In this article, a robust method is presented for handling constraints with the Nelder and Mead simplex search method, which is a direct search algorithm for multidimensional unconstrained optimization. The proposed method is free from the limitations of previous attempts that demand the initial simplex to be feasible or a projection of infeasible points to the nonlinear constraint boundaries. The method is tested on several benchmark problems and the results are compared with various evolutionary algorithms available in the literature. The proposed method is found to be competitive with respect to the existing algorithms in terms of effectiveness and efficiency.
Optimal kinematic design of parallel manipulators is a challenging problem. In this work, an attempt has been made to present a generalized approach of kinematic design for a 6-legged parallel manipulator, by considering only the minimally required design parameters. The same approach has been used to design a 7-legged redundant parallel manipulator. Two ways of introducing redundancy into the parallel manipulator have been demonstrated and comparison between them has been presented.
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