Swarm intelligence
The particle swarm optimization algorithm: convergence analysis and parameter selection
Information Processing Letters
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
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Hybrid mechanism, which are a combination of two types of motor and mechanism, has good flexibility. In this paper, the kinematics analysis for a hybrid five-bar mechanism is introduced. An optimization design of hybrid actuator is performed with reference to kinematics objective function. Compared with conventional optimum evaluation methods such as simplex search and Powell method, Particle Swarm Optimization (PSO) algorithm can improve the efficiency of searching in the whole field by gradually shrinking the area of optimization variable. Compared to GA, PSO is easy to implement and there are few parameters to adjust. In order to solve the design problem, integrating MATLAB Optimization Toolbox and PSO optimization algorithm for the constraint equations. The precision of optimum dimensions obtained by using the hybrid optimization method can be improved evidently. Finally, a numerical example is carried out, and the simulation results show that the optimization method is feasible and satisfactory in the design of hybrid mechanism.