Research On Model Predictive Control Algorithm Of An Uncertain Parallel Robot With Actuation Redundancy

Recently, parallel robot has become a new research hotspot. For the reasons of big stiffness, high precision, and strong carrying capacity etc, parallel robot shows the better superiority than serial robot. But parallel robot also have the problems of uncertain, highly nonlinear, control structure complex, large organization coupling internal force and exist singular configuration points in the workspace etc. These problems greatly limits the parallel robot is widely used in reality.Redundant force control technology can solve the parallel mechanism’s problems above effectively. Based on the 6PUS-UPU redundant drive parallel robot as the research object, according to the institution’s relevant problem to study, the main research content is as follows:Firstly, the structure of the 6PUS-UPU parallel robot is analyzed, the dynamic model is got based on KANE method. Then the driving forces are optimized by using the minimum norm solution method, and the driving force of the redundant branch is calculated. The research provides the basis for driving force control performance evaluation of redundant branch.Secondly, for parallel robot parameter time-varying, load disturbance and uncertain problems, establishing the permanent magnet synchronous motor vector control precision model to replace the previous transfer function simplified model. The redundant branch control of parallel robot requires the permanent magnet synchronous motor have good torque tracking and anti-interference ability. Therefore, the model predictive control(MPC) algorithm is introduced in the permanent magnet synchronous motor torque control of the redundant branch, and co-simulation verification is realized by using the software of MATLAB and ADAMS.Finally, for the problems in parallel robot control the model predictive controller has the large amount of calculation and the parameter adjustment complex, puting forward the PID model predictive control algorithm(PPC) and the fuzzy predictive control algorithm(FPC). PPC algorithm can give full play to the advantages of PID control principle simple; parameters adjust convenient and easy for engineering implementation. FPC algorithm is based on predictive control algorithm, and introduce the fuzzy control principle, maximum reduce the length of time domain of control of the predictive control algorithm, and reduce the computing workload, and improve the real-time control ability of the system, so as to improve the dynamic tracking performance and robustness of the original model predictive control system. Then the co-simulation verification is made by using the software of ADAMS/MATLAB for the proposed improved method.Research work of this paper lays the theory foundation for the further research and the engineering application of 6PUS-UPU redundant drive parallel robot. Research results are going to provide theoretical and technical support for actual engineering of heavy equipment precision assembly; capsule and high precision complex curved surface processing.