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...

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...

nonlinear static procedure (nsp) is a common technique to predict seismic demands on various building structures by subjecting a monotonically increasing horizontal loading (pushover) to the structure. therefore, the pushover analysis is an important part of each nsp. accordingly, the current paper aims at investigating the efficiencyof various algorithms of lateral load patterns applied to the...

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...

In this study, an extended stress-based forming limit diagram (FLD) for prediction of necking based on the Marciniak and Kucznski (M-K) model is represented and applied in tube hydroforming. The bulge forming of a straight tube is simulated by finite element method and verified with published experimental data. This adaptive simulation technique is based on the ability to detect the onset an...

In this paper, the optimal adaptive leader-follower consensus of linear continuous time multi-agent systems is considered. The error dynamics of each player depends on its neighbors’ information. Detailed analysis of online optimal leader-follower consensus under known and unknown dynamics is presented. The introduced reinforcement learning-based algorithms learn online the approximate solution...

The undesired operation of zone 3 may be one of the most conspicuous protective relay features due to the incorrect zone 3 relay operations which have been conducive to the severity of blackouts. Therefore, determining the accurate zone 3 setting of the distance relay is deemed to be necessary. This paper focuses on the development of a new technique for calculating zone-3 setting of distance r...

This paper proposes a new adaptive importance sampling (AIS) technique for approximate evaluation of multidimensional integrals. Whereas known AIS algorithms try to find a sampling density that is approximately proportional to the integrand, our algorithm aims directly at the minimization of the variance of the sample average estimate. Our algorithm uses piecewise constant sampling densities, w...