Intelligent anti-skid brake controller using a neural network
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The performance of current anti-skid brake controllers on aircraft becomes degraded due to the uncertain nature of the runway conditions. This paper presents the design of an intelligent anti-skid neural controller to overcome this problem. Their learning ability, nonlinear mapping ability and pattern-recognition capability are the features of neural networks that are ideally suited to the design of intelligent controllers. The controller described here identifies the runway condition from the aircraft-wheel responses, and modulates the brake torque for optimum braking. The proposed controller exhibits robustness under variations in brake characteristics and runway conditions. Simulation results confirm the satisfactory performance of the controller in adapting to changes in runway conditions. (C) 1999 . .
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