Most previous work about the hardware design of a fuzzy logic controller (FLC) intended to either improve its inference performance for real-time applications or to reduce its hardware cost. To our knowledge, there has been no attempt to design a hardware FLC that can perform an adaptive fuzzy inference for the applications of on-line adaptation. The purpose of this paper is to present such an ...

The Vapnik-Chervonenkis (VC) dimension measures the complexity of a learning machine, and a low VC dimension leads to good generalization. The recently proposed Minimal Complexity Machine (MCM) learns a hyperplane classifier by minimizing an exact bound on the VC dimension. This paper extends the MCM classifier to the fuzzy domain. The use of a fuzzy membership is known to reduce the effect of ...

This paper studies the evolutionary design of a fuzzy P+ID controller for an actual pneumatic muscle actuator system. The control of pneumatic muscles is a challenging problem because of their high degree of nonlinearity, time-varying parameters, and uncertainty. A fuzzy P+ID controller is constructed using an incremental fuzzy logic controller in place of the proportional term in a conventiona...

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

Fuzzy neural networks have several features that make them well suited to a wide range þÿ o l knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent explanation facilities in the fonn of semanticallymeaningful fuzzy rules, and the ability to accommodate both data and existing expert knowledge about the problem under co...

Proton exchange membrane fuel cells (PEMFCs) are promising clear and efficient new energy sources. An excellent control system is a normal working prerequisite for maintaining a fuel cell system in correct operating conditions. Conventional controllers could not satisfy the high performance to obtain the acceptable responses because of uncertainty, time-change, nonlinear, long-hysteresis and st...

Most of today’s chromatic adaptation transforms (CATs) are based on a modified form of the von Kries chromatic adaptation model, which states that chromatic adaptation is an independent gain regulation of the three photoreceptors in the human visual system. However, modern CATs apply the scaling not in cone space, but use “sharper” sensors, i.e. sensors that have a narrower shape than cones. Th...

This paper proposes an effective algorithm approach to hybrid control systems combining fuzzy logic and conventional control techniques of controlling the speed of induction motor assumed to operate in high-performance drives environment. The introducing of fuzzy logic in the control systems helps to achieve good dynamical response, disturbance rejection and low sensibility to parameter variati...

In this paper, we consider the fuzzy model-based designs for the complete synchronization of chaotic systems. T-S fuzzy model for chaotic systems are exactly derived. Based on the T-S fuzzy model, the fuzzy logic controllers for chaotic synchronization are designed via Linear Matrix Inequality (LMI). Lyapunov Exponent of lorenz system is calculated, one of them is positive which represents the ...

As to the control of fuzzy sliding mode, this paper proposes a cerebellar learning model for on-line learning of the controller. Fuzzy sliding mode has excellent robustness to the system uncertainty and immunity to the noise of the external noise. As for the cerebellar learning mode, it possesses the advantages of easy and fast correction. The combination of the two leads to the design of a fuz...