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Intelligent vehicle braking and steering control systems.

机译：智能车辆制动和转向控制系统。

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State-of-the-art vehicle dynamics control systems integrate the driver's steering and braking inputs together with the antilock braking system (ABS) and the four wheel steering system (4WS) in order to control the vehicle's yaw rate, lateral acceleration, longitudinal acceleration, and body sideslip angle. The goal of this project is to develop intelligent controllers for vehicle steering and braking maneuvers. In the first stage of the project, a simulation model of a vehicle is developed. Then, using this model several design models are constructed. Intelligent controllers are developed using the design models. The controller's performance is tested using the simulation model. Five different controllers are proposed. First, a Lyapunov based model reference steering controller is constructed. Its performance is tested by simulating an emergency lane change maneuver. The simulation results illustrate the improvement of the path tracking of the compensated vehicle over the uncompensated one. Then, a fuzzy logic based ABS wheel slip controller is proposed. Its performance is evaluated by simulating straight line emergency braking on dry pavement with no steering. The fuzzy logic controller results in a superior vehicle performance compared with a conventional brake control system. Next, a PID sliding mode based ABS controller is synthesized and analyzed. This controller performs an on-line search that determines the optimal wheel slip over any smooth road surface type. The fourth controller is developed for a 4WS system using a fuzzy modeling approach. Finally, a distributed neural brake controller is proposed to improve the vehicle's handling and stability during combined steering and braking maneuvers.
机译：先进的车辆动力学控制系统将驾驶员的转向和制动输入与防抱死制动系统（ABS）和四轮转向系统（4WS）集成在一起，以控​​制车辆的横摆率，横向加速度，纵向加速度和身体侧滑角。该项目的目标是开发用于车辆转向和制动操纵的智能控制器。在项目的第一阶段，开发了车辆的仿真模型。然后，使用该模型构建几个设计模型。使用设计模型开发智能控制器。使用仿真模型测试控制器的性能。提出了五个不同的控制器。首先，构建基于李雅普诺夫的模型参考转向控制器。通过模拟紧急车道变更操作来测试其性能。仿真结果表明，与未补偿车辆相比，补偿车辆的路径跟踪得到了改善。然后，提出了一种基于模糊逻辑的ABS轮滑控制器。通过在无转向的干燥路面上模拟直线紧急制动来评估其性能。与传统的制动控制系统相比，模糊逻辑控制器可提供出色的车辆性能。接下来，综合并分析基于PID滑模的ABS控制器。该控制器执行在线搜索，以确定在任何光滑路面类型上的最佳车轮打滑。第四个控制器是使用模糊建模方法为4WS系统开发的。最后，提出了一种分布式神经制动控制器，以提高车辆在转向和制动组合操纵过程中的操纵性和稳定性。

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