Control
hadi chahkandi nejad; Mohsen Farshad; Ramazan Havangi
Abstract
In this study, an adaptive controller for LTI systems with unknown and time varying input time delay is presented with the purpose of tracking. Due to the large area considered for time delay variations, the structure of the proposed controller is considered to be in form of Multiple Model Adaptive Control ...
Read More
In this study, an adaptive controller for LTI systems with unknown and time varying input time delay is presented with the purpose of tracking. Due to the large area considered for time delay variations, the structure of the proposed controller is considered to be in form of Multiple Model Adaptive Control (MMAC). The presented adaptive control system is of indirect type, i.e., at any moment of time, first, one band of time delay is identified using a proposed estimator, and then with a switching rule in the supervisory subdivision, the main control signal, which is a linear combination of multiple controllers output, forms. In fact, each of the multiple controllers in MMAC structure with optimal weights, participate in forming the main control signal. The multiple controllers used in this study are of PID type. It should be noted that the parameters for each of the multiple controllers, for the system under control, are adjusted offline and proportional to its corresponding time-delay sub-band using the genetic algorithm. Finally, simulation results show the relatively desirable performance of the proposed control system and observer in facing with large unknown and time varying delays.
Control
Hojjat Hajiabadi; Mohsen Farshad; MohammadAli Shamsinejad
Abstract
Fossil fuel combustion in power plants is the world’s most significant threat to people’s health and the environment. Recently, wind power, as a clean, sustainable and renewable source of energy, has attracted many researchers. The present paper studies how to maximize the extraction of wind ...
Read More
Fossil fuel combustion in power plants is the world’s most significant threat to people’s health and the environment. Recently, wind power, as a clean, sustainable and renewable source of energy, has attracted many researchers. The present paper studies how to maximize the extraction of wind power and the efficiency of a switched reluctance generator (SRG) by firing angles control. The proposed scenario comprises the optimization of turn-on and turn-off angles in the offline mode using a particle swarm optimization algorithm to control the system in the online mode with linear interpolation. The present approach simultaneously investigates the firing angles; also, it has simple structure, low execution time, and efficient convergence rate that are independent of machine characteristics (regardless of high nonlinearity of SRG). Furthermore, copper losses, as well as switching and conduction losses of semiconductors, were considered in simulations to achieve a more realistic outcome. Ultimately, the simulation results of a typical three-phase 6/4 generator using Matlab confirmed the validity of the presented control strategy that can easily find applications in the future.
