Creating some links between control feedback and biology modeling communities based on similarities in modeling, observing and perceiving alive structures, and analyzing interconnections between biological structures and subsystems was the main objective of this volume. In this context, biology systems need appropriate analysis tools due to their structure and hierarchy, complexity and environment interference, and we believe that these aspects may generate interesting research topics in control area. Indeed, several works, raising the potential impact of control developments to bring some beginning of answers in the context of biological systems, have been published in the recent years. The idea of this book was conceived in the context mentioned above with the objective to help in claiming many of the problems for control researchers, starting discussions and opening interactive debates between the control and biology communities, and, finally, to alert graduate students to the many interesting ideas at the frontier between control feedback theory and biology.

Creating some links between control feedback and biology modeling communities based on similarities in modeling, observing and perceiving alive structures, and analyzing interconnections between biological structures and subsystems was the main objective of this volume. In this context, biology systems need appropriate analysis tools due to their structure and hierarchy, complexity and environment interference, and we believe that these aspects may generate interesting research topics in control area. Indeed, several works, raising the potential impact of control developments to bring some beginning of answers in the context of biological systems, have been published in the recent years. The idea of this book was conceived in the context mentioned above with the objective to help in claiming many of the problems for control researchers, starting discussions and opening interactive debates between the control and biology communities, and, finally, to alert graduate students to the many interesting ideas at the frontier between control feedback theory and biology.

This book discusses the numerical treatment of delay differential equations and their applications in bioscience. A wide range of delay differential equations are discussed with integer and fractional-order derivatives to demonstrate their richer mathematical framework compared to differential equations without memory for the analysis of dynamical systems. The book also provides interesting applications of delay differential equations in infectious diseases, including COVID-19. It will be valuable to mathematicians and specialists associated with mathematical biology, mathematical modelling, life sciences, immunology and infectious diseases.

A survey of how engineering techniques from control and systems theory can be used to help biologists understand the behavior of cellular systems.

Computational biology, mathematical biology, biology and biomedicine are currently undergoing spectacular progresses due to a synergy between technological advances and inputs from physics, chemistry, mathematics, statistics and computer science. The goal of this book is to evidence this synergy by describing selected developments in the following fields: bioinformatics, biomedicine and neuroscience. This work is unique in two respects - first, by the variety and scales of systems studied and second, by its presentation: Each chapter provides the biological or medical context, follows up with mathematical or algorithmic developments triggered by a specific problem and concludes with one or two success stories, namely new insights gained thanks to these methodological developments. It also highlights some unsolved and outstanding theoretical questions, with a potentially high impact on these disciplines. Two communities will be particularly interested in this book. The first one is the vast community of applied mathematicians and computer scientists, whose interests should be captured by the added value generated by the application of advanced concepts and algorithms to challenging biological or medical problems. The second is the equally vast community of biologists. Whether scientists or engineers, they will find in this book a clear and self-contained account of concepts and techniques from mathematics and computer science, together with success stories on their favorite systems. The variety of systems described represents a panoply of complementary conceptual tools. On a practical level, the resources listed at the end of each chapter (databases, software) offer invaluable support for getting started on a specific topic in the fields of biomedicine, bioinformatics and neuroscience.

Control of multivariable industrial plants and processes has been a challenging and fascinating task for researchers in this field. The analysis and design methodologies for multivariable plants can be categorized as centralized and decentralized design strategies. Despite the remarkable theoretical achievements in centralized multiva- able control, decentralized control is still widely used in many industrial plants. This trend in the beginning of the third millennium is still there and it will be with us for the foreseeable future. This is mainly because of the easy implementation, main- nance, tuning, and robust behavior in the face of fault and model uncertainties, which is reported with the vast number of running decentralized controllers in the industry. The main steps involved in employing decentralized controllers can be summarized as follows: • Control objectives formulation and plant modeling. • Control structure selection. • Controller design. • Simulation or pilot plant experiments and Implementation. Nearly all the textbooks on multivariable control theory deal only with the control system analysis and design. The important concept of control structure selection which is a key prerequisite for a successful industrial control strategy is almost unnoticed. Structure selection involves the following two main steps: • Inputs and outputs selection. • Control configuration selection or the input-output pairing problem. This book focuses on control configuration selection or the input-output pairing problem, which is defined as the procedure of selecting the appropriate input and output pair for the design of SISO (or block) controllers.

Robot Motion Control 2009 presents very recent results in robot motion and control. Forty short papers have been chosen from those presented at the sixth International Workshop on Robot Motion and Control held in Poland in June 2009. The authors of these papers have been carefully selected and represent leading institutions in this field. The following recent developments are discussed: design of trajectory planning schemes for holonomic and nonholonomic systems with optimization of energy, torque limitations and other factors, new control algorithms for industrial robots, nonholonomic systems and legged robots, different applications of robotic systems in industry and everyday life, like medicine, education, entertainment and others, multiagent systems consisting of mobile and flying robots with their applications. The book is suitable for graduate students of automation and robotics, informatics and management, mechatronics, electronics and production engineering systems as well as scientists and researchers working in these fields.