CMAC Based Hybrid Control System for Solving Electrohydraulic System Nonlinearities

Abstract

Automation based electrohydraulic servo systems have a wide range of applications in nowadays industry. However, they still suffer from several nonlinearities like deadband in electrohydraulic valves, hysteresis, stick-slip friction in valves and cylinders. In addition, all hydraulic system parameters have uncertainties in their values due to the change of temperature while working. This paper addresses these problems by designing a suitable intelligent control system that has the ability to deal with the system nonlinearities and parameters uncertainties using a fast and online learning algorithm. A novel hybrid control system based on Cerebellar Model Articulation Controller (CMAC) neural network is presented. The proposed controller is composed of two parallel controllers. The first is a conventional Proportional-Velocity (PV) servo type controller which is used to decrease the large initial error of the closed-loop system. The second is a CMAC neural network which is used as an intelligent controller to overcome nonlinear characteristics of the electrohydraulic system. A fourth order model for the electrohydraulic system is introduced. PV controller parameters are tuned to get optimal values. Simulation and experimental results show a good tracking performance obtained using the proposed controller. The controller shows its robustness in two working environments. The first is by adding different inertia loads and the second is working with noisy level input signals.

Evolving Neural Network CMAC and its Applications

“…Using a mathematical model of the cerebellar cortex developed by D. Marr [1] in 1975 J. Albus proposed a model describing the motion control processes that occur in the cerebellum, which was subsequently implemented in the neural network controller for controlling the robot -arm, which he called CMAC -Cerebellar Model Articulation Controller [2,3]. Ease of implementation and a good network of approximating properties have ensured its wide usage not only in the tasks of controlling the robotic arm in real time, but also to solve many other practical problems [4][5][6][7][8][9][10][11][12][13][14].…”