Expert supervision of an anti-skid control system of a commercial aircraft

A rule-based supervising system that incorporates fuzzy logic has been designed to back-up a conventional anti-skid braking system (ABS). Expressing the expert knowledge about the ABS in terms of linguistic rules, the supervising fuzzy system adapts the reference wheel slip of the ABS with respect to the actual runway condition. Two approaches are presented: The first uses a simple rule-based decision logic, which evaluates a new reference slip directly from the measured system variables. The second approach employes an explicit identification of the runway condition, which is used as input information of a fuzzy system to evaluate a new reference slip. This application example demonstrates the capabilities of a parallel use of conventional control techniques and fuzzy logic

Intelligent control based on fuzzy logic and neural net theory

In the conception and design of intelligent systems, one promising direction involves the use of fuzzy logic and neural network theory to enhance such systems' capability to learn from experience and adapt to changes in an environment of uncertainty and imprecision. Here, an intelligent control scheme is explored by integrating these multidisciplinary techniques. A self-learning system is proposed as an intelligent controller for dynamical processes, employing a control policy which evolves and improves automatically. One key component of the intelligent system is a fuzzy logic-based system which emulates human decision making behavior. It is shown that the system can solve a fairly difficult control learning problem. Simulation results demonstrate that improved learning performance can be achieved in relation to previously described systems employing bang-bang control. The proposed system is relatively insensitive to variations in the parameters of the system environment

Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Towards autonomous fuzzy control

The efficient implementation of on-line adaptation in real time is an important research problem in fuzzy control. The goal is to develop autonomous self-organizing controllers employing system-independent control meta-knowledge which enables them to adjust their control policies depending on the systems they control and the environments in which they operate. An autonomous fuzzy controller would continuously observe system behavior while implementing its control actions and would use the outcomes of these actions to refine its control policy. It could be designed to lie dormant when its control actions give rise to adequate performance characteristics but could rapidly and autonomously initiate real-time adaptation whenever its performance degrades. Such an autonomous fuzzy controller would have immense practical value. It could accommodate individual variations in system characteristics and also compensate for degradations in system characteristics caused by wear and tear. It could also potentially deal with black-box systems and control scenarios. On-going research in autonomous fuzzy control is reported. The ultimate research objective is to develop robust and relatively inexpensive autonomous fuzzy control hardware suitable for use in real time environments

Intelligent active force control of a three-link manipulator using fuzzy logic

The paper presents a novel approach to estimate the inertia matrix of a robot arm using a fuzzy logic (FL) mechanism in order to trigger the active force control (AFC) strategy. A comprehensive study is performed on a rigid three-link manipulator subjected to a number of external disturbances. The robustness and effectiveness of the proposed control scheme are investigated considering the trajectory track performance of the robotic arm taking into account the application of external disturbances and that the arm is commanded to describe a reference trajectory given a number of initial and operating conditions. The results show that the FL mechanism used in the study successfully computes appropriate estimated inertia matrix value to execute the control action. The proposed scheme exhibits a high degree of robustness and accuracy as the track error is bounded within an acceptable range of value even under the influence of the introduced disturbances

A Bibliography on Fuzzy Automata, Grammars and Lanuages

This bibliography contains references to papers on fuzzy formal languages, the generation of fuzzy languages by means of fuzzy grammars, the recognition of fuzzy languages by fuzzy automata and machines, as well as some applications of fuzzy set theory to syntactic pattern recognition, linguistics and natural language processing

Energy management in biodiesel production

Biodiesel economics revolves around both private and public features. Success for an incentive for producers and consumers needs to be sufficient to take part in the marketing arena with the currently accessible alternatives in the private dimension. “Whereas in the civic aspect, success is described in terms of the community objectives that prompt government’s intercession (i. e. subsidies) and whether biodiesel will attain the public goals in a remunerative manner compared to other alternatives if the public assessment is highly preferred, but the market incentives are deficient, there will not be a possibility to produce the biodiesel. On the other hand, if market values generate strong dividends among producers and purchaser, but the social gains are very small, or the costs are extremely high compared to other alternatives, then the activity may not represent a better use of scarce public resources. Biodiesel has become more enticing to the world recently due to its environmental benefits and the fact that it is made from renewable resources. The production cost of biodiesel is the main barrier to commercialization of the product. In the absence of tax relief, there is an urgent need to explore alternative feedstocks for the production of biodiesel. Furthermore, Properties impact of biodiesel and its feedstock, Engine type and its operating conditions Additives are effected by the biodiesel type and production characteristics. Where Engine power is always affected by properties of biodiesel, especially in heating value, viscosity, and lubricity