## 1 Introduction
A comparison of performance for an active antiroll bar (ARB) system using two types of control strategy has been analyzed, where the LQG control strategy has been investigated, and a novel LQG CNF fusion control method has been developed to improve the active antiroll bar system performance for vehicle ride comfort and handling [18]. An observer-based predictive control approach has been proposed to actively compensate random communication constraints in the feedback channel of each agent and between agents in the cooperative output tracking control problem of linear heterogeneous multiagent systems with random communication constraints [19]. Additionally, leader-following consensus of distributed multiagent systems (MAS) under sampled-data control has been investigated [20]. Decentralized tracking control (DTC) problems for input-constrained unknown nonlinear interconnected systems have been solved using event-triggered adaptive dynamic programming [21]. The dynamic event-triggered optimal control problem of discrete-time (DT) nonlinear Markov jump systems (MJSs) has been investigated using policy iteration (PI) adaptive dynamic programming (ADP) algorithms [22]. Their successful experience has given us confidence in designing ground test equipment for space manipulators. We present a control system design method for test equipment that uses a suspension method to balance the gravity of the manipulator. Dynamic compensation of the manipulator's gravity in real time during its movement puts high demands on the test system's dynamic response ability. Suitable control parameters become key to the success of the test system development. Intelligent controller design can improve controller performance under certain conditions. For example, the Ho control of linear discrete-time systems can employ off-policy reinforcement learning to solve the game algebraic Riccati equation online using measured data along the system trajectories [23]. Another approach based on a Q-learning algorithm has been proposed to solve the infinite-horizon linear quadratic tracker (LQT) for unknown discrete-time systems in a causal manner [24]. During the actual debugging process, we discovered that the actuator's lag caused output shaking, which is a common problem in controller design. Scholars often use adaptive methods to solve it. For instance, a novel adaptive nonsingular terminal sliding mode (TSM) control procedure has been proposed for the speedy and finite time stabilization of nonlinear cyber-physical systems (CPSs) dealing with unwanted disturbances, actuator cyberattacks, and time-varying delays [25]. A time-delayed adaptive dynamic programming framework for optimal energy control has also been utilized to reconstruct the state utilizing more comprehensive historical data [26]. These adaptive control methods were applied to enhance the performance of our test system. The papers referenced in this paragraph are only a few examples of the extensive literature available on the topic of adaptive control,which has been demonstrated to have vast potential in improving the performance of complex control systems. In this paper, we designed a ground test system and presented a gravity compensation method for space manipulators, which allows a space manipulator to perform motion tests in the ground gravity environment. We used the adaptive dynamic programming (ADP) method to adjust the controller parameters and proposed a compensation method for the system's lagging. We present our own solution to improve the controller's vibration problem. Our approach involves using ADP to adjust the intelligent parameters of the controller and fine-tune them based on the actual operating effect. The remainder of this paper is as follows. We formulate the problem and the intelligent controller design in Section 2. Then, the simulation results and the results from the real equipment are compared in Section 3. The algorithm in our solution for solving the lagging is discussed in Section 4. Finally, the conclusions are contained in Section 5.