Research On Compound Control Of Bilateral Teleoperation System In Complex Environment

As a remote operating system that can replace humans in nuclear accident rescue,space exploration,telemedicine,agriculture and other fields,it has been widely developed in recent years.With the continuous improvement of functions,the application scenarios of the teleoperation system are more abundant,which also makes people have higher requirements for the control performance of the teleoperation system.In practical applications,the inevitable communication delay in the network communication between the master-slave system in the teleoperation system,the strong nonlinear characteristics of the teleoperation system itself,and the complexity of the environment lead to extremely high control performance of the system.It is susceptible to communication delays,model parameters,and interference from the external environment;in addition,in actual work,the teleoperation system is subject to considerations such as working environment constraints,operational safety,and system transient and steady-state performance improvement.The state is often subject to varying degrees of constraints.At the same time,because of the existence of master-slave communication delay,system uncertainty and external interference,it is urgent to design a full-state constraint control strategy for the networked teleoperation system to ensure the high-precision and fast synchronization of the master-slave system.The state is always within the constrained range.The main research contents of the thesis are as follows:For the bilateral-teleoperation system under all-state time-varying constraints,the synchronization control problem between master-slave systems is studied under system uncertainty and asymmetric time-varying time delays.In order to improve the synchronization accuracy of the master-slave system and avoid the collision problem caused by the sudden increase of the system state,the system’s full-state time-varying constraint problem is innovatively transformed into the system stability problem.At the same time,in view of the asymmetric time-varying delay between the master-slave system,a new nonlinear observer is introduced to ensure the stability of the closed-loop teleoperation system.The stability and synchronization performance of the master-slave system are proved by constructing a new obstacle Lyapunov function.Finally,simulation experiments verify the effectiveness of the designed control strategy.The tracking control problem of a bilateral-teleoperation system with flexible joints under system uncertainty and time-varying external disturbances is studied.First,a new type of composite neural network learning control framework is proposed and improve the tracking accuracy of the system,which combines the advantages of neural network and terminal sliding mode interference observer.In addition,based on the theory of backstepping recursion,a full-state compound neural network learning tracking control scheme is developed for the teleoperation system.Secondly,without using the higher-order derivative of the link state,the performance of the link end is improved.Under the composite framework,the system convergence speed and accuracy can be improved by increasing the prediction error.Finally,the bilateral teleoperation system is simulated and verified to verify the effectiveness of the proposed full-state tracking control strategy.