Case of Studies Systems

Coloured Petri Nets (CPN) is a graphical language for modelling and validating concurrent and distributed systems, and other systems in which concurrency plays a major role. The development of such systems is particularly challenging because of inherent intricacies like possible nondeterminism and the immense number of possible execution sequences.

This book introduces researchers and advanced students with a basic control systems background to an array of control techniques which they can easily implement and use to meet the required performance specifications for their mechatronic applications. It is the result of close to two decades of work of the authors on modeling, simulating and controlling different mechatronic systems from the motion control, automotive control and micro and nano-mechanical systems control areas.

This monograph explores the full context of sex-selective abortion (SSA) in India by examining the historical forces, political movements, government policies, and gender regimes that shape this reproductive practice. Using qualitative research methods within a feminist methodology, including in-depth interviews with service providers and professionals in New Delhi and a content analysis of Indian newspapers, the study engages the following areas of analysis: the social structures and determinants of SSA in India, the potential for women’s agency in SSA, and the representations of SSA and SSA-seeking women in the Indian media. This research expands the discourse and analysis of SSA by facilitating a nuanced and multilayered exploration of a profoundly contextual, personal, and gendered reproductive issue by grounding data and interpretation in the lived experiences of research participants with systems-wide knowledge of SSA. Further, the feminist theory-informed analysis moves away from normative victimhood frameworks. Lastly, the book contributes to the understudied area of media discourse analysis on the intersections of gender and SSA in national news coverage.

This book examines several leading-edge design and verification technologies that have been successfully applied to microprocessor systems for high-assurance applications at various levels – from arithmetic circuits to microcode to instruction sets to operating systems to applications. We focus on recent hardware, software, and system designs that have actually been built and deployed, and feature systems that have been certified at high Evaluation Assurance Levels, namely the Rockwell Collins AAMP7G microprocessor (EAL7) and the Green Hills INTEGRITY-178B separation kernel (EAL6+). The contributing authors to this book have endeavored to bring forth truly new material on significant, modern design and verification efforts; many of the results described herein were obtained only within the past year.

Fuzzy Control of Industrial Systems: Theory and Applications presents the basic theoretical framework of crisp and fuzzy set theory, relating these concepts to control engineering based on the analogy between the Laplace transfer function of linear systems and the fuzzy relation of a nonlinear fuzzy system. Included are generic aspects of fuzzy systems with an emphasis on the many degrees of freedom and its practical design implications, modeling and systems identification techniques based on fuzzy rules, parametrized rules and relational equations, and the principles of adaptive fuzzy and neurofuzzy systems. Practical design aspects of fuzzy controllers are covered by the detailed treatment of fuzzy and neurofuzzy software design tools with an emphasis on iterative fuzzy tuning, while novel stability limit testing methods and the definition and practical examples of the new concept of collaborative control systems are also given. In addition, case studies of successful applications in industrial automation, process control, electric power technology, electric traction, traffic engineering, wastewater treatment, manufacturing, mineral processing and automotive engineering are also presented, in order to assist industrial control systems engineers in recognizing situations when fuzzy and neurofuzzy would offer certain advantages over traditional methods, particularly in controlling highly nonlinear and time-variant plants and processes.