Mechatronics in Action s case-study approach provides the most effective means of illustrating how mechatronics can make products and systems more flexible, more responsive and possess higher levels of functionality than would otherwise be possible. The series of case studies serves to illustrate how a mechatronic approach has been used to achieve enhanced performance through the transfer of functionality from the mechanical domain to electronics and software.

Mechatronics in Action not only provides readers with access to a range of case studies, and the experts view of these, but also offers case studies in course design and development to support tutors in making the best and most effective use of the technical coverage provided. It provides, in an easily accessible form, a means of increasing the understanding of the mechatronic concept, while giving both students and tutors substantial technical insight into how this concept has been developed and used.

This book focuses on how the BOXES Methodology, which is based on the work of Donald Michie, is applied to ill-defined real-time control systems with minimal a priori knowledge of the system. The method is applied to a variety of systems including the familiar pole and cart. This second edition includes a new section that covers some further observations and thoughts, problems, and evolutionary extensions that the reader will find useful in their own implementation of the method. This second edition includes a new section on how to handle jittering about a system boundary which in turn causes replicated run times to become part of the learning mechanism. It also addresses the aging of data values using a forgetfulness factor that causes wrong values of merit to be calculated. Another question that is addressed is "Should a BOXES cell ever be considered fully trained and, if so, excluded from further dynamic updates". Finally, it expands on how system boundaries may be shifted using data from many runs using an evolutionary paradigm.

This book focuses on how the BOXES Methodology, which is based on the work of Donald Michie, is applied to ill-defined real-time control systems with minimal a priori knowledge of the system. The method is applied to a variety of systems including the familiar pole and cart. This second edition includes a new section that covers some further observations and thoughts, problems, and evolutionary extensions that the reader will find useful in their own implementation of the method. This second edition includes a new section on how to handle jittering about a system boundary which in turn causes replicated run times to become part of the learning mechanism. It also addresses the aging of data values using a forgetfulness factor that causes wrong values of merit to be calculated. Another question that is addressed is "Should a BOXES cell ever be considered fully trained and, if so, excluded from further dynamic updates". Finally, it expands on how system boundaries may be shifted using data from many runs using an evolutionary paradigm.