Adaptive Control of A Servo System Based on Multiple Models

This paper presents an alternative technology for adaptive control of a DC motor servo system based on multiple models. A dynamic mechanical model of the controlled plant is built, where the unmeasurable variables can be estimated by a filter observer. According to the mechanical model, an adaptive controller is designed. Specific attention is given to the jumping parameters in the control process, which motivate the proposition of multiple models, including fixed models, identified model, and adaptive model, to approximate the global dynamic characteristics of the plant model. A model switching rule is proposed to select the optimal model matching the plant, and the identified and adaptive models are reset when switching occurs, minimizing the effect caused by jumping parameters. Simulation results demonstrate that the introduced scheme is superior to the conventional adaptive control in that it yields a significant improvement of transient stability and response speed as well as steady accuracy, guaranteeing better low-speed performance.