The DC motor is being rapidly replaced in the industry by permanent magnet synchronous (PMSM), which has a number of benefits over it. Nonlinear equations are used to describe dynamics PMSM. It susceptible unidentified external disturbances (load), and its properties change time. These constraints make it more difficult exercise control. To overcome non-linearities aforementioned shortcomings, non-linear controls necessary. This manuscript refers development sturdy high-caliber position...

The dynamics of the permanent magnet synchronous motor (PMSM) are described by nonlinear equations, which present challenges. Variations in external factors such as unidentified disturbances (loads) and evolving properties add complexity to control efforts. To tackle these intricacies limitations, a approach is essential. Recent attention has turned employing predictive techniques for multivariable systems, offering an intriguing avenue research. In this context, study introduces novel...

This paper presents a novel control approach for indoor temperature regulation in tertiary buildings, based on predictive functional control. The main objective is to reduce the energy consumption while ensuring desired thermal comfort of occupants. novelty this may perform presence disturbances such occupancy profile, electrical equipment, temperature, surrounding temperatures and weather data. Predictive algorithm consists using dynamic model process inside controller real time order...

Abstract In the last few years there has been a great deal of interest in application adaptive and supervisory control linear systems using multi‐models multi‐controllers based on switching tuning algorithms. this paper methodology closed‐loop approach is developed for nonlinear evaluated simulation continuous stirred tank reactor (CSTR) process two scenarios according to different set‐point variations. The results show effectiveness terms performance robustness characteristics proposed...

A Backstepping adaptive control is proposed in this paper order to raise the extraction of power variable speed wind turbine region two. This modeled by two masses drive-train with generator torque control. By using model obtained, an algorithm has been designed achieve global asymptotic tracking and estimate unknown parameter viscous friction coefficient. numerical simulation studies are presented verify efficiency approach, if we add disturbances take advantage

The nonlinearities present in photovoltaic (PV) generator models can significantly impact the performance of PV systems, leading to decreased system efficiency and reduced profitability. This paper is aimed at addressing these challenges by developing a novel control algorithm based on high-performance adaptive method for systems. proposed designed effectively track set points optimize power extraction even presence disturbances. key contribution this work lies application strategy...

The building sector is considered a major consumer of energy among all economic sectors. It represents approximately 40 percent consumption. An important associated with heating systems. main objective this paper to use novel supervisory control strategy based on RBF neural networks architecture achieve good temperature regulation in zone and insure operational safety the presence different types disturbances such as neighborhood temperatures, weather data. simulation results for situations...

Photovoltaic systems have earned recognition as incredibly interesting renewable energy sources, due to simplicity of supply. These a nonlinear characteristic which causes them low conversion. However, it necessity for control capable outperforming conventional controllers and overcome the existing operational instabilities. The main objective this paper is design predictive functional photovoltaic generators, make follow desired trajectory generate maximum power. A defined advanced exploit...

In the last few years there was a great deal of interest in application adaptive and supervisory control linear systems using multi-models multi-estimators based on switching tuning. The aim this paper is to apply methodology highly nonlinear continuous stirred tank reactor process (NCSTRP), which very useful chemical biochemical engineering industries, other hand tackle some drawbacks closed-loop control. Closed-loop algorithm has been used as technique for identification models set same...

In recent years identification and control algorithms applied to heating, ventilation air conditioning (HVAC) systems have been paid an increasing attention. The main idea of this paper is exploit the learning capacity Radial Basic Function Neural Networks (RBFNN) for adaptation multi-zone building heating regulation. Several inputs disturbances that influence indoor temperature are considered. simulation results demonstrate efficacy strategy in terms minimal energy consumption desired...

The production of power in photovoltaic systems depends on the solar cells temperature and radiation. To improve energy yield PV modules, it is indispensable, order to follow maximum generator. main idea our work develop a new control approach based indirect adaptive strategy applied system ensure good tracking setpoint obtain power, spite appearance different disturbances. novelty this exhibited by its simplicity robustness. simulation results illustrate effectiveness performances method.

Heating systems are becoming an increasingly important research subject in the building field because, they main element used to improve occupants comfort. This work is being done comfort while also reducing energy consumption by employing a new proposed optimized neural network control approach for commercial space's temperature regulation system genetic algorithm. The key goal decrease electricity maintaining occupants' optimum thermal approach's originality may allow it face of...

Nowadays the decrease of energy consumption is a world target and it no longer feasible to design system without concerning optimization. An important consumer associated with building heating systems. The main objective this paper make comparative study between two neural network architectures; first not recurrent, Radial Basis Function (RBF) second Recurrent Memory Neural Networks (RMNN) for adaptive control strategy from one room in order minimize reducing comfort occupants. method was...

This paper presents the contribution of a matrix converter for frequency stabilization an energy source. Venturini optimal amplitude method is used. The source assumed to be purely random. A new approach based on concept Lyapunov's functions revealed. study done electrical network with random variable frequency, following normal distribution and typical RL load. tested using simulations under MATLAB® /Simulink® environment. criteria used in analysis are signal form, analysis, THD....