ABSTRACT This paper investigates the inverse optimal control design problem for a class of uncertain switching nonlinear multi‐input multi‐output (MIMO) systems with asymmetric output error constraints and event‐triggered control. Compared to existing work, this study enables the controlled system to achieve optimal control stabilization and guarantees the convergence of the output tracking error to the intended control accuracy range. The unknown nonlinear dynamics are modeled using a neural network, upon which a neural network observer is built. A nonlinear transformation function is designed to deal with the output asymmetric constraint, and an event‐triggering mechanism consisting of an observer‐controller channel is developed. An adaptive neural network event‐triggered output feedback inverse optimization control system is designed inside the backstepping control framework. The primary objectives are to maintain the semi‐global uniform ultimate boundedness (SGUUB) of the closed‐loop system and to achieve the optimum control aim. A simulation example is used to validate the effectiveness of the control strategy.
Yu et al. (Tue,) studied this question.
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