Research On Trajectory Tracking Control Of Robotic Arm With State Constraint

The manipulator has accelerated the development of modern automation and changed the way of human life.However,with the increase of work complexity,the research of manipulator needs to be improved and perfected continuously.In order to achieve reliable stability and high-precision tracking control requirements,the problems of model uncertainty,interference from human and environment,state constraints and so on can not be ignored.Therefore,three different control algorithms are designed for the above problems.The main research contents are as follows:1.Aiming at the problems of output constraints and unknown disturbances in the motion of manipulator,an observer based fuzzy adaptive control strategy is studied.Firstly,error conversion is added to ensure the requirements of output constraints.The advantage is to avoid the virtual controller and abate the complexity of calculation.The uncertainty in the model can be removed by adaptive fuzzy logic.The fuzzy logic residuals and unknown disturbances from inside and outside the system are regarded as an integrated disturbance,and then the observer is used to compensate the integrated disturbance.The stability and convergence are deduced and verified by Lyapunov theory.The results of Matlab / Simulink simulation strongly show that the controller can not only meet the requirements of output constraints,but also have better transient and static response.2.For the manipulator with output constraints and model uncertainty,a finite time output constraint control scheme is studied.An adaptive fuzzy logic system is designed to approximate the unknown dynamic model of the manipulator.In the process of controller design,error transformation technology is used to ensure that the output constraints are not violated.The finite time sliding mode controller can ensure that the system signal converges to the equilibrium point in a finite time.According to Lyapunov law,the stability of the error system is verified,and the desired joint position tracking is realized.Matlab / Simulink simulation experiment is used to verify the effectiveness of the control strategy through numerical simulation.3.For the manipulator with input saturation and model uncertainty,a fixed time fuzzy adaptive control scheme is studied.Firstly,the saturation compensation system is designed,and the compensation state variable is added to the tracking error to form a new error system,which effectively solves the problem of input saturation.Based on the new error system,nonsingular terminal sliding surface and auxiliary function are constructed to avoid singular value problem.The fuzzy logic system can be utilized to approach the uncertainty and improve the control accuracy.It can be proved that the state of the closed-loop tracking error system is bounded,and it is proved that the sliding mode variable and trajectory tracking error converge to a compact set near zero in a fixed time.A large number of simulation indicate that the algorithm can achieve high-precision fixed time tracking control of manipulator with input saturation.In this paper,fuzzy adaptive and finite time algorithms are designed for output constrained manipulators.Compared with back-stepping,the difficulty of controller calculation is reduced,and the transient and steady-state performance of the system are improved.For the input saturated manipulator,a compensation system is designed,and a fixed time algorithm is added to solve the problems of safety and cost caused by input saturation,which improves the response speed and steady-state accuracy of the system.