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...

2. Direct Adaptive Control of Scalar Plant. Let us begin with a simple scalar adaptive system, ẋp(t) = apxp(t) + kpu(t) (1) where xp(t) ∈ R is the plant state, u(t) ∈ R is the control input, ap ∈ R is an unknown scalar and only the sign of kp ∈ R is known. For the direct adaptive controller we choose a reference model as ẋm(t) = amxm(t) + kmr(t)− l(x(t)− xm(t)). (2) All of the parameter above a...

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, an optimal adaptive sliding mode controller is proposed for anti-synchronization of two identical hyperchaotic systems. We use hyperchaotic complex T-system for master and slave systems with unknown parameters in the slave system. To construct the optimal adaptive sliding mode controller, first a simple sliding surface is designed. Then, the optimal adaptive sliding mode controll...

The present research produces a new technique for the optimum operation of an isolated microgrid (MGD) based on enhanced block-sparse adaptive Bayesian algorithm (EBSABA). To update proportional-integral (PI) controller gains online, suggested approach considers impact actuating error signal as well its magnitude. reach compromise result between various purposes, Response Surface Methodology (R...