Modelling, Simulation and Control of Non-linear Dynamical Systems
Regular price
€78.99
14 days return policy
Shipping & Delivery
A01=Oscar Castillo
A01=Patricia Melin
Adaptive Neuro Fuzzy Inference Systems
Adaptive Neuro Fuzzy Systems
ANFIS Architecture
ANFIS Controller
ANFIS Output
Author_Oscar Castillo
Author_Patricia Melin
automated mathematical modeling
Automated Parameter Selection
biochemical systems modelling
Category=PBWR
complexion-linear dynamical systems
computational intelligence
computing
Data Set
Derivative Free Optimization Method
dimension
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
evolutionary algorithms
fractal
fractal analysis
Fractal Dimension
function
fuzzy
Fuzzy Controller
Fuzzy Inference Systems
Fuzzy Rule Base
Fuzzy Rules
Fuzzy Set
fuzzy-fractal approach
Hyperbolic Tangent Sigmoidal Functions
intelligent control strategies for industry
Large Scale Combinatorial Optimization Problems
logic
MATLAB programming examples
membership
Membership Functions
Neuro Fuzzy Control
non-linear dynamical systems
Non-linear Model Predictive Control
Nonlinear Dynamical Systems
process automation
rule
SA
SC Technique
set
soft
soft computing techniques
Specific Genetic Algorithm
Strange Attractor
Sugeno Fuzzy Model
Product details
- ISBN 9780367455101
- Weight: 480g
- Dimensions: 178 x 254mm
- Publication Date: 02 Dec 2019
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Paperback
Secure
checkout
Fast Shipping
Easy returns
These authors use soft computing techniques and fractal theory in this new approach to mathematical modeling, simulation and control of complexion-linear dynamical systems. First, a new fuzzy-fractal approach to automated mathematical modeling of non-linear dynamical systems is presented. It is illustrated with examples on the PROLOG programming language. Second, a new fuzzy-genetic approach to automated simulation of dynamical systems is presented. It is illustrated with examples in the MATLAB programming language. Third, a new method for model-based adaptive control using a neuro-fussy fractal approach is combined with the methods mentioned above. This method is illustrated with MATLAB. Finally, applications of these new methods are presented, in the areas such as biochemical processes, robotic systems, manufacturing, food industry and chemical processes.
Melin, Patricia; Castillo, Oscar
