In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutiona...

Parallel robots exhibit good performance in terms of rigidity, accuracy, and dynamic characteristics. However, parallel robots have complex configurations and their dynamic model is highly nonlinear, and conventional PID controllers are not sufficiently robust for their motion control. In this paper, we have investigated the intelligent control of a hydraulically driven parallel robot based on ...

A control scheme is being presented for the trajectory tracking of a nonholonomic kinematic model of mobile robots. As a kinematic model of mobile robots is nonlinear in nature, therefore, it is controlling is always being a difficult task. Thus, a control hybrid scheme comprises of fuzzy logic and PID (Proportional Integral Derivative) is being proposed, in which adaptive gains of PID controll...

Abstract. A Fuzzy-PID controller is designed for tracing reference cutting forces in grinding by integrating a high performance fuzzy controller and an easy to use PID controller. When the error of the grinding force is large, in order to respond quickly, the fuzzy controller with a self-tuning factor is adopted and the Max-Proc strategy is also used. This will be good for fuzzy reasoning. If t...

During the past several years, fuzzy control has emerged as one of the most active and fruitful areas for research in the applications of the fuzzy set theory, especially in the realm of the industrial processes, which do not lend themselves to control by conventional methods because of a lack of quantitative data regarding the inputoutput relations i.e., accurate mathematical models. The fuzzy...

In the sewage treatment system, the dissolved oxygen concentration control, due to its nonlinear, time-varying, large time delay and uncertainty, is difficult to establish the exact mathematical model. While the conventional PID controller only works with good linear not far from its operating point, it is difficult to realize the system control when the operating point far off. To solve the ab...

This paper deals with the experimental control of a rotating active magnetic bearing (AMB) system using PID-type fuzzy controllers (PIDFCs) with parameter adaptive methods. There are three kinds of parameter adaptive methods, including fuzzy tuner, function tuner, and relative rate observer, have been proposed in literatures for tuning the coefficients of PIDFCs. However, only a simulation comp...

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...

Permanent Magnet Synchronous Motor (PMSM) is a non-linear, complex time-varying system. The control performance is not satisfactory in the traditional PID control method. Based on the combination of PI and fuzzy control, the controller of fuzzy self-adaptive PI was designed in this paper. The PID parameters can be set with fuzzy algorithmic approach automatically. Experimental results show that...

This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the basе of system’s state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simu...