## 3 Control Strategy  
When testing the power system of a vehicle on the bench, it is the primary task of the bench to exert a load equal to the actual working condition. For the test bench in this paper, the task of the control system is to accurately simulate the driving resistance of the tracked vehicle [33]. In order to achieve this function, the driving moment \(T_{e}\) of the tested vehicle is measured by the torque sensor, and the theoretical rotational speed \(\omega_{em}\) of the driving wheel can be obtained by substituting \(T_{e}\) into Formula (6). When the combined torque of \(T_{e}\) and output torque of the load analog motor makes the system rotate, the current rotational speed \(\omega\) is obtained by the sensors and a controller C is designed to make \(\omega\) infinitely approach \(\omega_{em}\), so that the simulation of vehicle driving resistance can be realized. The system control block diagram is shown in Figure 10, where G(s) and J(s) are the transfer function of the motor and transmission mechanism, respectively. As can be seen from the above figure, the control method is actually used to track the speed response of the system under the current torque. However, in the actual operation process, because the system is affected by environmental factors and friction coefficients at different velocities, a non-linear uncertainty \(\Delta(\mathrm{s})\) exists in its transfer function. In addition, the system loop is also affected by the driving torque \(T_{e}\), which is an external additional torque for the whole load simulation system. [34; 35]. However, in practice, the system is driven by the combined torque of \(T_{e}\) and \(T_{e}\). For the control loop, \(T_{e}\) is not controlled by the system and is controlled by the external controller on the test vehicle or throttle. Therefore, for the load simulation system, \(T_{e}\) is an uncontrollable random variable, and when it changes dramatically, it is very likely that the system will deviate from the target speed. Because of this, when \(\Delta(\mathrm{s})\) changes or \(T_{e}\) mutations occur, the stability of the system is problematic. In this regard, it is necessary to design a controller C which can not only adjust the loading and transmission system, but also respond quickly and follow \(\omega_{em}\) under the action of system disturbance torque. There is an intuitive idea that the robust control method can be used to design the controller C(s) by taking the maximum disturbance and the maximum uncertainty of the test-bed system as the disturbance rejection index of the system and combining it with the tracking requirement of \(\omega_{em}\)[36; 37]. However, for a single controller, the responsiveness and strong anti-jamming ability are contradictory. Therefore, according to the structural invariance principle, the system is designed as a 2-degree-of-freedom loop (2-DOF), as shown in Figure 11. In the figure, \(\xi\) is the sensor noise, \(G_{n}(s)\) is the nominal transfer function of the system, \(G_{n}(s)=G(s)\cdot J(s)\), and Q(s) is the filter to be designed. The disturbance observer (DOB) composed of Q(s) and \(G_{n}{}^{-1}(s)\) in the dashed line frame is used to suppress the disturbance of the system, enhance the robustness of the system, and make the system transfer function close to the nominal transfer function \(G_{n}(s)\). The DOB and the controlled system constitute the inner loop of the system [38]. The outer loop is controlled by controller C. Since the disturbance observer in the inner loop has suppressed the disturbance and noise of the system, the outer loop controller only needs to control the response speed and steady-state error of the system. According to the design requirements and test experience, controller C needs to control the response time of the system within 100 ms and the tracking error within 1%. Figure 10: Control block diagram of the load simulation system.