This paper investigates the closed loop stability of the SEPIC converter using an optimal PID controller; In this model, the parameters are adjusted using the Gray Wolf Multi-Objective (MOGWO) algorithm. The Gray Wolf Multi-Objective Algorithm is a random evolution-insp More
This paper investigates the closed loop stability of the SEPIC converter using an optimal PID controller; In this model, the parameters are adjusted using the Gray Wolf Multi-Objective (MOGWO) algorithm. The Gray Wolf Multi-Objective Algorithm is a random evolution-inspired random algorithm that has been widely used in recent years as an optimization technique in power electronics. The state mode average method has been used to model and achieve the transducer-based system transfer function. Therefore, the MOGWO-based PID controller has been studied and implemented in the system to enable the converter stability to be evaluated and compared with conventional PID controllers. To evaluate the stability of the system, various performance parameters such as overtaking percentage, peak time, settling time and peak size have been considered. The impact response of the closed-loop system is obtained by simulation in MATLAB. The performance of the model is evaluated to perform a general comparative analysis of the system.
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Multi variable control of fuel inlet (FI) and inlet gas vane (IGV) parameters of gas turbine via PID controller in presence of noise, that is discussed in this paper. Nowadays, there is undoubtedly main rules(energy harvesting and high efficiency) of gas turbine in vari More
Multi variable control of fuel inlet (FI) and inlet gas vane (IGV) parameters of gas turbine via PID controller in presence of noise, that is discussed in this paper. Nowadays, there is undoubtedly main rules(energy harvesting and high efficiency) of gas turbine in various industries. Researchers think and discover about different physical parameters of gas turbine. So, they can present model of complicate gas turbine in order to model should be near reality structure and also gas turbine model has more perfect features. Therefore, fuel FI and IGV are critical parameters for increasing and decreasing efficiency of system of gas turbine, where are effected on power system. In this research, we are modeling and simulating gas turbine in frequency and time domains respectively, for controlling FI and IGV parameters based on PID controller in existence of noise signals. PID coefficients are determined on trail and error approach, in order to system preserve or track its velocity, power and temperature of outlet gas in nominal and reference values.
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A micro grid (MG) system that benefits from distributed generation (DG) resources has a non-linear and time-varying nature which encounters the control problem with some difficulties. Also, due to the fact that in the most MG systems the frequency controllers are centra More
A micro grid (MG) system that benefits from distributed generation (DG) resources has a non-linear and time-varying nature which encounters the control problem with some difficulties. Also, due to the fact that in the most MG systems the frequency controllers are centralized in the control room and, the DGs are located at distances from the control room, the occurrence of delay is undeniable and it should be considered in the design of the controller. For this purpose, a self-tuning fuzzy PID controller has been designed for load frequency control in a MG system in the presence of delay. The designed fuzzy PID controller is a nonlinear controller and can handle the nonlinearities. To deal with the delay in the input of the system, the Ziegler-Nichols like criteria has been utilized to derive the adaptive mechanism which tunes the scaling factors according to the maximum amount of delay in the online manner. The proposed self-tuning fuzzy PID controller has been applied for load frequency control of a time-delay MG system and the simulation results have been compared with the results of fixed structure fuzzy PID controller. The simulation results indicate the efficiency of the proposed controllers in dealing with time-varying delay.
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Restructuring of power systems and integration of different renewable energy sources with complex dynamic behaviors and high structural uncertainties has made the issue of load frequency control more important. For a hybrid power system that includes a thermal power pla More
Restructuring of power systems and integration of different renewable energy sources with complex dynamic behaviors and high structural uncertainties has made the issue of load frequency control more important. For a hybrid power system that includes a thermal power plant taking into account nonlinear limitations such as the governor dead band and generator rate constraints and renewable energy sources including a wind turbine, solar-thermal power plant, electrolyzer, fuel cell, and plug-in electric vehicle, this paper proposes an adaptive wavelet neural network fractional order PID controller (AWNNFOPID) based on self-recursive wavelet neural networks and fractional order PID controller. To compare the performance of the proposed AWNNFOPID controller, four different scenarios are considered and the simulation results are compared with traditional I, PI, and PID controllers as well as with the optimized FOPID controller. The simulation results show that the proposed AWNNFOPID controller has better performances than the other control strategies used for the studied hybrid power system based on performance indicators such as settling time, rise time, maximum overshoot, maximum undershoot, integral time absolute error (ITAE), and integral absolute error (IAE).
