In this paper, a self-tuning rule-based position control algorithm is proposed for DC motors with system parameter estimation using the recursive least squares method. First, a mathematical model of the angular position control of a DC motor was derived. Next, the time-varying parameters including the rotational inertia in the model were estimated using the RLS method along with multiple forgetting factors without prior knowledge of the system. Based on the derived model and the parameter estimation, a sliding mode control algorithm was designed by applying a self-tuning rule that enables the magnitude of the voltage input to be adaptively adjusted for improvement of the energy efficiency. The performance of the designed control algorithm was then experimentally evaluated under several different load conditions. Finally, the evaluation results show that the designed controller achieves a satisfactory capability for a DC motor to deal with both tracking accuracy and energy efficiency without prior knowledge of the system.

本文提出了一种基于规则自调整的位置控制算法，该算法基于递推最小二乘法对系统参数进行估计的直流电动机。首先，推导了直流电动机角位置控制的数学模型。接下来，在没有系统先验知识的情况下，使用RLS方法连同多个遗忘因子一起估算了模型中包括旋转惯性在内的时变参数。基于导出的模型和参数估计，通过应用自调整规则设计了滑模控制算法，该自调整规则可以自适应地调整输入电压的大小，以提高能效。然后，在几种不同的负载条件下，通过实验评估了设计的控制算法的性能。最后，