Designing an optimized model-free controller for improved motion tracking by rugged electrohydraulic system

Abstract

Electrohydraulic actuation systems with proportional valves and industry-grade cylinders have widespread use due to their low cost and ease of maintenance. Achieving good tracking of output position of the piston in such a system by a proper controller design is the objective of this study. Due to various parameter uncertainties and complex nonlinearities like piston friction, valve deadband and flow characteristics, the variation of oil property with working temperature and air entrapment volume, the implementation of a model-based control becomes quite difficult for such systems. A notable contribution of this work is to couple a model-free fuzzy controller with a feedforward controller with all the parameters estimated by a real-coded genetic algorithm. Also, the optimizer has been used for identifying an appropriate fuzzy structure that is easy to implement in real time. A comprehensive experimental study has revealed the best fuzzy structure to be achieved through a Gaussian fuzzification of linear combination of the position and velocity errors as the input and singleton membership function for the output voltage actuating the proportional valve. Excellent responses with good disturbance rejection capability and energy efficiency have been achieved. These responses have emerged superior to those achieved in a similar system with different controller structures and in systems with much costlier components.

Keywords

Deadband friction fuzzy feedforward bias real-time control real-coded genetic algorithm

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