Analytical analysis of the structure of fuzzy controllers is important as it provides insightful information and makes it possible to eliminate or reduce the trial-and-error effort in system design. Most results available in the literature only deal with the fuzzy controllers using up to three input variables (i.e. PI, PD, or PID type with the input space being three dimensional at most). In th...

The goal of this study was to design a practical fuzzy controller of the cycle-to-cycle control for multi-joint movements of swing phase of functional electrical stimulation (FES) induced gait. First, we designed three fuzzy controllers (a fixed fuzzy controller, a fuzzy controller with parameter adjustment based on the gradient descent method, and a fuzzy controller with parameter adjustment b...

In the first part of this paper, we investigate explicit structure of the typical Takagi– Sugeno (TS) fuzzy PI and PD controllers. By typical, we mean the use of at least three trapezoidal or triangular input fuzzy sets for each input variable, fuzzy rules with linear consequent, Zadeh fuzzy logic AND operator and the centroid defuzzifier. This configuration covers many TS fuzzy controllers in ...

Article Info Abstract This paper presents a Hybrid Adaptive Neuro Fuzzy Control technique for speed control of BLDC motor drives. The proposed controller is an integration of adaptive neuro fuzzy, fuzzy PID and PD controllers. The objective is to utilize the best attribute of fuzzy PID and PD controllers, which exhibits a better response than the neuro fuzzy controllers. The error back propagat...

An adaptive fuzzy controller is constructed from a set of fuzzy IF-THEN rules whose parameters are adjusted on-line according to some adaptation law for the purpose of controlling the plant to track a given-trajectory. In this paper, two adaptive fuzzy controllers are designed based on the Lyapunov synthesis approach. We require that the final closed-loop system must be globally stable in the s...

This paper investigates two fuzzy logic PID controllers that use simplified design schemes. Fuzzy logic PD and PI controllers are effective for many control problems but lack the advantages of the fuzzy PID controller. Design methodologies are in their infancy and still somewhat intuitive. Fuzzy controllers use a rule base to describe relationships between the input variables. Implementation of...

Stability of a fuzzy control system is closely related to the analytical structure of the fuzzy controller, which is determined by its components such as input and output fuzzy sets and fuzzy rules. We first characterize the mathematical input–output structure of fuzzy controllers and then utilize the structure characteristics to advance stability analysis. We study how the components of a gene...

In this paper, we incorporate fuzzy reasoning in fractional-order PD controllers. The resulting fuzzy fractional PD controller is investigated in terms of its digital implementation and robustness. The combined features of both algorithms will result in a better control system performance. Also, the effectiveness and robustness of the new methodology is illustrated through an application exampl...

This paper proposes inverse fuzzy-model-based feed-forward fuzzy controllers to compensate non-linear terms that affect the system dynamics. The gradient-descent algorithm can be used on-line to form adaptive fuzzy controllers. This ability allows these controllers to be used in applications were the knowledge to control the process does not exist or the process is subject to changes in its dyn...

This paper presents a pseudo-equivalence of the digital PI fuzzy controllers with the PI linear controllers in the continuous time domain. A method to design PI fuzzy controller is presented. Transfer functions and equivalence relations between controller’s parameters are obtained for the common structures of the PI fuzzy controllers. The pseudo-equivalence is made based on a grapho-analithic a...