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Physical systems always include constraints and limits. Usually, the limits and constraints, in the control systems, are appeared as temperature and pressure limits or pumps capacity. One of the existing limits in the systems with PID controller is associated with the a More
Physical systems always include constraints and limits. Usually, the limits and constraints, in the control systems, are appeared as temperature and pressure limits or pumps capacity. One of the existing limits in the systems with PID controller is associated with the actuator’s saturation limits. With the saturating of the actuator, the controller’s output and plant’s input will be different and the output signal of controller do not lead the system and their states could not update correctly where this issue makes the system response undesirable. In this paper, by adding a fuzzy compensator that it’s parameters are tuned using imperialist competitive algorithm, the actuator saturation is prevented and the important parameters of the system response, such as setting time and overshoot, are improved.
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The idea of using fractional order calculus in control became apparent when this kind of calculus was accepted as a powerful tool in many applications. This resulted in a new generation of PID controller called fractional order PID Controller, named as Controller. More
The idea of using fractional order calculus in control became apparent when this kind of calculus was accepted as a powerful tool in many applications. This resulted in a new generation of PID controller called fractional order PID Controller, named as Controller. controller is more flexible and provides a better response with larger stability region as compared with standard PID controller. This paper presents a simple and reliable method for finding the family of controllers. The required calculations are done in frequency domain based on frequency response of the system and the stability region is specified in the parameters space. This method can be used for time-delay systems and, more generally, for any system with no transfer function.
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A Quadrotor helicopter is an unmanned aerial vehicle (UAV). This vehicle has attracted lots of researchers’ attention because of its unique abilities such as being an under-actuated system, vertical take-off and landing, spot movement, more degree of freedom (DOF) More
A Quadrotor helicopter is an unmanned aerial vehicle (UAV). This vehicle has attracted lots of researchers’ attention because of its unique abilities such as being an under-actuated system, vertical take-off and landing, spot movement, more degree of freedom (DOF) and military and non- military functions. Because of nonlinear and complex dynamic, modeling and controlling this vehicle is one of the most challenging areas in control engineering. In this paper modeling of a Quadrotor will be described using Newton-Euler equations. Stabilizing and controlling of altitude and its attitude are done by three controller including classic PID, Fuzzy- PID and Neural- Fuzzy based on PID. Performances of these controllers are analyzed in the presence of disturbances and mass uncertainties. The main aim of this paper is designing an intelligent PID algorithm which is made by combining fuzzy logic and neural system and it will introduce a Neural- Fuzzy controller which is based on PID. Simulation results are presented by MATLAB software.
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This paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required More
This paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required for designing a set of direct force-modes for the longitudinal axis) based on particle swarm optimization (PSO) algorithm. The autopilot system for military or civil aircraft is an essential component and in this paper, the autopilot system via 6 degree of freedom model for the control and guidance of aircraft in which the autopilot design will perform based on defining the longitudinal and the lateral-directional axes are supposed. The effectiveness of the proposed controller is illustrated by considering HIMAT aircraft. The simulation results verify merits of the proposed controller.
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Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared with the Standard PID controller, two adjustable variables “differential order” and “integral order” are added to the More
Fractional-order PID (FOPID) controller is a generalization of standard PID controller using fractional calculus. Compared with the Standard PID controller, two adjustable variables “differential order” and “integral order” are added to the PID controller.Three tank system is a nonlinear multivariable process that is a good prototype of chemical industrial processes. Cuckoo Optimization Algorithm (COA), that was recently introduced has shown its good performance in optimization problems. In this study, Improved Cuckoo Optimization Algorithm (ICOA) has been presented. The aim of the paper is to compare different controllers tuned with a Improved Cuckoo Optimization Algorithm (ICOA) for Three Tank System. In order to compare the performance of the optimized FOPID controller with other controllers, Genetic Algorithm(GA), Particle swarm optimization (PSO), Cuckoo Optimization Algorithm (COA) and Imperialist Competitive Algorithm (ICA).
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