Adaptive Event-Based Control for Discrete-Time Nonaffine Systems with Constrained Inputs

Abstract

This paper investigates an event-based controller for the near-optimal control policy of nonaffine discrete-time systems with constrained inputs. This algorithm is based on the dual heuristic dynamic programming (DHP) approach. In order to overcome the challenge which is generated by systems with control constraints, a useful nonquadratic performance index is introduced. Besides, the event-based control technique is employed to reduce the computational burden. Meanwhile, a Lyapunov stability analysis is elaborated to prove that the proposed control algorithm can asymptotically stabilize this type of systems. Moreover, we give the stablility condition and the design procedure of the event-based controller. Additionally, we apply three neural networks to realize the present algorithm. Finally, a numerical simulation is conducted to verify the feasibility and performance of the proposed control algorithm.