Research On Force Control For Constrained Reconfigurable Manipulators Based On Force Sensor Of The End-effector

Because of the modular characteristics and the capability of reorganizing into different configurations to meet various needs of different tasks, reconfigurable manipulators have a lot of advantages such as strong robustness, good fault tolerance, strong flexibility and low cost, reconfigurable manipulators are increasingly used in many applications. Most of the existing research for reconfigurable manipulators was carried out under the space which was totally free of external factor or task constraints. Manipulators did not contact with external factor or generate contact force when it was executing the manipulating tasks. However, the flexibility and intelligence of the manipulators were asked to be higher and higher, people use them to perform some complicated and delicate operations in more cases. On this occasion, not only the trajectory tracking of manipulators should be controlled, but also the contact force between the manipulators and external factor. Therefore, exploring the force/position of reconfigurable manipulators as well as the control strategy becomes the priority among priorities currently.In this paper, forward kinematics of the reconfigurable manipulators was analyzed based on the exponential product formula firstly, and then the inverse kinematics was introduced by using the numerical method, thus establishing the transformational relation between the joint space and work space.The dynamic model of the reconfigurable manipulators in free space was set up combining with the screw theory and Newton-Euler equation. The transformational relation for contact force between the end-effector and each joint was analyzed using the Jacobi matrix. Then, dynamic model of the reconfigurable manipulators in constraint space was set up. Aiming at the problem that, the motion task of controlled manipulators was usually defined in the workspace, while the trajectory control of the manipulators was implemented at joint space before, robust trajectory tracking control method of constrained reconfigurable manipulators was proposed based on neural network compensation. And then, aiming at the reconfigurable manipulators mounted with force sensors at the end, an adaptive neural network position/force hybrid control scheme was designed according to reduced-order model which built on the base of the relationship between the manipulators and the environmental constraints under the condition of that the contact force can be measured. Finally, simulation results showed the effectiveness and universality of the proposed control scheme.