is constructed to estimate the states. Compared with [9,20,34,35], this paper does not require the whole states of the system are measurable. For missile guidance systems, the benefit is that it can save space inside the warhead and be equipped with other advanced equipment to enhance the missile's power.…”

Adaptive dynamic programming algorithm for uncertain nonlinear switched systems

“…Adaptive dynamic programming has been considered in many situations, such as nonlinear continuous time systems [18], actuator saturation [19], linear systems [20]- [22], output constraint [23]. In the case of nonlinear systems, the algorithm should be implemented based on Neural Networks (NNs).…”

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