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A novel singularity control method for a fully parallel robot manipulator was proposed in this paper. The damped least-square method has frequently been used to solve the singularity problem of resolved-acceleration control schemes. It works by damping accelerations of the end-effector, so that accelerations in the degenerated directions are zero at a singular point. However, its velocities may not be zero in some situations, in those cases they will encounter fluctuations around the singular point. In this paper, the control using damped velocity, being called the damped-rate resolved-acceleration control scheme (DRRAC) is proposed to overcome this drawback. We will show that the DRRAC is asymptotically stable, and discuss its convergent properties. The main advantage of the DRRAC in the 3RPS parallel manipulator control system is not to plan its path to avoid the singular point, and could improve the workspace. Illustrative examples are given to show its effectiveness in practical applications, and experimental results are taken to verify the proposed control scheme.

This paper proposes a decision tool for utilities to perform the optimal generation expansion planning in a deregulated electricity market. Combining the immune algorithm (IA) and Tabu search (TS) an refined immune algorithm (RIA) is developed to solve this problem. By considering the various load types (peak load, middle load, basic load) and independent power producers (IPPs) competition, the generation expansion planning model is established under the operational constraints, reliability constraints and CO 2 constraints. RIA is conducted by an improved crossover and mutation mechanism with a competition and auto-adjust scheme to avoid prematurity. Tabu lists with heuristic rules are also employed in the searching process to enhance the performance. Testing results show that RIA can offer a better tool for generation expansion planning of utilities and promoted the competition ability of company. © 2005 Elsevier B.V. All rights reserved.