Optimal robust sliding mode tracking control of a biped robot based on ingenious multi-objective PSO

The aim of this paper is to present novel Multi-objective Particle Swarm Optimization (MOPSO) called Ingenious-MOPSO and compare its capability with three well-known multi-objective optimization algorithms, modified NSGAII, Sigma method, and MOGA. The application of this investigation is on an intellectual challenge in robotics, that is, a biped robot walking in the lateral plane on slope. Recently, a number of researches have been done on the walking of biped robots in the sagittal plane; however, biped robots require the ability to step purely in the lateral plane in facing obstruction, such as a wall. Hence, this paper introduces an optimal robust sliding tracking controller tuned by Ingenious-MOPSO to address the problem of heavy nonlinear dynamics and tracking systems of the biped robots which walk in the lateral plane on slope. Two phases of a biped robot, single support phase and double support phase; and also impact are regarded to control the robot. In the sliding mode controller, the heuristic parameters are usually determined by a tedious and repetitive trial-and-error process. By using Ingenious-MOPSO, the trial-and-error process is eliminated and the optimal parameters are chosen based on the design criteria. In the proposed algorithm, Ingenious-MOPSO, the rate of convergence and diversity of solutions are enhanced simultaneously, and innovative methods are proposed to select the global and personal best positions for each particle. Moreover, a new fuzzy elimination technique is suggested for shrinking the archive which promotes the diversity of solutions. A turbulence operator is utilized to evade local optima, for further improving the search ability. Numerical results and analysis demonstrate the superiority of Ingenious-MOPSO over three effectual multi-objective optimization algorithms. •An optimal robust sliding tracking controller is employed to control the heavy dynamic equations of a biped robot.•Ingenious particle swarm optimization is proposed to design optimal control coefficients.•Ingenious particle swarm optimization is more efficient than modified NSGAII, Sigma method, and MATLAB’s Toolbox MOGA.•The proposed controller is applied to a biped robot walking in the lateral plane on slope.