Download Biomimicry for Optimization, Control, and Automation by Kevin M. Passino PDF

By Kevin M. Passino

Biomimicry makes use of our scienti?c figuring out of organic structures to use principles from nature for you to build a few know-how. during this booklet, we concentration onhowtousebiomimicryof the functionaloperationofthe “hardwareandso- ware” of organic platforms for the improvement of optimization algorithms and feedbackcontrolsystemsthatextendourcapabilitiestoimplementsophisticated degrees of automation. the first concentration isn't at the modeling, emulation, or research of a few organic method. the focal point is on utilizing “bio-inspiration” to inject new principles, recommendations, and point of view into the engineering of advanced automation platforms. there are lots of organic techniques that, at a few point of abstraction, can berepresentedasoptimizationprocesses,manyofwhichhaveasa basicpurpose computerized regulate, choice making, or automation. for example, on the point of daily event, we will view the activities of a human operator of a few approach (e. g. , the motive force of a motor vehicle) as being a sequence of the simplest offerings she or he makes in attempting to in attaining a few aim (staying at the road); emulation of this decision-making approach quantities to modeling one of those organic optimization and decision-making technique, and implementation of the ensuing set of rules ends up in “human mimicry” for automation. There are clearer examples of - ological optimization techniques which are used for regulate and automation when you think about nonhuman organic or behavioral techniques, or the (internal) - ology of the human and never the ensuing exterior behavioral features (like riding a car). for example, there are homeostasis tactics the place, for example, temperature is regulated within the human physique.

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Extra info for Biomimicry for Optimization, Control, and Automation

Example text

2 Information Space and Strategies . . . . 3 Decision and Action Timing . . . . . 5 Example: Dynamic Foraging Games . . . . . 1 Dynamic Foraging Game Model . . . . 2 Biomimicry for Foraging Strategies . . . 6 Challenge Problems: Intelligent Social Foraging . . 1 Intelligent Foraging . . . . . . . . 2 Intelligent Social Foraging . . . . . . 7 Exercises and Design Problems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

814 817 817 817 818 820 . . . . . . . . . . . . . . . . . . . . . . . 2 Design Objectives for Control Systems . . . . . . . . 3 Control System Design Methodology . . . . . . . . 4 Complex Hierarchical Control Systems for Automation . . . 5 Design Objectives for Automation . . . . . . . . . 6 Software Engineering for Complex Control Systems . . . . 7 Implementing Complex Control Systems .

4 Complex Hierarchical Control Systems for Automation . . . 5 Design Objectives for Automation . . . . . . . . . 6 Software Engineering for Complex Control Systems . . . . 7 Implementing Complex Control Systems . . . . . . . 8 Hybrid System Theory and Analysis . . . . . . . . 9 Exercises . . . . . . . . . . . . . . . . 1 Control Systems in Biology . . . . . . . . . . . 2 Nervous Systems . . . . . . . . . . . . . . 3 Organisms .

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