Adaptive Dynamic Programming Optimal Control Based on Prescribed Performance

This paper proposes a robust tracking control strategy for nonlinear systems based on prescribed performance control (PPC) and adaptive dynamic programming (ADP). By introducing a performance function, the system tracking error is confined within a prescribed dynamic range, thereby strictly guaranteeing the transient response characteristics and steadystate control accuracy of the system. The adopted ADP technique enables online optimization of the control law, eliminating the dependence on an initial stabilizing controller in traditional methods. External disturbances are handled by a disturbance observer. Analysis based on Lyapunov stability theory demonstrates that all signals of the closed-loop system are uniformly ultimately bounded (UUB). To verify the effectiveness of the proposed strategy, it is applied to a DC motor position tracking system. Simulation results show that even under disturbance conditions, the strategy can still strictly maintain the prescribed performance indicators, thus verifying the advantages of the scheme in disturbance rejection capability and performance preservation.