This paper proposes a new data-driven optimization of integrated control for flexible systems to achieve high-performance automatic control. The integrated control that is composed of feedback control, feedforward control and disturbance observer is adopted in this paper as the control framework that can effectively address the control problems of the flexible system. However, it is difficult to optimize all the parameters of the integrated control, because the number of the parameters to be optimized is larger than the conventional feedback control, which complicates the optimization procedure. In this paper, the optimization procedure of the integrated control as well as the mathematical background of it is proposed. At first, the closed-loop characteristics of the integrated control is analyzed and its convexity with respect to control parameters is theoretically investigated. The proposed optimization method is designed taking into consideration the convexity of the control configuration to guarantee the global optimality of the obtained parameters. Moreover, the proposed method can simultaneously optimize all the parameters of the integrated controller based on the experimental data. The effectiveness of the proposed algorithm is experimentally confirmed using a flexible system under two conditions: 1) change of initial parameters and 2) change of plant conditions. IEEE
Research Interests
Research on Human-friendly motion control; Development of human assistance;rehabilitation system; Design of robotic system based on human musculoskeletal system; Analysis of human walking dynamics and its application to robotics; 친인간적인 운동제어 설계연구; 인간 보조;재활 시스템의 설계 및 개발연구; 인간 근골격계에 기초한 로봇기구 개발연구; 보행운동 분석과 모델 및 로봇기구에의 응용