Point-to-point trajectory planning for space robots based on jerk constraints.

This paper studies the Cartesian point-to-point optimal trajectory planning for space robots oriented to space maintenance operations. Aiming at the problems of poor stability, large base disturbance, and large joint variation in the motion planning of point-to-point maintenance in space, a planning method is proposed to minimize the base disturbance and the total joint angle variation under the jerk constraint on the premise of ensuring the accuracy of the end pose. First, the attitude of the space robot is described by the unit quaternion, and the velocity relationship between the joint angle, the end effector, and the base posture is introduced. Then, the joint trajectories were parameterized by a fifth degree polynomial, and a trajectory planning model with the minimum perturbation of the base and the minimum variation of the joint of the manipulator was established under the condition that the end effector satisfied the pose and the jerk constraint. Finally, a multi-objective optimization algorithm is proposed to deal with the trajectory optimization problem under nonlinear constraints. The simulation results show that the proposed trajectory planning method can optimize the base attitude and joint angle of the space manipulator under the premise of the optimal trajectory and stability of the terminal execution tool, which ensures the stability of the space robot's on-orbit service and reduces the energy consumption.

Reliable finite frequency filter design for networked control systems with sensor faults.

This paper is concerned with the reliable finite frequency filter design for networked control systems (NCSs) subject to quantization and data missing. Taking into account quantization, possible data missing and sensor stuck faults, NCSs are modeled in the framework of discrete time-delay switched systems, and the finite frequency l(2) gain is adopted for the filter design of discrete time-delay switched systems, which is converted into a set of linear matrix inequality (LMI) conditions. By the virtues of the derived conditions, a procedure of reliable filter synthesis is presented. Further, the filter gains are characterized in terms of solutions to a convex optimization problem which can be solved by using the semi-definite programme method. Finally, an example is given to illustrate the effectiveness of the proposed method.