Adaptive PI control with guaranteed transient and steady-state tracking performance for strict feedback systems

In this work, a neuroadaptive proportional integral (PI) control solution for SISO strict feedback nonlinear systems with model uncertainties, capable of guaranteeing prescribed performance bounds, is developed. First, we introduce a special speed function and transform the original error constrained system into an unconstrained one by transformation techniques. Then, by stabilizing the converted system, the error of the original system is guaranteed to evolve within the performance function boundary. And the virtual errors and tracking error converge to the pre-set region of accuracy within user-given time. Lastly, the effectiveness of the proposed control algorithm is verified by simulation.