DDC Control Techniques for Three-Phase BLDC Motor Position Control

Abstract

In this article, a novel hybrid control scheme is proposed for controlling the position of a three-phase brushless direct current (BLDC) motor. The hybrid controller consists of discrete time sliding mode control (SMC) with model free adaptive control (MFAC) to make a new data-driven control (DDC) strategy that is able to reduce the simulation time and complexity of a nonlinear system. The proposed hybrid algorithm is also suitable for controlling the speed variations of a BLDC motor, and is also applicable for the real time simulation of platforms such as a gimbal platform. The DDC method does not require any system model because it depends on data collected by the system about its Inputs/Outputs (IOS). However, the model-based control (MBC) method is difficult to apply from a practical point of view and is time-consuming because we need to linearize the system model. The above proposed method is verified by multiple simulations using MATLAB Simulink. It shows that the proposed controller has better performance, more precise tracking, and greater robustness compared with the classical proportional integral derivative (PID) controller, MFAC, and model free learning adaptive control (MFLAC).

Keywords

• model free adaptive control
• sliding mode control
• model free learning adaptive control
• brushless DC