| Parallel robots are applied more and more widely in every field of national product because its merit of good carrying capacity, high movement precision, great rigidity and lower movement inertia and so on. 6-PRRS mechanism, as a new parallel mechanism with a special structure, has non-variable length of link and is drived by six linear straight motions, with a single-direction big workspace. It enlarges the workspace of parallel mechanism. The kinematics, dynamics, error analysis, calibration and control method based on the domestic and external theories of parallel robot are discussed and studied deeply.Parallel robot is opposite to series robot in some characteristic. Its inverse kinematics is easier to solve and forward kinematics is harder to solve.After some existent typical methods of solving forward kinematics being analyzed, a new method is brought forward, that adopts neural network combined with quasi-Newton iteration method. Efficiently combination of neural network and quasi-Newton iteration can avoid the complicated computing process of parallel robot forward kinematics solution and the solution is one and only. So enlarges the application range of parallel robot forward kinematics.Parallel robot's dynamic equation is a system with multi variables, serious nonlinearity and multi parameter coupling. So principle of virtual work is used to set up the whole dynamics equation, including each branched chain's inertia and quality, with the parameter varying form actuation motor to each component of the parallel robot. The affection of configuration on joint driving force is considered in this equation. After this, dynamics equation is simplified in terms of actual work condition and it is linearized. This work settles the basis of real-time control.The precision robot can reach is not only relative of controller but also of mechanism error. The errors mainly include components'machining and assembly error and clearance error between hinge and leading screw. In this paper, vector chain method is applied to analysis of the affection to mechanism error on system precision, D-H method based on links'parameters is used to model 6-PRRS parallel robot's kinematics, the method of parameter identification is given and error compensation scheme is proposed, then system calibration is finished by experiments. Because the parallel robot is hard to real-time control in terms of the complication of its dynamics, controller without considering parallel robot's dynamics is studied firstly. Based on discrete scheme, auto disturbance-rejection controller(ADRC) is designed, the coupling of robot dynamics is regarded as disturbance and extended state observer with model compensation function is used to compensate the disturbance. So ADRC on 6-PRRS parallel robot is realized. Simulation results show the ADRC can realize the robot high speed and high precision controlling, satisfy the demand of system performance and the validity and feasibility of this algorithm are proved.In spite of the control algorithm not considering dynamics is simple and easy realized, it has two obvious disadvantages for high speed and high precision control of robot. First, it is difficult to ensure the dynamic and static better quality of controlled robot. Second, the system needs larger control energy. So an adaptive feed forward control method is proposed, this method basing on robot dynamics adopts ideal trajectory on workspace to control robot, its stability is analyzed. The basis is using linear dynamics form, real-time identifying object property change online, then reduceing the affection of dynamics coupled and external disturbance on system to least. The validity of this algorithm is proved by experiments.Finally, simulation and hardware systems are built. The method of ADRC and NNPID is verified in practice. In experiments, 6-PRRS parallel robot can finish high-precision track given trajectory, the system has a strong disturbance- rejection capability. It is indicated from experiments that results about research of 6-PRRS parallel robot are correct and feasible.
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