Innovations and Developments of Swarm Intelligence Applications > Section 1: PSO Algorithms > Chapter 6: Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation

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Innovations and Developments of Swarm Intelligence Applications

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Table of Contents

Title Page

Editorial Advisory Board

Preface

Acknowledgment

Section 1: PSO Algorithms

Chapter 1: Beyond Standard Particle Swarm Optimisation

Chapter 2: Biases in Particle Swarm Optimization

Chapter 3: Taguchi-Particle Swarm Optimization for Numerical Optimization

Chapter 4: Constraint Handling in Particle Swarm Optimization

Chapter 5: Adaptive Neuro-Fuzzy Control Approach Based on Particle Swarm Optimization

Chapter 6: Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation

ABSTRACT

1. INTRODUCTION

2. MODEL OF MULTIPLE UAVS CLOSE FORMATION

3. CONTROLLER DESIGN

4. MULTI-CRITERIA PSO-BASED PI CONTROL DESIGN

6. CONCLUDING REMARKS

Chapter 7: Oscillation Damping Enhancement via Coordinated Design of PSS and FACTS-Based Stabilizers in a Multi-Machine Power System Using PSO

Chapter 8: Compensation of Voltage Sags with Phase-Jumps through DVR with Minimum VA Rating Using PSO based ANFIS Controller

Chapter 9: Optimal Power Flow with TCSC and TCPS Modeling using Craziness and Turbulent Crazy Particle Swarm Optimization

Chapter 10: Congestion Management Using Hybrid Particle Swarm Optimization Technique

Chapter 11: Particle Swarm Optimization Algorithms Inspired by Immunity-Clonal Mechanism and Their Applications to Spam Detection

Section 2: Other Algorithms

Compilation of References

About the Contributors

Index

99 Design of Multi-Criteria PI Controller Using Particle Swarm Optimization for Multiple UAVs Close Formation Xiangyin Zhang Beijing University of Aeronautics and Astronautics, China Haibin Duan Beijing University of Aeronautics and Astronautics, China Chapter 6

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