Command-Filter-Approximator-Based Adaptive Control for Uncertain Nonlinear Systems and Its Application in PMSMs
Jiapeng Liu, Qing‐Guo Wang, Jinpeng Yu
Abstract
We develop a modified adaptive control scheme for uncertain nonlinear systems based on command-filtered backstepping in this study. Our main task is to construct the virtual stabilizing functions in the presence of the uncertain control gain functions. First, the command-filter technique is employed to predict the system performance. Next, a new adaptive control strategy is introduced to stabilize each subsystem. In the final step, the actual stabilizing function is designed by utilizing the hyperbolic tangent function. The proposed strategy overcomes the problem of the input saturation and guarantees the convergence of all the system signals. The simulation study for a numerical nonlinear system and experimental results from a PMSM control platform are presented to validate our control strategy.