Kevin M. Passino – författare

Includes a solution manual for problems.Provides MATLAB code for examples and solutions.Deals with robust systems in both theory and practice.

As control systems become increasingly complex, there is a growing need for software tools for use in their design and implementation. Introducing proven, free-to-use software from the NIST's real-time control systems (RCS) library, this practical resource arms readers with the tools they need to construct hierarchical and distributed RCSs for challenging industrial applications. Featuring numerous design and implementation examples, this is a complete reference to high-technology automation solutions.Market: Electronic Engineers and Computer Scientists involved with controls; Professionals in manufacturing, process control, and robotics.

There are many highly effective optimization, feedback control, and automation systems embedded in living organisms and nature. Evolution persistently seeks optimal robust designs for biological feedback control systems and decision making processes. From this comprehensive text you will gain knowledge of how mimicry of such biological processes can be used to solve optimization, control, and automation problems encountered in the construction of high technology systems. Mathematical stability analysis is treated for a number of cases, from attentional systems to social foraging swarm cohesion properties. Bio-inspired optimization and control methods are compared to conventional techniques with an objective to provide a balanced viewpoint. A companion web site, continually updated by the author, will provide you with further examples and design problems, solution hints, lecture slides, a running lab and ongoing self- study problems and resources. Matlab code is provided to solve a number of key problems. Focus lies on verifying correct operation of technologies via a process of mathematical modelling and analysis complimented by computer simulations. Written from an engineering per

Swarming species such as flocks of birds or schools of fish exhibitfascinating collective behaviors during migration and predatoravoidance.  Similarly, engineered multi-agent dynamic systems such as groups of autonomous ground, underwater, or air vehicles (“vehicle swarms”) exhibit sophisticated collective behaviors while maneuvering.In this book we show how to model and control a wide range of suchmulti-agent dynamic systems and analyze their collective behaviorusing both stability theoretic and simulation-based approaches. Inparticular, we investigate problems such as group aggregation, socialforaging, formation control, swarm tracking, distributed agreement,and engineering optimization inspired by swarm behavior.