An adaptive input-output linearization method for general nonlinear systems is developed without using states of the system. Another key feature of this structure is the fact that, it does not need model of the system. In this scheme, neurolinearizer has few weights, so it is practical in adaptive situations.  Online training of neuroline...

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...

An adaptive version of growing and pruning RBF neural network has been used to predict the system output and implement Linear Model-Based Predictive Controller (LMPC) and Non-linear Model-based Predictive Controller (NMPC) strategies. A radial-basis neural network with growing and pruning capabilities is introduced to carry out on-line model identification.An Unscented Kal...

this paper presents fuzzy and conventional performance of model reference adaptive control(mrac) to control a dc drive. the aims of this work are achieving better match of motor speed with reference speed, decrease of noises under load changes and disturbances, and increase of system stability. the operation of nonadaptive control and the model reference of fuzzy and conventional adaptive contr...

In order to improve the optimal performance of a machining process, a booster to improve the serve control system performance with high stability for EDM is needed. According to precise movement of machining process using electrical discharge (EMD), adaptive control is proposed as a major option for accuracy and performance improvement. This article is done to design adaptive controller based o...

in this paper, the design and implementation of adaptive speed controller for a sensorless synchronous reluctance motor (synrm) drive system is proposed. a combination of well-known adaptive input-output feedback linearization (aiofl) and adaptive backstepping (abs) techniques are used for speed tracking control of synrm. the aiofl controller is capable of estimating motor two-axis inductances ...

Model predictive controller is widely used in industrial plants. Uncertainty is one of the critical issues in real systems. In this paper, the direct adaptive Simplified Model Predictive Control (SMPC) is proposed for unknown or time varying plants with uncertainties. By estimating the plant step response in each sample, the controller is designed and the controller coefficients are directly ca...

in this paper, the enhancement of vehicle stability and handling is investigated by control of the active geometry suspension system (ags). this system could be changed through control of suspension mounting point’s position in the perpendicular direction to wishbone therefore the dynamic is alternative and characteristics need to change. for this purpose, suitable controller needs to change mo...

This paper presents a novel indirect adaptive Power System Stabilizer (PSS) via a developed synergetic control methodology and fuzzy systems. Fuzzy system is utilized in an adaptive scheme to estimate the system using a nonlinear model. The synergetic control guarantees robustness of the controller and makes the controller easy to implement because of using a chatter free continuous control law...