Abstract
A hybrid intelligent control technique based on combination of neural network and fuzzy logic will be proposed for hydraulic actuated active suspension system. A half car model will be used for design of Adaptive Neuro Fuzzy Inference System (ANFIS) controller for hydraulic actuated active suspension. The nonlinear behavior of hydraulic system and uncertain parameters in active suspension has increased the difficulty of creating mathematical model for active suspension system. The performance of most of the classical controller depends on nature of mathematical model of system. Hence it is very difficult to create classical controller without mathematical model of a system. Fuzzy logic controller has ability to predict the behavior of system without the need of mathematical model of a system. In this paper, ANFIS controller proposed for active suspension due to its ability to handle actuator dynamics and parameter uncertainty in hydraulic actuator. The simulation carried out for sinusoidal road profile in order to measure the performance of proposed controller. The result of simulation indicates performance of the ANFIS controller for active suspension with actuator dynamics.
Highlights
A suspension system is a mechanism which consist of spring and damping element connected between wheel and car body
A better ride comfort can be achieved by using soft suspension, whereas better stability can be achieved with the help of hard suspension
The response of front wheel for sinusoidal road profile is represented in Fig. 6 which indicates the response of passive, Proportional Integral derivative (PID) and Adaptive Neuro Fuzzy Inference System (ANFIS) controlled active suspension for various suspension parameter
Summary
A suspension system is a mechanism which consist of spring and damping element connected between wheel and car body. The performance of active suspension system obtained by measuring suspension travel and acceleration of vehicle body. The effect of ride comfort on suspension can be measured with the help of body acceleration of vehicle. The development of classical controller without mathematical model would be difficult for active suspension. Hrovat [15] addressed optimal controller for active suspension system using half car and full car model. He discussed some issues in mathematical model of system. Rao and Prahlad [17] introduced fuzzy controller for active suspension using quarter car model where suspension travel and its derivative act as input to fuzzy controller.
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