Abstract ⎯ This paper proposes an internal model (IMC) fuzzy controller based on fuzzy model inversion. The gradient-descent algorithm can be used on-line to form adaptive fuzzy controllers. This ability allows these controllers to be used in applications where the knowledge to control the process does not exist or the process is subject to changes in its dynamic characteristics. The proposed a...

Fuzzy controllers are designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. The optimization of these parameters can be carried out by neural networks, which are designed to learn from training data, but which a...

This paper presents a comparative study between various control strategies. The design of different controllers, the sliding mode controller, the self tuning fuzzy logic controller, the fuzzy logic controller and the classical PI controller are proposed. The simulations results showed the performances and limits of the different cited controllers. In fact, the sliding mode controller is charact...

This paper presents the optimization of shunt active power filter parameters based on fuzzy logic control. The current active filter control is based on constant, fuzzy hysteresis band techniques, which are employed to derive the switching signals and also to choose the optimal value of the decoupling inductance. The DC voltage controller optimizes the energy storage of the DC capacitor, where ...

An Evolutionary Algorithm (EA) strategy for the optimization of generic Work-In-Process (WIP) scheduling fuzzy controllers is presented. The EA is used to tune a set of fuzzy control modules which are used for distributed and supervisory WIP scheduling. The distributed controllers objective is to control the rate in each production stage so that satisfies the demand for final products while red...

An adaptive fuzzy PID controller with gain scheduling is proposed in this paper. The structure of the proposed gain scheduled fuzzy PID (GS FPID) controller consists of both fuzzy PI-like controller and fuzzy PD-like controller. Both of fuzzy PIlike and PD-like controllers are weighted through adaptive gain scheduling, which are also determined by fuzzy logic inference. A modified genetic algor...

This paper offers a new technique for designing fuzzy controllers as analog hardware devices on bases of CMOS implementation of multi-valued logical functions. This approach is based on using a summing amplifier with saturation as a building block that can be considered as a multi-threshold logical element. The functional completeness in an arbitrary-valued logic of a summing amplifier with sat...

Complex production systems can produce more than one part type. For these systems, production rate and priority of production for each part type is determined by production controllers. In this paper, genetic fuzzy logic control (GFLC) methodology is used to develop two production control architectures namely ‘‘genetic distributed fuzzy” (GDF), and ‘‘genetic supervisory fuzzy” (GSF) controllers...

Fuzzy controllers are represented by if-then rules and thus can provide a user friendly and understandable knowledge representation. Evolutionary algorithms have been widely used for optimal design of fuzzy controllers. In this paper, we first present the state-of-art adaptive fuzzy control design using evolutionary algorithms and then attempt to enhance the performance of the simple genetic se...

A novel approach to design fuzzy controllers using fuzzy-arithmetic-based Lyapunov function that gives a linguistic description on the plant and the control objective is presented in this paper. An inverted pendulum system is used as a benchmark dynamic nonlinear plant for evaluating the proposed method. It is shown that a set of stable fuzzy control rules can be derived from perception-based i...