A robust self-organizing fuzzy-neural control (RSOFNC) system is proposed in this paper. The RSOFNC system is comprised of a self-structuring fuzzy neural network (SFNN) controller and a robust controller. The SFNN controller is the principal controller and the robust controller is designed to achieve tracking performance. In the SFNN controller design, a SFNN with the asymmetric Gaussian membe...

Despite the popularity of PID (Proportional-Integral-Derivative) controllers, their tuning aspect continues to present challenges for researches and plant operators. Various control design methodologies have been proposed in the literature, such as auto-tuning, self-tuning, and pattern recognition. The main drawback of these methodologies in the industrial environment is the number of tuning pa...

In this paper an adaptive PID controller for Wind Energy Conversion Systems (WECS) has been developed. Theadaptation technique applied to this controller is based on Reinforcement Learning (RL) theory. Nonlinearcharacteristics of wind variations as plant input, wind turbine structure and generator operational behaviordemand for high quality adaptive controller to ensure both robust stability an...

This paper proposes an approach to tune an Adaptive Neuro Fuzzy Inference System (ANFIS) inverse controller using Iterative Learning Control (ILC). The control scheme consists of an ANFIS inverse model and learning control law. Direct ANFIS inverse controller may not guarantee satisfactory response due to different uncertainties associated with operating conditions and noisy training data. In t...

control of well drilling operations poses a challenging issue to be tackled. the loss of well control could lead to the occurrence of blowout as a severe threat, involving the risk of human lives and environmental and economic consequences. conventional proportional-integral (pi) controller is a common practice in the well control operation. the small existing margin between pore pressure and f...

A new set of tools, including controller scaling, controller parameterization and practical optimization, is presented to standardize controller tuning. Controller scaling is used to frequency-scale an existing controller for a large class of plants, eliminating the repetitive controller tuning process for plants that differ mainly in gain and bandwidth. Controller parameterization makes the co...

This paper studies the fuzzy PID controller design algorithm, and it has set up a hardware platform for the temperature control system thermal analyzer, respectively with MATLAB tools to conventional PID and fuzzy PID control method has carried on the simulation analysis, and in the actual building experiments have been carried out to test system platform. Experimental results show that the fuz...

This paper presents two new controllers and uses an extension of the generalized secant method of solving linear equations. 1] The rst controller is adaptive and operates in the time domain. The second one is a learning-adaptive controller which uses a similar mathematical concept, but it is formulated to deal with repetitive systems with repetitive disturbances. This controller operates in the...

This paper presents the derivation of a new computationally efficient self-tuning controller with a proportional plus integral plus derivative (PID) structure which incorporate the effectiveness the Feed forward Feedback (FF-FB) control. The main feature of the proposed design is a combination of the advantages of implicit self-tuning property, in which the controller parameters tuned automatic...