Plant/controller co-design of motor driving systems based on finite-time filtering control

Recently, motor driving systems have been widely applied in the military and industries. Load tracking control is one of the commonly considered issues in such systems. In this study, a plant/controller co-design based on finite-time control was developed for the motor driving system. A finite-time convergent controller was also presented to address the tracking problem in the motor driving system. Because the system state was unknown, a filter was developed to estimate the velocity of the load. The overall system, including the tracking controller and filter, is proven to be finite-time stable. Hence, the upper bound of the convergence time can be determined. To enhance the control performance of the motor driving system, the coupling between plant and controller is considered and a co-design scheme was developed for the motor driving system. First, a combined performance index, which could indicate the largest load with satisfactory control performance, was established. Both the plant and controller parameters were considered in the developed performance index to simultaneously optimize the plant and controller. Through this optimization, the system-level optimality can be determined and a better control performance can be achieved. Moreover, a nested optimization strategy was adopted to simplify the co-design scheme and an adaptive cuckoo search algorithm was used to achieve the co-design result. Through the nested optimization scheme, the controller parameter is optimized in the inner loop and the plant parameter can be optimized in the outer loop. The cuckoo search algorithm exhibits a superior performance because it has fewer parameters that need to be tuned than most existing algorithms. Hence, the co-design problem can be simplified and resolved reliably using the proposed method. Contrastive simulation results indicates the efficacy of the proposed method.