Research On ATO Speed Optimal Control Based On LQR Algorithm

With the acceleration of urbanization and population growth, people’s travel difficulties are increasingly serious. In order to mitigate and even solve this problem, urban rail transit with large capacity, high efficiency gradually be taken seriously, begin to flourish all over the country. ATO (Automatic Train Operation) subsystem as one of the core part of the ATC (Automatic Train Control) system, reduce the labor intensity of the driver, while increasing the operating efficiency of the train. With the control of ATO, the index of train operation, including punctuality, comfort and energy-saving can be continuous improved by the optimization of control algorithm. Searching for better control algorithms, which can accurately and efficiently control the train’s automatic operation, is a problem that need to be overcome urgently in the industry.This paper based on analyzing research results of current ATO speed controller’s control processes and control algorithms, designed a control algorithm based on the linear quadratic optimal controller LQR (Linear Quadratic Regulator), introduced the advantages of LQR’s easy to control and its being able to take into account the effect of a number of performance indicators to ATO control.Paper started from.the ATO’s principle, function and the performance index of ATO speed controller, researched the delay and interference characteristics of the train, analyzed the traction and braking characteristics of the train, and force analysis of different working conditions based on the single particle train model, then built a dynamics model aiming at the ATO speed controller’s control object. Based on researching the principle of the LQR algorithm and the method of converting the ATO control’s process to optimal control, designed a control algorithm for ATO speed controller based on LQR, and analyzed it compared with classic PID control algorithm. Paper through the simulation results of designed LQR control algorithm and PID control algorithm to verify, analyzed the performance of LQR control algorithm and PID control algorithm from the parking precision, comfort, punctuality and energy-saving indicators. Simulation results show that in the circumstance of the speed detection error is not more than0.6km/h, the LQR algorithm can satisfy the parking error is less than30cm and the travel time error is less than2%, other performance indicators also meet the requirements and are slightly better than the simulation results using the PID algorithm in this paper, achieved the desired purpose of optimizing control.