Adaptive Receding Horizon-Based Self-Triggered Constrained SMC

This brief proposes a novel adaptive receding horizon-based self-triggered constrained sliding mode control (SMC) approach for controlling constrained systems. The approach formulates an optimal control problem (OCP) to enable SMC to satisfy constraints. To reduce the computational burden, self-triggered and adaptive prediction horizon mechanisms are introduced, which respectively decrease the frequency and complexity of the OCP solving. Additionally, a shrinking terminal set is designed to replace the traditional terminal set for OCP, which improves state convergence. Simulation and experiment results demonstrate the effectiveness of the proposed algorithm.