Event-Triggered Near-Optimal Control of Discrete-Time Constrained Nonlinear Systems With Application to a Boiler-Turbine System

This article presents a novel event-triggered near-optimal control (ETNOC) method for discrete-time (DT) constrained nonlinear systems. First, the tracking error system is constructed to convert the tracking control problem to the regulation problem. By introducing the tracking error system, the asymmetric control constraints design for the original constrained system can be converted to the symmetric control constraints design for the tracking error system. Second, a novel triggering condition is developed using the time-triggered optimal value function and control law. It is proven that the closed-loop system (CLS) is asymptotically stable under the developed ETNOC method, and there exists a predetermined upper bound for the real performance index. Then, to implement the developed ETNOC method, a parallel control approach with neural networks (NNs) and adaptive dynamic programming techniques is proposed to predict the next state of the system and obtain the optimal value function and control law. The stability analysis of the CLS is provided in the consideration of the estimation errors of the NN weights and state. Finally, the effectiveness of the developed ETNOC method is validated by an application to a boiler-turbine system.