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The paper discusses means to adapt the braking pressure to changing road conditions by analyzing the relation between brake torque and slip ratio in real time. No additional sensory inputs are used. The fuzzy logic controller and a decision logic network identify the current road condition, based on current and past readings of the slip ratio and brake pressure. The controller detects wheel blockage immediately and avoids excessive slipping. The fuzzy logic controller output signal represents the brake torque applied to the vehicle. The ABS system performance is examined on a quarter vehicle model with nonlinear elastic suspension. The parallelity of the fuzzy logic evaluation process ensures rapid computation of the controller output signal, requiring both less time and fewer computation steps than controllers with adaptive identification.

The transducer operates as a drag-force flow meter. A thin flexible membrane, oriented perpendicular to the direction of flow, and a fixed plate form a capacitor. The dynamic pressure generated by the fluid flow (density times velocity squared) deflects the membrane, thus varying the capacitance and the resonant frequency of an electronic circuit. The frequency variations are sampled by a microprocessor. In order to obtain the mass flow rate, the microprocessor corrects the signal for nonlinearities such as the laminar-turbulent transition and fluid density variations. Because the membrane stiffens with increasing deflection and because of the high sensor resolution the sensor operates over a wide range (turndown ratio 100:1) with a flow rate uncertainty of less than 1%. The membrane natural frequency being above 20 kHz, fast flow transients and pulsations do not distort the measurement.