# A Cooperative Control Method for Excavation Support Robot with Desired Position/Posture
## 1 Introduction  
An advanced hydraulic unit is the Excavation Support Robot (ESR). A scenario simulation diagram of the actual operation of the ESR is illustrated in Figure 1. The Adjustment Hydraulic Cylinder (AHC) is composed of a driving system as the ESR power actuator, and the excavation is alternately advanced. In particular, the roof supporting the excavation roadway is irreplaceable. Considering the complex construction road environment and theoperation factors of on-site personnel, ESR is prone to position deviation and posture offset during actual operation. The accumulated consequences of position/posture deviation can easily lead to accidents such as side collision and overturning, which seriously affects mining efficiency and excavation safety. Therefore, whether the position/posture deviation of ESR can be adjusted automatically and quickly to achieve the expected collaborative value has become a key technical problem to be solved urgently. Within the aforementioned context, the deviation of the position and the quick adjustment of the posture are the technical bottlenecks in the field of engineering control. Scholars have achieved fruitful results in the field of coordinated adjustment of position/posture [1,2]. The ESR posture adjustment control algorithm and the integral sliding mode control controller are designed to correct and adjust the position/posture deviation generated by the ESR during the execution of the task, which makes the deviation correction error converge with a negative exponent [3,4]. A memory network neural immune control algorithm for rapid posture adjustment of manned exploration device is proposed [5]. Based on the PID fuzzy algorithm with the optimal deviation path, the overall control scheme has a simple structure and a small amount of calculation, which can realize the optimal control of the position/posture action coordination [6, 7, 8]. A basic posture adjustment algorithm for singular robust path planning is expounded, so as to realize the rapid coordinated adjustment of the basic posture of space satellites [9,10]. A robust model-free adaptive control algorithm and strategy based on adaptive backward technology is discussed, which is oriented to the position/posture adjustment problem of quadrotor aircraft [11,12]. An adaptive sliding mode control method based on the neural network minimum parameter learning method is presented, which improves the convergence speed and better meets the requirements of real-time control of the magnetic levitation system [13]. A new coupled sliding mode control is investigated, which plays an important role in pendulum stability control of an inverted pendulum system [14]. A sliding mode control method for uncertain systems with nonlinear disturbance observer is proposed, which has better integral performance than the basic sliding mode control [15]. Considering the robust sliding surface configuration with the optimal coefficient ratio, a sliding surface algorithm based on the optimal coefficient ratio and an integral sliding mode robust tracking control method are proposed. Even in the presence of design parameter disturbances, the expected sliding surface obtained by this method is robust and optimal [16]. Several optimization algorithms in system optimization are mentioned, which make the control system have higher convergence accuracy and faster convergence speed [17, 18, 19]. Considering the problem of ESR posture adjustment in the process of excavation, an optimized plane linear correction curve model and a double closed-loop posture control strategy are expounded to  
Figure 1: A scenario simulation diagram of the actual operation of the ESR. correct the working posture of the single hydraulic support in the fully mechanized mining face [20; 21; 22]. Faced with complex driving conditions, a motion control algorithm for driving deviation correction is proposed, which can realize online real-time deviation correction position adjustment of control parameters and real-time position control of driving deviation [23; 24; 25].