A Novel Parallel Control of Best Weight CMAC and PD for Electric Load Simulator

作者：Han Huatao^*; Yang Bo; Tai Yuying

来源：EPE Journal, 2014, 24(1): 14-20.

DOI：10.1080/09398368.2014.11463871

• Electric load simulator
• CMAC neural network
• Best weight method
• Parallel controller
• Stability
• Surplus torque

This paper considers a novel parallel control algorithm of Best Weight CMAC (Cerebella Model Articulation Controller) and PD (Proportional Derivative) for the actuator electric load simulator of Unmanned Aerial Vehicles (UAVs). Although the conventional parallel controller can effectively reduce loading error and restrain the surplus torque of load simulatot, it could destabilize the system due to overlearning of CMAC when tracking continuously variable loading signals like sinusoidal instructions. The overlearning issue of CMAC is investigated in detail and its divergent trend is predicted. A novel weight updating rule of CMAC, Best Weight Method, is proposed and its convergence is theoretically analyzed. This novel parallel controller can not only retain the normal learning process of conventional parallel controller, but also avoid the overlearning of CMAC. The experimental results have demonstrated that the proposed controller has good robustness, can effectively reduce the loading error, eliminate the surplus torque and assure the stability of system as well.

• 出版日期2014-3
• 单位北京航空航天大学