| An ideal haptic device should have the following characteristics: when the operator operates the device to interact with the virtual environment or the remote environment,the operator feels the force touch during the interaction and feels at the scene to perform the real operation.The same is true.Therefore,how to make the haptic device able to construct a real,accurate and reliable presence effect is the most challenging problem in the design of haptic devices.Among them,the performance of haptic device is related to the selection of hardware such as structure,reducer and sensor,and the control algorithm is also a key factor affecting its performance.The control algorithm can eliminate the influence of self-inertia,friction,gravity and other factors in the haptic device,thereby enhancing the transparency of the system and the fidelity of the force feedback.However,the performance of the control algorithm in practical applications is also affected by the accuracy of the device model and the accuracy of the device motion information.In order to enable the haptic device to finally achieve precise control of position and contact force,this paper has carried out research on the following aspects:Firstly,the kinematics model and dynamics model of the haptic device are established by the kinematics and dynamics analysis method of the robot.Found that the gravity required to be compensated by the control algorithm is mainly caused by the 2th and 3th joints,and the movement of the end in the working space is mainly controlled by the 2th and 3th joints.Therefore,the device model is simplified to a twolink model,mainly for the control of the 2th and 3th joints.Secondly,in order to improve the anti-interference ability,dynamic response speed and tracking accuracy of the control system,a fast terminal sliding mode impedance control algorithm is proposed.The Lyapunov stability theory is used to prove that the algorithm is globally asymptotically stable and derived.The time the system converges from any non-zero state to the equilibrium point.Then,considering the uncertainty of the kinetic parameters of the haptic device,the control algorithm will not be able to provide accurate torque.In this regard,an improved comprehensive learning particle swarm algorithm is proposed to estimate the parameters of the haptic device.Simulation experiments show that the parameters estimated by the algorithm can provide more precise control torque.In addition,precise position,velocity,and acceleration can improve the performance of the control algorithm.Usually,the speed sensor and the acceleration sensor are not configured in the haptic device,and the angular velocity and angular acceleration of each joint cannot be directly obtained.Therefore,using the nonlinear tracking differentiator,the angle information of the device is filtered and differentiated to obtain the position,velocity and acceleration information of the haptic device.Finally,the experimental verification was carried out on the experimental platform of haptic device. |
