Abstract This is to minimize the oscillations while carrying loads from the initial point to the final point in minimum time to prevent security hazards. A Proportional Derivative (PD) Fuzzy controller is proposed to control the overhead crane with minimal load swing. A Non-Linear dynamic model is used to investigate and compare the results of Fuzzy PD controller (Mamdani & Takagi... This is to minimize the oscillations while carrying loads from the initial point to the final point in minimum time to prevent security hazards. A Proportional Derivative (PD) Fuzzy controller is proposed to control the overhead crane with minimal load swing. A Non-Linear dynamic model is used to investigate and compare the results of Fuzzy PD controller (Mamdani & Takagi Sugeno) with conventional PD controller. The controllers are compared in terms of load swing, Time taken to reach final point, Steady state performance and Transient performance. The proposed control strategy has been designed and validated with MATLAB. Simulation results are obtained and discussed. Read More Read Less

Abstract For the ease of controlling of an unknown Hammerstein model, it is usually desired to cancel out the effects of static nonlinearities. This requires the proper cancellation of all the nonlinearities or otherwise it may either create control problems or can result in the optimization complexity. The paper discusses a novel approach towards the designing of fuzzy inverse model controller... For the ease of controlling of an unknown Hammerstein model, it is usually desired to cancel out the effects of static nonlinearities. This requires the proper cancellation of all the nonlinearities or otherwise it may either create control problems or can result in the optimization complexity. The paper discusses a novel approach towards the designing of fuzzy inverse model controller that can effectively cancel out the effect of static nonlinearities in unknown Hammerstein models. The controller is used in conjunction with Generalized Predictive controller for controlling an unknown Hammerstein model. Simple single layer convex optimization is found sufficient to generate a converged optimized solution. Simulation results are presented to show the effective performance of the proposed controller. Read More Read Less