Application of Fuzzy control algorithms for electric vehicle antilock braking/traction control systems

Abstract—The application of fuzzy-based control strategies has recently gained enormous recognition as an approach for the rapid development of effective controllers for nonlinear time-variant systems. This paper describes the preliminary research and implementation of a fuzzy logic based controller to control the wheel slip for electric vehicle antilock braking systems (ABSs). As the dynamics of the braking systems are highly nonlinear and time variant, fuzzy control offers potential as an important tool for development of robust traction control. Simulation studies are employed to derive an initial rule base that is then tested on an experimental test facility representing the dynamics of a braking system. The test facility is composed of an induction machine load operating in the generating region. It is shown that the torque-slip characteristics of an induction motor provides a convenient platform for simulating a variety of tire/road - driving conditions, negating the initial requirement for skid-pan trials when developing algorithms. The fuzzy membership functions were subsequently refined by analysis of the data acquired from the test facility while simulating operation at a high coefficient of friction. The robustness of the fuzzy-logic slip regulator is further tested by applying the resulting controller over a wide range of operating conditions. The results indicate that ABS/traction control may substantially improve longitudinal performance and offer significant potential for optimal control of driven wheels, especially under icy conditions where classical ABS/traction control schemes are constrained to operate very conservatively

Simulation of Water Distribution Systems

In this paper a software package offering a means of simulating complex water distribution systems is described. It has been developed in the course of our investigations into the applicability of neural networks and fuzzy systems for the implementation of decision support systems in operational control of industrial processes with case-studies taken from the water industry. Examples of how the simulation package have been used in a design and testing of the algorithms for state estimation, confidence limit analysis and fault detection are presented. Arguments for using a suitable graphical visualization techniques in solving problems like meter placement or leakage diagnosis are also given and supported by a set of examples

Variation Modeling of Lean Manufacturing Performance Using Fuzzy Logic Based Quantitative Lean Index

The lean index is the sum of weighted scores of performance variables that describe the lean manufacturing characteristics of a system. Various quantitative lean index models have been advanced for assessing lean manufacturing performance. These models are represented by deterministic variables and do not consider variation in manufacturing systems. In this article variation is modeled in a quantitative fuzzy logic based lean index and compared with traditional deterministic modeling. By simulating the lean index model for a manufacturing case it is found that the latter tend to under or overestimate performance and the former provides a more robust lean assessment

Hierarchical fuzzy logic systems and controlling vehicles in computer games

This paper presents a possible application of fuzzy logic systems to control vehicles in computer games. A new architecture of a fuzzy logic system is here proposed: Hierarchical Fuzzy Controller, that is composed of several fuzzy controllers in their classic meaning. ”Hierarchical” means that fuzzy sets produced as output of one of fuzzy controllers are then processed as input of another fuzzy controller. The use of such a controller significantly enhances the possibilities of computational intelligence methods in singleplayer games, i.e. where the enemy is controlled by an agent simulating real behaviour (movement, decisions, etc.). The proposal of an original architecture of Hierarchical Fuzzy Controller, built with fuzzy controllers (in the sense of Mamdani), and discussing advantages of using this architecture to control military vehicles in a 2D single-player game, in comparison to classic fuzzy controllers, are the main scope of the paper

Constructing Fuzzy for Socio Economic Urban Growth Dynamic In Surabaya Based on GIS

Urban modeling is an important tool for efficient policy designing in a big city. Surabaya, a big city are now recognized as complex systems through which nonlinear and dynamic processes occur. The paper present a methodological framework for urban modeling from socio economic point of view, which suggested framework incorporates a set of fuzzy systems. In this case, the variable consist of manufacture, hospital, school and shopping centre. Combining with spatial analysis in GIS, the result is a dynamic model was shown to be capable of replicating the trends and characteristics of an urban environment, in this case the city of Surabaya