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This paper proposes an efficient PID control of a highly nonlinear double-pendulum overhead crane without the need for a payload motion feedback signal. Optimal parameters of the PID controllers are tuned by using an improved particle swarm optimisation (PSO) algorithm based on vertical distance oscillations and potential energy of the crane. In contrast to a commonly used PSO algorithm based on a horizontal distance, the approach resulted in an efficient performance with a less complex controller. To test the effectiveness of the approach, extensive simulations are carried out under various crane operating conditions involving different payload masses and cable lengths. Simulation results show that the proposed controller is superior with a better trolley position response, and lower hook and payload oscillations as compared to the previously developed PSO-tuned PID controller. In addition, the controller provides a satisfactory performance without the need for a payload motion feedback signal.

This paper presents the design of a fuzzy tracking controller for balancing and velocity control of a Two-Wheeled Inverted Pendulum (TWIP) mobile robot based on its Takagi-Sugino (T-S) fuzzy model, fuzzy Lyapunov function and non-parallel distributed compensation (non-PDC) control law. The T-S fuzzy model of the TWIP mobile robot was developed from its nonlinear dynamical equations of motion. Stabilization conditions in a form of linear matrix inequalities (LMIs) were derived based on the T-S fuzzy model of the TWIP mobile robot, a fuzzy Lyapunov function and a non-PDC control law. Based on the derived stabilization conditions and the T-S fuzzy model of the TWIP mobile robot, a state feedback velocity tracking controller was then proposed for the TWIP mobile robot. The balancing and velocity tracking performance of the proposed controller was investigated via simulations. The simulation result shows the effectiveness of the proposed control scheme.

Trajectory tracking control is an important issue in the field of autonomous mobile robot. In high speed and heavy load applications, the dynamic of autonomous mobile robot plays an important factor in allowing the robot to follow the desired trajectory path. However, the parameters attribute to robot dynamic are difficult to model and highly uncertain. One of the uncertainty factors is the load variation which changes the dynamic parameters of autonomous mobile robot. Meanwhile, Sliding Mode Control (SMC) is well known for its robustness against model uncertainties and disturbances. This paper is about design of dynamic controller based on SMC technique for trajectory tracking control of autonomous mobile robot system. The model of mobile robot is developed based on Pioneer 3-DX mobile robot. The trajectory tracking controller is divided into two parts, kinematic controller and dynamic controller. Stability of both dynamic and kinematic controller is verified using Lyapunov stability theory. The performance of trajectory tracking control for proposed dynamic controller based on SMC technique is compared against dynamic controller based on Proportional-Integral-Derivative (PID) technique with and without the presence of dynamic uncertainties. Simulation results show proposed dynamic controller based on SMC technique give better performance in trajectory tracking control in comparison to PID.

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