The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Wheeled inverted pendulum (WIP) models have been widely used in the field of autonomous robotics and intelligent vehicles. A novel transportation system, WIP-car is proposed in this paper, which is composed of a mobile wheeled inverted pendulum system, a driven chair, an acceleration pedal and a deceleration pedal, which are used to drive the chair forward or backward such that the car can be accelerated...
The present work is focused on the synthesis and the analysis of robust control techniques for rear electric traction control in 4×4 hybrid-converted CVs (Conventional Vehicles) at urban speed limits (lower than 60 Km/h). This set represents a practicable alternative for the automotive industry, improving vehicular performance and reducing considerably fossil fuel air pollution. Our goal is to design...
The sliding mode controller is presented for automotive Anti-lock Braking System (ABS), and the drawback of control chattering occurred in the classical sliding mode control can be alleviated with the proposed control scheme. Moreover, the robustness of neural network adaptive control system can be improved to some extent. Simulation research is performed to the vehicles brake on the wet road situation,...
Modern electric cars require electrical power steering systems (EPAS). Many control algorithms where employed in this field. Some of these controllers exhibit robustness and stability problems for certain road conditions. Neural networks are known for their ability to imitate systems and stay stable if operation conditions change. In this paper we use neural controllers to imitate the H∞ controller...
In this paper, the state equation for the dynamics of quarter-car is established, and a stable robust sliding mode control law based on RBF neural network is presented for the vehicle slip ratio control. In addition, a moving sliding surface based on global sliding mode control is presented. Unlike the conventional sliding mode control, the moving sliding surface moves to the desired sliding surface...
This paper presents an active suspension system for passenger cars, using adaptive critic-based neurofuzzy controller. The model is described by a system with seven degrees of freedom. The car is subjected to excitation from a rode surface and wheel unbalance. The main superiority of the proposed controller over previous analogous fuzzy logic controller designed approaches, e.g., genetic fuzzy logic...
This paper presents the design of a neural network-based feedback linearisation (NARMA-L2) slip controller for an anti-lock braking system (ABS). The dynamics of the electro-mechanical based braking system are incorporated in the ABS model and thus a slip controller is developed to minimise the braking distance. The proposed controller is compared with an optimally-tuned PID controller. Simulation...
In order to improve the handling and stability of four-wheel-steering (4 WS) vehicle, a new 4 WS intelligent control system with genetic algorithm (GA) fuzzy neural network (FNN) was put forward. According to the tire cubic formula, a vehicle nonlinear dynamics model was built. Then a vehicle model based on back-propagation (BP) network was identified from the vehicle dynamics. Next a fuzzy neural...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.