Zeeshan Shareef

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Over the last few decades, many evolutionary algorithms have emerged. One such algorithm is Particle Swarm Optimization which emulates social and cognitive behavior of bird-flocks. In this paper, particle swarm optimization algorithm is presented as a robust and highly useful optimization technique to tune the gains of the PID controllers in the two(More)
Feed-forward model-based control relies on models of the controlled plant, e.g., in robotics on accurate knowledge of manipulator kinematics or dynamics. However, mechanical and analytical models do not capture all aspects of a plant's intrinsic properties and there remain unmodeled dynamics due to varying parameters, unmodeled friction or soft materials.(More)
In this paper, we show the generalization of an inverse dynamic model for KUKA LWR IV+ under load mass variations. We use a modular approach based on regression in the model space. First, inverse dynamic models for the known masses are learned using a recently proposed approach called Independent Joint Learning (IJL). In IJL the torque errors due to(More)
This paper presents a joint selection criterion for optimal trajectory planning using dynamic programming along a specified geometric path subject to torque and velocity constraints. A single non-stationary joint is normally considered for optimization purpose. In case of more than one non-stationary joints, the optimization by selecting any joint at random(More)
In this paper, the optimal static and the dynamic anti-windup compensators (AWC) are designed using a new improved particle swarm optimization (PSO) algorithm. The existing optimization techniques for AWC make use of LMI (Linear Matrix Inequality) and various concepts of nonlinear control concepts that require complex mathematics. For this optimization, we(More)
There are always some type of constraints present in the all physical systems and these constraints or saturations produce the windup effect. This paper describes the design and implementation of a new dynamical Anti-Windup Compensator (AWC) scheme to remove the windup effect. In the new anti-windup scheme the state space matrices of the mixed sensitivity(More)
In this paper, the problem of trajectory optimization for robotic manipulators is solved by a newly developed methodology called Discrete Mechanics and Optimal Control (DMOC). This new methodology is based on the direct discretizaion of the Lagrange-d'Alembert principle. The constraints for the objective function to be optimized are the forced discrete(More)