An Adaptive Controller with Guarantee of Better Conditioning of the Robot Manipulator JointSpace Inertia Matrix The illconditioning of the jointspace inertia matrix plays an important role in the dynamic behavior of robot manipulators, as well as in the controllersu0027 performance. Indeed, due to the illconditioning, small perturbations in the system can produce large changes in the numerical solutions, which can lead to instability. Moreover, this characteristic is intrinsic to a phenomenon of illconditioning in the mechanism itself, which suggests that it may be more difficult to control the mechanism. In this context, this paper proposes an adaptive controller to be used together with an algorithm that ensures better conditioning of the inertia matrix. To evaluate the proposed technique, we compared it with two widely used controllers via statistical analysis. The results showed that the proposed adaptive controller presents a better performance than the one based on the inverse dynamics with feedback linearization, and similar results when compared to a PID controller with gravity compensation.

Decoupling Control and Simulation of a 3RSR Spheroid Parallel Wrist The control of position and trajectory tracking are critical issues in parallel robots. Traditional PID tracking algorithms, which are based on kinematics control use the position and speed deviation as a negative feedback in order to design a controller. However, this method is not only hard to maintain the excellent dynamic and static quality of a system, but it is also incapable of realizing complete decoupling, and it needs large energy to be controlled. To overcome such drawbacks, this paper proposes, a computed torque decoupling control strategy for a 3RSR spheroid parallel mechanism. The control strategy includes a computed torque decoupling control method with traditional PD controller and selfadaption fuzzy controller. It was proved that the corresponding Lyapunov function is global asymptotic stable in the ideal and nonideal estimation. A set of ADAMSMATLAB dynamic simulations were established based on virtual prototyping technology. The results demonstrated that the performance of the control scheme with selfadaption fuzzy controller is more effective than that with PD controller.