A Bilateral Teleoperation Control With Time-varying Delay

With the widely using of teleoperation robot,teleoperation plays a great role in space exploration,underwater operation,remote medical treatment,and many other fields.It ensured the safety of operators and reduced the costs.Time delay has been a major issue which affect teleoperation,especially for space robot,due to the distance between heaven and earth,it has a great influence to the stability and transparency of the system.And along with the network popularizing,the random time delay of the network in teleoperation system is also increasingly prominent,how to guarantee stability of teleoperation system under random time delay has been a difficult problem.In this paper,further research on bilateral control will be done on the basis of previous research.The main work is as follows:Firstly,it presented passive control and PD control,analyzed their stability,transparency and tracking,compared their advantages and disadvantages in different environment,and calculate their parameters to ensure the stability and operational of the system.Then fuzzy PD control is presented in this paper according to the advantages and disadvantages of passive control and PD control,the simulation are carried out to verify the result.Secondly,the master adopted on-line identification to predict unknown environment,at the same time,Smith predictor was adopted in slave.In the first place,advanced fuzzy PD control proposed based on passive control and PD control,then the master adopted on-line identification to predict unknown environment with the Smith predictor was adopted in slave to keep stability with any non-symmetric time-varying delay.And the switching control law was added in the slave,to improve the tracking of the system.The simulations are carried out to verify the result that this method can overcome the stability issues with the random time delay.Finally to perfect the system,using fuzzy neural network to forecast the time,to make the parameters of Smith Predictor more accurate.And using the fuzzy neural network-PD controller instead of fuzzy PD controller,to make the control more precise,and to make the system more stable under random time delay.Then the simulation resultcarried out that the system can be stable under random time delay.