Purpose -The electric power industry has been moving from a regulated monopoly structure to a deregulated market structure in many countries. The purpose of this study is to comprehensively review the existing markets to study advantages, issues involved and lessons learnt to benefit emerging electricity markets. Design/methodology/approach -The paper employs a comprehensive review of existing competitive electricity market models in USA (California), UK, Australia, Nordic Countries (Norway), and developing country (Chile) to analyze the similarities, differences, weaknesses, and strengths among these markets based on publically available data, literature review and information. Findings -Ongoing or forthcoming electricity sector restructuring activities in some countries can be better designed based on lessons learnt from existing markets and incorporating their own political, technical and economical contexts. A template for design of successful electricity market has also been presented.Research limitations/implications -This study is limited to a comparative analysis of five markets and can be extended in the future for other existing and emerging electricity markets. Practical implications -The discussed weaknesses and strengths of existing electricity markets in this study can be practically utilized to improve the electricity industry market structures leading to several social benefits including lower electricity cost. Originality/value -The comprehensive review and analysis of five existing markets, physically located in different continents, may be used as an assistance or reference guide to benefit the emerging electricity markets in other countries.

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In this paper a novel fizy logic bused multiple reference model adaptive controller approach for the position control of a single link robotic manipulator is presented. The proposed fuzy logic scheme is used for generating multiple reference models, within the Model Reference Adaptive Control (MRAC)J?amework, in response to changes in modes of operation or modal swings due to manipulator tip load variation. Thus the scheme is utilized to generate dynamic reference model and the overall structure is coined as Fuzzy Multiple Reference Model Adaptive Controller (FM7LWC). Following a rule base the fu~y switching scheme effectively monitors changes in operating conditions due to tip load vnriation. A f i z z y inference engine then fires appropriate rules, which gives afuzzfied output value. Further defuzficarion is performed to switch the reference model in a predefined domain. The main contribution of the paper is that the proposed approach can be performed online and is very well suitable for plants showing sudden Yump' in operating conditions. Unlike, static multiple model algorithms for switching (noninteracting individual model-based filters) or switching dynamic algorithms (srrrceptible to numerical overflow), this scheme provides on interactive multiple model environment with soft swirching. l%is approach is found to be every effective and fault tolerant.

This article explains fuzzy controllers and general fuzzy systems. It emphasizes the basic idea of fuzzy control and the mathematics behind the concept. The article is divided into two sections. In the first part, the mathematics of fuzzy systems is discussed, which includes the definitions and basics of fuzzy expert systems, general fuzzy systems, and their properties. In the second part, the concept of fuzzy control are detailed which include the selection of inputs and outputs, enhancing control knowledge as a rule base, determining which rules to use, determining conclusions, converting decisions into actions, and graphical visual representation of fuzzy control operation. Then, various fuzzy control techniques and the essence of how fuzzy systems can be used for a wide range of control architectures are explained. The article concludes with the summary and future prospects of fuzzy logic systems.

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