Advances in Chaos Theory and Intelligent Control by Ahmad Taher Azar

By Ahmad Taher Azar

The publication stories at the most up-to-date advances in and purposes of chaos concept and clever regulate. Written by means of eminent scientists and energetic researchers and utilizing a transparent, matter-of-fact type, it covers complex theories, equipment, and functions in numerous learn components, and explains key suggestions in modeling, research, and regulate of chaotic and hyperchaotic structures. themes comprise fractional chaotic platforms, chaos keep an eye on, chaos synchronization, memristors, jerk circuits, chaotic structures with hidden attractors, mechanical and organic chaos, and circuit recognition of chaotic platforms. The booklet extra covers fuzzy good judgment controllers, evolutionary algorithms, swarm intelligence, and petri nets between different issues. not just does it give you the readers with chaos basics and clever control-based algorithms; it additionally discusses key purposes of chaos in addition to multidisciplinary strategies constructed through clever keep an eye on. The e-book is a well timed and complete reference consultant for graduate scholars, researchers, and practitioners within the components of chaos concept and clever control.

Show description

Read Online or Download Advances in Chaos Theory and Intelligent Control PDF

Best robotics & automation books

Autonomous robots: modeling, path planning, and control

It really is not less than twenty years because the traditional robot manipulators became a typical production software for various industries, from car to pharmaceutical. the recent iteration of robots at the moment are being built that may be categorised in teams; redundant (and hyper-redundant) manipulators, and cellular (ground, marine, and aerial) robots.

Imitation in Animals and Artifacts

The hassle to give an explanation for the imitative skills of people and different animals attracts on fields as varied as animal habit, synthetic intelligence, laptop technological know-how, comparative psychology, neuroscience, primatology, and linguistics. This quantity represents a primary step towards integrating learn from these learning imitation in people and different animals, and people learning imitation in the course of the development of software program and robots.

Improving Stability in Developing Nations through Automation 2006 (IPV - IFAC Proceedings Volume) (IPV - IFAC Proceedings Volume)

Technological improvement has triggered profound alterations and social balance. areas that have had strong populations for hundreds of years have skilled huge, immense inhabitants progress resulting in the emergence of occasionally unmanageable megaplex towns in addition to bringing approximately macroscopic environmental swap.

Design of Intelligent Systems Based on Fuzzy Logic, Neural Networks and Nature-Inspired Optimization

This publication provides fresh advances at the layout of clever platforms in keeping with fuzzy good judgment, neural networks and nature-inspired optimization and their program in parts equivalent to, clever regulate and robotics, trend popularity, time sequence prediction and optimization of complicated difficulties. The ebook is geared up in 8 major elements, which comprise a gaggle of papers round the same topic.

Extra resources for Advances in Chaos Theory and Intelligent Control

Sample text

24) becomes 1 (25) iυ = − R3 which represents the i − υ characteristic of the negative resistor. If the voltage takes large values the slope of the i − υ characteristic is positive, since the op amp saturates. For example, for the positive saturation (υ0 = E sat ) the Eq. (21) can be written as i= υ − E Sat R1 (26) which now represents a i − υ characteristic which is translated with respect to the origin and has a positive slope. The breakpoint υ = E 1 of the whole i − υ characteristic of the nonlinear resistor can be calculated by substituting υ = E 1 in Eq.

Proof Here ea (t) and eb (t) are the parameter estimation errors given as ea (t) = a − A (t) eb (t) = b − B (t) . (17) Differentiating (17) with respect to t, we obtain e˙a (t) = − A˙ (t) e˙b (t) = − B˙ (t) . (18) Substituting adaptive control law (15) into (14), the closed-loop error dynamics is determined as ⎧ e˙x = −k x ex ⎪ ⎪ ⎨ e˙ y = − (a − A (t)) (x1 W (ϕ1 ) + x2 W (ϕ2 )) − 2 (b − B (t)) − k y e y (19) e˙z = −k z ez ⎪ ⎪ ⎩ e˙ϕ = −kϕ eϕ Dynamics, Synchronization and SPICE Implementation … 43 Then substituting (17) into (19), we have ⎧ e˙x = −k x ex ⎪ ⎪ ⎨ e˙ y = −ea (x1 W (ϕ1 ) + x2 W (ϕ2 )) − 2eb − k y e y e˙z = −k z ez ⎪ ⎪ ⎩ e˙ϕ = −kϕ eϕ (20) We consider the Lyapunov function as V (t) = V ex , e y , ez , eϕ , ea , eb = 21 ex2 + e2y + ez2 + eϕ2 + ea2 + eb2 .

EU result for linear equations of the form R D α y(x) − λy(x) = f (x), (n − 1 ≤ Re(α) < n), (1) where R D α is Riemann-Lioville fractional derivative is derived by Barret [47]. Al-Bassam [48] used method of successive approximation to derive EU result for nonlinear problem R D α y(x) = f (x, y(x)), (0 < α ≤ 1). (2) Delbosco and Rodino [49] derived EU results for nonlinear equations using Schauder’s fixed point theorem. Cauchy problems of the form (2) with Caputo derivative are investigated by Diethelm and Ford [50].

Download PDF sample

Rated 4.13 of 5 – based on 19 votes