| Micro-electro-mechanical systems(MEMS)have great application potential in the field of biomedicine,among which the micromanipulator system for surgical operation plays an important role in the field of high precision control.In order to solve the problems in practical applications,the interaction between the end of micromanipulator and the environment has always been a hot research direction.Since the tracking force error at micro scale is more significant than that at macro scale,the precise control of the contact force between the micro manipulator and the environment is the key to improve the accuracy of micromanipulation.At microscale,it is difficult to obtain the feedback of the interaction force between the operator and the object.The operation object is more irregular shape.The application of the control strategy with position feedback and force feedback can not only reduce the deformation degree and additional damage of the operating object,but also prevent the deflection of the end of the micromanipulator,so as to provide more accurate,compliant and safe control.Active control with force feedback as the core has become one of the current research hotspots.An adaptive neural force control system is designed in this paper to solve the problem that MEMS is affected by dynamic model uncertainty and time-varying output and input saturation.The system consists of a high-precision linear motor for generating precise motion and a sensor for measuring micro-scale forces.The interaction forces between the micro-operating system and the external unknown environment can be measured.It is mainly used in micro-nano operations,such as surgery,which require accurate motion and force tracking.Simulation is used to verify the feasibility of this method,and experiments show that the control strategy can effectively stabilize the input pulse number and control the motion speed of the sliding platform to prevent overshooting in the interaction.The ability of the system to follow the time-varying output is proved by time varying force experiment.The reliability of the control strategy is proved by multiple experiments.The mean error ranges from-72 to 46.67 m N,the mean absolute error is 29.31 m N,the root mean square error is33.61 m N,and the percentage of force tracking error relative to the expected force is-7.2% to4.7%.Then,this paper studies the compliant control when the micro-operating platform interacts with the unknown environment.In the conventional hybrid force control,position and force control law need to be switched,so the frequent conversion of free space motion and restricted space motion will affect the system.The impedance control provides a flexible interaction method between the micromanipulator and the manipulated object,especially the interaction model and the force tracking control strategy in the complex environment,and the verification experiment is designed.In order to realize the flexible,compliant and safe control of the force when the micromanipulator is interacting with the complex environment,the measurement errors and other disturbances in the complex environment are considered.A contact force impedance control method based on extended Kalman filter is designed.In this method,the interaction between the external environment and the micromanipulator is regarded as a spring damping model,and the dynamic coupling between the micromanipulator and the contact environment is considered.By this method,the desired force can be accurately tracked and the tracking error can be reduced.In order to verify the feasibility of stiffness estimation of the designed EKF filter in unknown environment,simulation was used to verify.The results show that this method can accurately track the desired force and reduce the tracking error.Finally,to further verify the reliability of the method,a Sensapex micro-nano manipulator was used.The experimental results show that the proposed control method can accurately track the desired force and maintain the dynamic relationship between the position and force.In the experiment,the average error range of force tracking is-44.49-13.20 m N,the average absolute error is 14.75 m N,and the root-mean-square error is 19.76 m N.The percentage of force tracking error relative to the expected force is-4.94%-1.47%,the average trajectory tracking error ranges from-0.14-1.65 um,the average absolute error is 0.14 um,and the root mean square error is0.26 um,achieving the tracking accuracy of um level.The effectiveness of this method is proved. |
