[...]... (19 91) Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence Prentice Hall, New York 8 Goonatilake S, Khebbal S (eds) (19 96) Intelligent hybrid systems Wiley, New York 9 Medsker LR (19 95) Hybrid intelligent systems Kluwer, Dordrecht 10 Schwartz DG, Klir GJ (19 92) Fuzzy logic flowers in Japan IEEE Spectrum 29(7):32–35 11 Zilouchian A, Jamshidi M (20 01) Intelligent control. .. 14 4 5 .15 Genetic Programming Algorithm 14 5 5 .15 .1 Length 14 6 5 .16 Genetic Programming Stages 14 6 5 .16 .1 Initialization 14 6 5 .16 .2 Fitness 14 7 5 .16 .3 Selection 14 7 5 .16 .4... system plays 6 1 Intelligent Control for LabVIEW Fig 1. 3 Front panel Adapted from [15 ] Fig 1. 4 Control block loops a key role in the control system design Nowadays National Instruments is one of the most important companies in the world for providing excellent acquisition systems Different acquisition systems are shown in Fig 1. 6 References 7 Fig 1. 5 Waveform chart Fig 1. 6a,b Acquisition systems developed... Jamshidi M (20 01) Intelligent control systems using soft computing methodologies CRC, Boca Raton, FL 12 Warwick K (19 98) Recent developments in intelligent control IEE Colloquium on Updates on Developments in Intelligent Control, Oct 19 98, pp 1/ 1 1/ 4 13 Josifovska S (2003) The father of LabVIEW IEE Rev 49(9):30–33 14 Kehtarnavaz N, Gope C (2006) DSP system design using LabVIEW and Simulink: a comparative... 13 9 5 .11 An Application of the ICTL for the Optimization of a Navigation System for Mobile Robots 14 0 5 .12 Genetic Programming Background 14 3 5 .12 .1 Genetic Programming Definition 14 3 5 .12 .2 Historical Background 14 4 5 .13 Industrial Applications 14 4 5 .14 Advantages... 15 8 6 .1. 5 Industrial Applications of Fuzzy Clustering 15 8 6 .1. 6 Industrial Applications of Tabu Search 15 8 6.2 Simulated Annealing 15 9 6.2 .1 Simulated Annealing Algorithm 16 1 6.2.2 Sample Iteration Example 16 3 6.2.3 Example of Simulated Annealing Using the Intelligent Control. .. 7.8 .1 Modeling Procedure of the Gray System 206 7.9 Example of a Gray Predictor Using the ICTL 207 References 210 Futher Reading 210 Index 211 Chapter 1 Intelligent Control for LabVIEW 1. 1 Introduction Intelligent. .. problems as human beings do The main tools for IC are presented below: • Fuzzy logic systems are based on the experience of a human operator, expressed in a linguistic form (normally IF–THEN rules) P Ponce-Cruz, F D Ramirez-Figueroa, Intelligent Control Systems with LabVIEW © Springer 2 010 1 2 1 Intelligent Control for LabVIEW • Artificial neural networks emulate the learning process of biologic neural... the case of IC, we will be able to design controllers that work outside the opera- 1. 2 Intelligent Control in Industrial Applications 3 Fig 1. 1 Basic sets for obtaining IC systems tion point A global position in control theory of IC is shown in Fig 1. 1, in which different sets intersect in the IC area As it is presented, IC systems are in contrast to analytical control, because soft computing methodologies... areas of opportunities If you use only the IC systems as a conventional controller the difference is quite small For instance, using a FLC as a PID 4 1 Intelligent Control for LabVIEW controller with the error and the change in error as inputs, the fuzzy controllers look similar to the conventional PID controller except that fuzzy control provides a non-linear control law Another case is the use of a neural . GeneticProgrammingAlgorithm 14 5 5 .15 .1 Length 14 6 5 .16 GeneticProgrammingStages 14 6 5 .16 .1 Initialization 14 6 5 .16 .2 Fitness 14 7 5 .16 .3 Selection 14 7 5 .16 .4 Crossover 14 7 5 .16 .5 Mutation 14 8 5 .17 VariationsofGeneticProgramming. City Contents 1 Intelligent Control for LabVIEW 1 1 .1 Introduction . . 1 1.2 Intelligent Control in Industrial Applications . . . . 3 1. 3 LabVIEW 4 References 7 2 Fuzzy Logic 9 2 .1 Introduction.