Because of its advantages in long armspread, high mobility and low energy consumption, light and slender structure manipulators are widely used in aerospace, construction, nuclear industry and other fields. However, the tip vibration problem has great influence on the stability of operation. Therefore, the vibration control of light and slender structure manipulator has become a hot research topic at home and abroad. This light and slender structure manipulator is called flexible manipulator by researchers. At present, the research object of flexible manipulator is mainly single link or multi-link flexible manipulator with only rotating joints. But the hybrid-structured flexible manipulator can adapt to a wide range of tasks in complex and compact space, and its motion stability is worth further study. Compared with the single link or multi-link flexible manipulator containing only rotating joints, the hybrid-structured flexible manipulator with both rotating joints and telescopic joints has stronger dynamic coupling, more parameter variables, more complex vibration modes and more difficult control. In this paper, a hybrid-structured flexible manipulator with a rotating joint and a telescopic joint is taken as the research object, and the problems of system modeling, trajectory planning, state estimation and vibration control are studied. The main contents are as follows:
1. Combined with practical application requirements, the research significance of hybrid-structured flexible manipulator is analyzed, and the key problems in vibration suppression control process are summarized. On this basis, the research status of key technologies of flexible manipulator is reviewed, and the research idea of this paper is proposed.
2. In view of the problem of coupling between rigid variable and flexible variable of hybrid-structured flexible manipulator, a modeling method based on decomposition idea is proposed, which can effectively avoid the problem of rigid flexible variable coupling and the difficulty of model solving. Firstly, a flexible manipulator experimental platform with a rotating joint and a telescopic joint is designed and built, and the physical parameters of the experimental platform are determined. In the modeling process, the telescopic joint is decomposed into foundation segment, overlap segment and extension segment, and the system is decomposed into rigid parts and flexible parts. The two parts of rigid and flexible parts are modeled and analyzed respectively. For rigid part, rigid system model is obtained by traditional rigid mechanical analysis method. For the flexible part, the elastic deviation of the flexible part is obtained by the assumed modal method, and the flexible system model is established by the Lagrange equation. By integrating the rigid flexible two part model, a complete dynamic model of the hybrid-structured flexible manipulator is established, and its vibration characteristics are analyzed and discussed.
3. In view of the problem of tip vibration affected by the joint trajectory of hybrid-structured flexible manipulator, a vibration suppression trajectory planning method based on particle swarm optimization algorithm and non-uniform spline interpolation is proposed, which can effectively reduce the tip vibration. In order to improve the search efficiency of optimal vibration suppression trajectories, piecewise functions are used to select non-uniform interpolation points, and interpolation points are initialized based on five polynomial and random normal distribution function. Particle swarm optimization algorithm is used to optimize the increment of each interpolation point. Based on the optimized interpolation points, the new joint trajectories are reconstructed by the three spline function. In the optimization process, the sum of the tip amplitude of each sampling time is taken as the optimization objective function, and the weight factor is defined to coordinate the suppression of the vibration in the motion process and suppress the residual vibration after stopping the motion. Finally, optimal vibration suppression trajectories of each joint are obtained.
4. In view of the problem that the tip state of hybrid-structured flexible manipulator cannot be accurately obtained, a tip state estimation method based on sliding discrete Fourier transform and fuzzy logic adaptive Kalman filter is proposed, which can effectively estimate the tip state and be used in the feedback control process. In order to improve the accuracy of the tip estimation of the hybrid-structured flexible manipulator, the system model is decomposed into a deflection model and an elastic vibration model, and a state measurement system consisting of accelerometer, attitude sensor and encoder is built. The discrete Fourier transform is used to analyze the vibration of the measured signal, and is used to replace the elastic vibration model to obtain the tip vibration state. The deflection model and the improved fuzzy logic adaptive Kalman filter are combined to estimate the vibration equilibrium position. The accurate tip state can be obtained through the state of the tip vibration and the equilibrium position.
5. In view of the difficulty of vibration control of hybrid-structured flexible manipulator, a vibration control method based on reinforcement learning and sliding mode control is proposed, which can effectively track the input position of the tip position and reduce amplitude. In order to track the tip trajectory accurately and suppress the tip vibration, the controller is decomposed into a sliding mode controller based on nominal model and a reinforcement learning controller based on Actor-Critic structure. The driving torque for trajectory tracking and the compensation torque for vibration suppression are respectively obtained. In the sliding mode controller based on nominal model, the nominal model and the measurement feedback signal are used, and the integral sliding mode part is added to improve the robustness of the system. In the reinforcement learning controller based on Actor-Critic structure, the approximate method based on neural network is adopted, and the prioritized experience replay method is introduced to improve the efficiency of neural network training.
Finally, the research results obtained in this paper are summarized, and the future research is prospected.