Robust Active Force Controller for an Automotive Brake System

Abstract

The paper presents a robust feedback control method to suppress the vibration and squeal noise phenomenon in disc brake model using an active force control (AFC) strategy. A two degree-of-freedom (2-DOF) Wagner model was considered in the study as the main dynamical element to be controlled. The system was tested for robustness and effectiveness in reducing the vibration and squeal, taking into account a number of disturbances acting on the system. Three control schemes were simulated and compared involving the classic proportional-integral-derivative (PID) controller, AFC with crude approximation (AFCCA) and AFC with fuzzy logic (AFCFL) schemes. The AFC-based schemes show superior performance compared to the PID only counterpart with the AFCFL method producing the best performance.

Experimental implementation of a vehicle anti-lock brake system employing intelligent active force control with a P-type iterative learning algorithm

“…AFC has been incorporated experimentally with the standard proportional-derivative (PD) controller via data acquisition system (DAS) in order to control the upper motor of a mobile robot (Abdullah et al, 2013). It has been simulated on a two-degree-of-freedom mechanism in the form of a Wagner brake model with standard PID control (Al-Mola et al, 2012a). This technique has been implemented in the ABS through a simulation study and produced positive outcomes in the control of the vehicle behavior during panic braking and preventing the wheel from locked under various disturbances that include non-linearity, parametric changes, and uncertainties (Al-Mola et al, 2012b).…”

“…It has been simulated on a two-degree-of-freedom mechanism in the form of a Wagner brake model with standard PID control (Al-Mola et al, 2012a). This technique has been implemented in the ABS through a simulation study and produced positive outcomes in the control of the vehicle behavior during panic braking and preventing the wheel from locked under various disturbances that include non-linearity, parametric changes, and uncertainties (Al-Mola et al, 2012b). Recent research used hybrid control schemes based on AFC applied to ABS by coupling the AFC with SMC (Al-Mola et al, 2013), and with Takagi-Sugeno fuzzy controller (Al-Mola et al, 2021).…”

The effective frequency range of an active suspended handle based on the saturation effects of a piezo stack actuator

“…Of these three arrangements, parallel and series types are limited by the actuator stroke, while series and inertia types require additional mass. Even though many Active Vibration Control (AVC) models for vibration isolation using piezo actuators have been reported (Hassan et al, 2010;Al-Mola et al, 2012;Hashemi-Dehkordi et al, 2012), these did not include the saturation effect of the piezo actuator in the overall AVC system. This can contribute to an unrealistic vibration attenuation level, since the stroke of the piezo actuator is limited by the displacement saturation.…”

Design for the Predictor of the Emergency Braking System Based on Fuzzy Algorithm

“…1/4 car braking system model [3], [4] Equation (1) is the vehicle acceleration and where ΣF is total resistance, m is the mass of a quarter vehicle, a is the vehicle acceleration rate, F bf is the braking force on one front wheel calculated by (2), F g is the hill climbing resistance calculated by (4), F w is the aerodynamic drag calculated by (5), F r is the rolling resistance calculated by (6). In (2), μ(λ) is the friction coefficient between tire and road, W f is the normal load on the front axle calculated by (3).…”

“…Velocity of Wind(Vw) 0 km/h Equation (7) is the rotational dynamics of the wheel used for calculating wheel speed, and where J w is the moment of inertial of wheel, ώ is the wheel angular acceleration rate, T bf is the brake torque of one of front wheels, R w is the effective radius of tire [4]. All the parameters used in above equations are shown in Table І.…”