A Novel Control Strategy for CableDriven Parallel Robots with Unknown Jacobians Cabledriven parallel robots (CDPRs) have been studied by many researchers in the past decades. Due to the inconsistency among setups of a CDPR in some applications, such as rehabilitation, the Jacobian of the CDPR may not be known for a setup. In order to control a CDPR with unknown Jacobian, a novel control strategy named the PIDFNN control strategy is proposed in this paper. The control strategy consists of a PID controller and a feedforward neural network (FNN). The FNN takes over the role of the Jacobian by mapping a wrench applied on the endeffector of the CDPR at a pose in the task space to a set of cable tensions in the joint space. In this way, the CDPR is controlled by cable tensions computed by solving the inverse dynamics problem using such a mapping, rather than the Jacobian. Simulation results show that the PIDFNN control strategy works as expected in controlling an example CDPR with four cables, three degrees of freedom, and unknown Jacobian.

Tracking Control of FullyConstrained CableDriven Parallel Robots using Adaptive Dynamic Programming In this paper, a new adaptive tracking controller with learning ability is proposed for fullyconstrained cabledriven parallel robots (CDPRs). For these systems, the necessity of maintaining positive and bounded tensions in all cables while coping with disturbances represents a critical control requirement. To achieve this goal, we propose a control law based on adaptive dynamic programming (ADP), with an actorcritic structure. In the critic part, an artificial neural network (NN) approximates the value function which is to evaluate the system performance; in the action part, the controllerxe2x80x99s parameters are tuned online to achieve optimal control performance. Additionally, the antiwindup (AW) technique is combined with the adaptive controller to cope with the input saturation problem. The stability of the closedloop system with the proposed control algorithm is proved using the Lyapunov method. Numerical simulations show the effectiveness of the proposed controller.