Adaptive Command Filtering Backstepping Control Of State-constrained Flexible Joint Manipulato

With the rapid development of high-precision manufacturing industry,the industrial requirements for manipulator systems are getting higher and higher,and how to realize fast and good trajectory tracking of manipulator systems is very important.Flexible joint manipulators have attracted more and more attention because of its fast response speed,high control precision and high load weight ratio.At present,the nonlinearity and high coupling of flexible joint manipulator system are the main factors affecting its controller design.Therefore,how to realize the accurate joint position tracking of flexible joint manipulator systems is a very important topic.In this paper,the dynamic model of flexible joint manipulators is considered.In addition,due to the influence of physical space constraints and the requirements of tracking speed in practical application,a finite-time adaptive backstepping control method under state constraints is designed in this paper.The main research work includes the following points:1.For the nonlinear systems of flexible joint manipulator under state constraints,a command filter backstepping control method based on adaptive is designed.Firstly,considering the computational complexity caused by continuous integration of virtual control signals in backstep method,this paper introduces a commend filter,but the commend filter will produce errors when it gets intermediate signals,so an error compensation mechanism is constructed to eliminate the influence of filtering errors on the control effect of the system.The limitation of full-state in the system is realized by constructing the barrier Lyapunov functions,which ensures that full-state do not exceed the expected interval.Finally,it is proved that the proposed controller can ensure the joint position tracking error converges to an expected interval,and the advantages of the proposed algorithm are proved by comparing the simulation results of Matlab/Simulink.2.For the nonlinear systems of flexible joint manipulator under state constraints,using finite-time control,a command filter backstepping control based on neural network is designed.Firstly,in order to meet the requirements of system response speed in engineering,we apply the finite-time control to the design of the controller.By introducing the finite-time commend filter and error compensation mechanism,the problems of a large amount of computation and filtering error of the system are solved successfully,and improve the convergence speed and precision.On this basis,the uncertain dynamic parameters in the model are replaced by the neural network to further improve the control effect of the system,and full-state of the system is controlled by I_iin the obstacle Lyapunov function.Finally,comparative analysis of Matlab/Simulink simulation results proves the advantages of the algorithm.3.For the nonlinear systems of flexible joint multiple manipulators with state constraints,the distributed adaptive cooperative control problem under directed graph is studied.Firstly,the information exchange between each manipulator in the system is realized by using the directed graph.On this basis,neural network,finite-time commend filter,error compensation mechanism and finite-time control are introduced to ensure that the consensus tracking error of the system can converge to the expected interval in finite-time.And the barrier Lyapunov functions are used to ensure that full-state of the system do not exceed the expected interval.Finally,the advantages and effectiveness of the control strategy are proved by the analysis and comparison of Matlab/Simulink simulation results.