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A complex optimization problem in robotics is the optimum movement between certain physical configurations while minimizing certain criteria. The fundamental objective in movement planning for robot arms is to minimize movement time, total distance, joint torque, avoiding obstacles and the robot arm itself as an obstacle. This paper presents a study on clonal selection algorithm (CSA) and CSA with oppositional approach to optimize the 2D point to point movement of a 3-links robot arm. Simulations with MATLAB of the problem were implemented with both techniques to minimize an objective function depending on the mentioned criteria. Results of both methods are presented, showing that the CSA with oppositional approach presented better results than the classical CSA in terms of convergence and response quality.

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Abstract. The purpose of this paper is to derive an alternative tuning design from Generalized Predictive Controller (GPC) that is based on both positional plant model and cost function, involving the selection of an integral polynomial weighting filter. The obtained Filter Positional GPC can be transformed into RST structure and next to Filtered Internal Model and PID controllers. Numerical and experimental essays show the effectiveness of the control methodologies.