モデル予測制御による高速鉄道車両のアクティブサスペンション

抄録

In this research, we control the active suspension of railway vehicles. Currently the generated force of the actuator in railroad is about 5 kN, so we decide the upper limit and lower limit of the generated force of the actuator by 5 kN, and we will aim for improvement of ride comfort by controlling in it. Model predictive control is handled as control in constraints such as determining the upper and lower limits of the actuator generated force. The model predictive controller consists of optimization and prediction model, and optimization is to minimize or maximize the evaluation function, and the prediction model predicts the future behavior of the controlled object. Solving these optimization problems at high speed and determining the control input at each time is a control method. As a result of simulation by model predictive control, the ride comfort level was 2 (about 83 dB), and good control effect was able to be obtained. As a future task, the model predictive control is a control method that decides the optimal control amount at each time, has a disadvantage that it takes much time to calculate since the amount of calculation is extremely large, so it is necessary to reduce the amount of calculation There is. Also, since the design parameters are very large, it is considered necessary to find out how to determine them.