Optimal control for earth pressure balance of shield machine based on action-dependent heuristic dynamic programming

Abstract

Earth pressure balance (EPB) shield has been widely used in underground construction. The excavation face stability is crucial to avoid the accidents caused by EPB shield tunneling, so that it is very important to propose an effective control method for the earth pressure balance in sealed cabin. Considering the problem that stable automatic control of the earth pressure in shield’s sealed cabin is difficult, an optimal control method of the earth pressure is proposed based on action-dependent heuristic dynamic programming (ADHDP), which can realize online autonomous learning and adaptive control in tunneling process. According to Bellman’s principle of optimality, the cost function with respect to the sealed cabin’s earth pressure is given. In addition, the action network and critic network of ADHDP controller are constructed. The critic network approximates the cost function and feeds error back into the action network. With the goal of minimizing the cost function, the action network utilizes the critic network’s error to optimize screw conveyor speed. The simulation results show that the earth pressure controller based on ADHDP can realize the earth pressure balance control, and the control process is steadier. Moreover, ADHDP controller has good dynamic performance and anti-interference ability.