Nature-Inspired Computing for Control Systems

1. Front Matter

   Pages i-xii

   PDF

2. The Power of Natural Inspiration in Control Systems

   • Hiram Eredín Ponce Espinosa, José Roberto Ayala-Solares

   Pages 1-10

3. General Control Approaches

   1. Front Matter

      Pages 11-11

      PDF

   2. Bioinspired Control Method Based on Spiking Neural Networks and SMA Actuator Wires for LASER Spot Tracking

      • Mircea Hulea

      Pages 13-38

   3. The Spread of Innovatory Nature Originated Metaheuristics in Robot Swarm Control for Smart Living Environments

      • Bo Xing

      Pages 39-70

4. Control Tuning and Adaptive Control Systems

   1. Front Matter

      Pages 71-71

      PDF

   2. Evolutionary Modeling of Industrial Plants and Design of PID Controllers

      • Monica Patrascu, Andreea Ion

      Pages 73-119

   3. Designing Fuzzy Controller for a Class of MIMO Nonlinear Systems Using Hybrid Elite Genetic Algorithm and Tabu Search

      • Nesrine Talbi, Khaled Belarbi

      Pages 121-144

   4. Neural Network Fitting for Input-Output Manifolds in Constrained Linear Systems

      • José M. Araújo, Carlos E. T. Dórea

      Pages 145-167

   5. Adaptive Neuro-Fuzzy Controller of Induction Machine Drive with Nonlinear Friction

      • Abdesselem Boulkroune, Salim Issaouni, Hachemi Chekireb

      Pages 169-192

5. Robotics Applications

   1. Front Matter

      Pages 193-193

      PDF

   2. Fuzzy Logic Sugeno Controller Type-2 For Quadrotors Based on Anfis

      • Pedro Ponce, Arturo Molina, Israel Cayetano, Jose Gallardo, Hugo Salcedo, Jose Rodriguez et al.

      Pages 195-230

   3. Mobile Robot with Movement Detection Controlled by a Real-Time Optical Flow Hermite Transform

      • Ernesto Moya-Albor, Jorge Brieva, Hiram Eredín Ponce Espinosa

      Pages 231-263

   4. Evolutionary Function Approximation for Gait Generation on Legged Robots

      • Oscar A. Silva, Miguel A. Solis

      Pages 265-289

The book presents recent advances in nature-inspired computing, giving a special emphasis to control systems applications. It reviews different techniques used for simulating physical, chemical, biological or social phenomena at the purpose of designing robust, predictive and adaptive control strategies. The book is a collection of several contributions, covering either more general approaches in control systems, or methodologies for control tuning and adaptive controllers, as well as exciting applications of nature-inspired techniques in robotics. On one side, the book is expected to motivate readers with a background in conventional control systems to try out these powerful techniques inspired by nature. On the other side, the book provides advanced readers with a deeper understanding of the field and a broad spectrum of different methods and techniques. All in all, the book is an outstanding, practice-oriented reference guide to nature-inspired computing addressing graduate students, researchers and practitioners in the field of control engineering.

• Biologically-Inspired Control
• Meta-Heuristic Optimization
• Adaptive Control Systems
• Neuro-Fuzzy Controllers
• Controlling Quadrotors
• Spiking Neural Networks
• Grey Wolf Optimizer (GWO)
• Robotic Swarm Control
• Nonlinear PID Controller
• MIMO Nonlinear Systems
• Multi-Layer Perceptron Neural Networks
• Optical Flow Models

• Faculty of Engineering, Universidad Panamericana, Mexico City, Mexico

  Hiram Eredín Ponce Espinosa

Policies and ethics