Tuning Innovation with Biotechnology
This book deals with evolving intelligence systems and their use in immune algorithm (IM), particle swarm optimization (PSO), bacterial foraging (BF), and hybrid intelligent system to improve plants, robots, etc. It discusses the motivation behind research on and background of evolving intelligence systems and illustrates IM-based approach for parameter estimation required for designing an intelligent system. It approaches optimal intelligent tuning using a hybrid genetic algorithm?particle swarm optimization (GA-PSO) and illustrates hybrid GA-PSO for intelligent tuning of vector system.
Background. Immune Network–Based Parameter Estimation. Intelligent PID Controller Tuning Using a Hybrid GA-PSO Approach. GA-PSO-Based PI Controller Tuning for Indirect Vector Control of Three-Phase Induction Motor. Novel Hybrid System Based on GA and Bacteria Foraging. Conclusion.
Date de parution : 02-2018
15.2x22.9 cm
Thèmes de Tuning Innovation with Biotechnology :
Mots-clés :
Antibody A1; Pid Controller; Fuzzy Controller; Induction Motor; Bacterial Foraging; Pi Controller; PSO; Chemotactic Step; Conventional GA; Indirect Vector Control; Speed Pi Controller; Negative Selection Algorithm; Immune Network; Antibody A2; T-cell Receptor; Membership Function; FOC; Rotor Flux; Equivalent Circuit; Ai; Evolutionary Algorithm Approaches; Optimal Search Process; Clonal Selection Algorithm; Fuzzy Neural Network Model; Clonal Selection Principle