Fuzzy Control Systems

Whatever a man prays for, he prays for a miracle. Every prayer reduces itself to this Great God, grant that twice two be not four. [Pg.209]

Fuzzy control systems are ones in which experts decision-making rnles are used to produce a control output. The rules may either be mathematically based or not, and the controller output is usually sufficiently correct to perform the intended function. However, control with a Fuzzy system is not usually very precise. [Pg.209]

A healthy rose plant will bloom with profuse, beautiful flowers. The plant requires water, and therefore must be watered. If water is added without regard to the condition of the plant, this is an open-loop system. If water is added only when the plant needs it, or if the amount varies to meet plant moisture requirements, then the system is closed-loop with feedback. If extra water is added because you will be unable to care for the plant for a few days, then this is a feedforward control system. [Pg.209]

Learning will require feedback control habit will allow open-loop control. [Pg.209]

Cell growth will be regulated with feedback from its neighbors. [Pg.209]

Watano S, Numa T, Miyanami K, Osako Y. A fuzzy control system of high shear granulation using image processing. Powder Technol 2001 115 124-130. [Pg.328]

FIGURE 57.17 Basic fuzzy control system configuration. [Pg.1168]

E.H. Mamdani, The application of fuzzy control systems to industrial processes, Automatica, 13(3) 235-242, 1977. [Pg.1170]

Hoffmann F (2001) Evolutionary algorithms for fuzzy control system design. Proc IEEE 89... [Pg.63]

More comprehensive and integrating approaches have been followed by several academic researchers, aiming to develop both offline sewability testing/process planning tools, as well as inbuilt intelligent and self-learning sewing machines and control systems. Some examples include neuro-fuzzy control systems that are... [Pg.331]

Stylios, G., Sotomi, J., 1995. A neuro-fuzzy control system for intelligent overlock sewing machines. Int. J. Cloth Sci. Tech. 7 (2/3), 49—55. [Pg.336]

Figure 3.21 Proposed neuro-fuzzy control system for the smart clothing. [Pg.56]

The results are given in Figures 6-11. We observe that displacements can be easily reduced, while velocity and acceleration results of the fuzzy-controlled system are not very satisfactory, due to the nonlinear, impact-like nature of the control force. [Pg.174]

The performance of the fuzzy control system can be further enhanced by fine-tunning the parameters of the fuzzy system (membership functions, rules, etc) by using a neural network or a global optimization scheme. First results in this direction, using the Particle Swarm Optimization method, have been presented in Marinakis et al. 2008. Furthermore, from the practical point of view a big deficiency of fuzzy controllers are... [Pg.175]

Chen, G. and T. T. Pham. Introduction to Fuzzy Sets, Fuzzy Logic, and Fuzzy Control Systems. CRC Press, Boca Raton, FL, 2001. [Pg.572]

Figure 3 shows a modified version of the automatic braking system, in which a Fuzzy Controller object hcis been introduced to encapsulate the fuzzy decision making. This is a very common approach in fuzzy control systems, where a central fuzzy controller will interact with several interface objects. [Pg.156]

Cheng, Y, Wang, X., Lei, R. (2009). A fuzzy control system for path following of mobile robots. ICIC Express Letters, 3(3), 403-408. [Pg.76]

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