Although antiskid braking systems (ABS) are designed to optimize braking effectiveness while maintaining steerability, their performance often degrades under harsh road conditions (e.g. icy/snowy roads). The use of the fuzzy model reference learning control (FMRLC) technique for maintaining adequate performance even under such adverse road conditions is proposed. This controller utilizes a learning mechanism that observes the plant outputs and adjusts the rules in a direct fuzzy controller so that the overall system behaves like a reference model characterizing the desired behavior. The performance of the FMRLC-based ABS is demonstrated by simulation for various road conditions (wet asphalt, icy) and transitions between such conditions (e.g. when emergency braking occurs and the road switches from wet to icy or vice versa). >

Fuzzy learning control for antiskid braking systems

This paper focuses on the application of adaptive vehicle traction force control to the robust longitudinal control of vehicles. Adaptive fuzzy logic control and adaptive sliding mode control are applied to the fastest stable acceleration/deceleration and robust vehicle platooning problems. Results indicate that both controllers show good performance under time-varying operating conditions.

Adaptive vehicle traction force control for intelligent vehicle highway systems (ivhs)

This paper is concerned with robust longitudinal control of vehicles in intelligent vehicle highway systems by adaptive vehicle traction force control. Two different traction force controllers, adaptive fuzzy logic control and adaptive sliding-mode control, are proposed and applied to the fastest stable acceleration/deceleration and robust vehicle platooning problems. The motivation for investigating adaptive techniques arises from the unknown time-varying nature of the tire/road surface interaction that governs vehicle traction. Synchronous application of the engine or brake torques is also proposed for more stable vehicle maneuvers. The lack of controllability during braking (only one net input torque for the two control objectives, i.e., front and rear wheel slips) is partly overcome by applying auxiliary engine torque. Simulations of the two control methods are conducted using a complex nonlinear vehicle model which fully describes the dynamic behavior of the vehicle. Both controllers result in good performance under time-varying operating conditions.

Adaptive vehicle traction force control for intelligent vehicle highway systems (IVHSs)

Many different control methods for ABS systems have been developed. These methods differ in their theoretical basis and performance under the changes of road conditions. The present review is a part of research project entitled “Intelligent Antilock Brake System Design for Road-Surfaces of Saudi Arabia” In the present paper we review the methods used in the design of ABS systems. We highlight the main difficulties and summarize the more recent developments in their control techniques. Intelligent control systems like fuzzy control can be used in ABS control to emulate the qualitative aspects of human knowledge with several advantages such as robustness, universal approximation theorem and rule-based algorithms.

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An Antilock-Braking Systems (ABS) Control: A Technical Review

Although antiskid braking systems (ABSs) are designed to optimize braking effectiveness while maintaining steerability, their performance often degrades for harsh road conditions (e.g., icy/snowy roads). The authors introduce the idea of using the fuzzy model reference learning control (FMRLC) technique for maintaining adequate performance even under such adverse road conditions. This controller utilizes a learning mechanism which observes the plant outputs and adjusts the rules in a direct fuzzy controller so that the overall system behaves like a reference model which characterizes the desired behavior. The performance of the FMRLC-based ABS is demonstrated by simulation for various road conditions (wet asphalt, icy) and 'split road conditions' (the condition where, e.g. emergency braking occurs and the road switches from wet to icy or vice versa). >

Fuzzy learning control for anti-skid braking systems

This paper describes a new type Rear Brake Lock-up Control System which is mounted on Mitsubishi Starion. This system meets all the requirements of the ECE R13, Annex 13, gives a high braking stability regardless of the road conditions, and minimizes the body vibration and the pulsative reaction on the brake pedal to achieve a comfortable feeling during the brake application. It would be expected that the adoption of this system could contribute greatly to the reduction of car accidents caused by the rear wheel lock-up.

Hideo Kigoshi

Papers

Rear brake lock-up control system of mitsubishi starion