Research On Position Control Method Of Underactuated Space Manipulator

Underactuated control is an important branch in the field of robotics.It can be used as an emergency control strategy to ensure the normal operation of the system when some specific faults occur.Meanwhile,the mechanical systems in some specific environments have to be designed as underactuated state on account of the compact and flexible requirements.The underactuated robotic systems are characterized by non-holonomic redundancy,which fails to be linearized by full-state strict feedback and cannot be asymptotically stabilized by smooth feedback control laws.Therefore,the research on the position control method of under-actuated manipulator has not only important theoretical and practical significance,but also broad application prospects.The planar manipulator is taken as the research object in this paper to carry out the following research:The optimization methods of fault detection for manipulator based on particle filter algorithm,the hierarchical sliding mode control method for under-actuated manipulator based on fuzzy optimization and the piecewise position control method for planar three-degree-of-freedom under-actuated manipulator based on fuzzy and Lyapunov function.The main research work is as follows:Firstly,the observer-based fault detection method is studied.As the fault threshold is difficult to set,an optimization method based on particle filter algorithm is proposed.Based on the analytic dynamic model of the manipulator,a nonlinear disturbance observer is designed to estimate the motion state of the manipulator and a Lyapunov function is selected to prove its convergence.Then,the estimated result compensates the sliding mode controller to reduce the chattering in the control process.Because of the measurement interference,the joint angle measured by the sensor cannot reflect its actual state.Therefore,the probability of the actual joint angle of the manipulator reaching the desired angle is computed by particle filter algorithm.The fault can be dynamically determined combining with the observation curve.Secondly,the position control method of AP planar manipulator is studied.As the chattering performance in the control process,a hierarchical sliding mode control method based on fuzzy optimization is proposed.The difficulty of active joint driving passive joint is analyzed to provide reference for the choice of base position.The dynamic model is simplified to an affine non-linear system and two joint angles are selected as the control objectives.Then a hierarchical sliding mode controller is designed.The angle and angular velocity of each joint are composed of a subsystem and the equivalent inputs of the two subsystems are solved.The total sliding mode switching surface is constructed by Lyapunov function and the control rate of the manipulator can be obtained.Furthermore,the fuzzy coefficients are added to the switching robustness term.The larger switching term is related to high convergence speed while the smaller switching term can reduce chattering.The simulation shows that the optimized control rate can stabilize the end of the manipulator at the target position and reduce the steady-state time.Thirdly,the position control method of PA planar manipulator is studied.A control method based on fuzzy and Lyapunov function is proposed and a piecewise model is introduced to extend the method to high degree of fieedom.The dynamic model of a planar three degree of freedom manipulator is established to analyze the constraint characteristics between the angles and angular velocities.Then,the control process is decomposed into two control stages and the difference between the end of the manipulator and the target position is taken as the fitness function of the particle swarm optimization algorithm to calculate the target angle of the driving joint.In the first control process,a fuzzy controller is designed to make the second joint reach the target angle,and the third joint control law is obtained by Lyapunov function to keep the initial state.In the second stage,a fuzzy controller is designed to make the third joint reach the target angle,and the second joint control law is obtained by Lyapunov function to keep the target angle.Visual simulation show the manipulator can reach the target position and has good dynamic performance.