Integral Derivative Controller Research Articles

An Improved Marine Predators Algorithm-Tuned Fractional-Order PID Controller for Automatic Voltage Regulator System

One of the most popular controllers for the automatic voltage regulator (AVR) in maintaining the voltage level of a synchronous generator is the fractional-order proportional–integral-derivative (FOPID) controller. Unfortunately, tuning the FOPID controller is challenging since there are five gains compared to the three gains of a conventional proportional–integral–derivative (PID) controller. Therefore, this research work presents a variant of the marine predators algorithm (MPA) for tuning the FOPID controller of the AVR system. Here, two modifications are applied to the existing MPA: the hybridization between MPA and the safe experimentation dynamics algorithm (SEDA) in the updating mechanism to solve the local optima issue, and the introduction of a tunable step size adaptive coefficient (CF) to improve the searching capability. The effectiveness of the proposed method in tuning the FOPID controller of the AVR system was assessed in terms of the convergence curve of the objective function, the statistical analysis of the objective function, Wilcoxon’s rank test, the step response analysis, stability analyses, and robustness analyses where the AVR system was subjected to noise, disturbance, and parameter uncertainties. We have shown that our proposed controller has improved the AVR system’s transient response and also produced about two times better results for objective function compared with other recent metaheuristic optimization-tuned FOPID controllers.

Design of Sliding Mode Control Strategy for DC Motor

Abstract: This research paper presents a comparative study ofsliding mode control (SMC) strategies and proportional- integralderivative (PID) control for DC motor applications. The project involves the design and implementation of PID and SMC controllers, as well as the evaluation of their respective response characteristics. Furthermore, the SMCcontroller is designed using three different sliding surfaces to analyze their impact on the control system's performance. A model is developed and simulated usingMATLAB/SIMULINK. Overall, the simulation results show that sliding mode controller is superior than PID for speed control of dc motor.

Ant Colony Optimization of Fractional-Order PID Controller based on Virtual Inertia Control for an Isolated Microgrid

Background: Increasing the penetration of renewable energy sources has become necessary, especially in isolated microgrids. This increase leads to a decrease in the total inertia of the microgrids, which affects microgrid stability. Moreover, voltage and frequency control in lowinertia microgrids is more difficult and sensitive. Objective: Improve low inertia isolated microgrids' dynamic response and save the microgrid stability at different contingency and uncertainty conditions. Moreover, it allows for more penetration of renewable energy sources. Method: Proposing different control strategies based on virtual inertia control. The first is a proportional- integral-derivative (PID) controller, and then, to allow for more tuning flexibility, a fractional- order proportional-integral-derivative (FOPID) controller is used. MATLAB TM/Simulink is used to compare the response of the isolated microgrid without virtual inertia control, with conventional virtual inertia control, PID-based virtual inertia control, and FOPID-based virtual inertia control. The PID and FOPID controllers’ parameters are tuned using the ant colony optimization (ACO) technique. Results: The proposed control techniques save the isolated microgrids' stability at different penetration levels of renewable energy sources and operating conditions. At the same time, the isolated microgrid without virtual inertia control or conventional virtual inertia control can not save its stability in many operating conditions. Conclusion: The proposed fractional-order proportional-integral-derivative (FOPID)-based virtual inertia control has proven its effectiveness in saving the isolated microgrid stability and gives the best controller response. FOPID-based virtual inertia control minimizes the frequency deviation with different disturbances and operating conditions.

Proportional–integral and proportional–derivative controller design based on analytically computed centroid point for controlling integrating processes

The proportional–integral and proportional–derivative controller is characterized by its capability to effectively control integrating processes compared with proportional–integral/proportional–integral–derivative controllers. Recently, several graphical methods have been proposed for tuning the PI-PD controller parameters by computing the centroid point of the stability boundary locus. However, these approaches are time-consuming because they entail plotting the stability boundary locus for finding the centroid point. Another disadvantage of those design methods is that the design procedure has to be redone as the transfer function changes. In this article, a generalized stability boundary locus is constructed in terms of the controller and assumed plant transfer function model parameters to enable the designer to avoid replotting the stability boundary locus as the process transfer function changes. More importantly, two analytical approaches, which simplify the design of the proportional–integral and proportional–derivative controller very much, are proposed to compute the centroid point of the generalized stability boundary locus. Analytical expressions for computing the performance measures of the designed closed-loop system have also been provided so that one can predict the performance of the designed closed-loop system. It has been shown by simulation examples that the analytical centroid of convex stability region method provides quicker responses with faster disturbance rejections compared to other reported design methods. Also, the simulation results have displayed that analytical weighted geometrical center gives more robust closed-loop responses in terms of gain margin, phase margins, and maximum sensitivity than analytical centroid of convex stability region. Finally, the feasibility of the proposed methods is tested using a real-time application based on an aerodynamical system. Real-time results have demonstrated that the analytical centroid of convex stability region and analytical weighted geometrical center methods give quicker responses with small overshoots compared to other reported methods.

Single Spectral Line Method for TDLAS Imaging of Temperature and Water Vapor Concentration

A single spectral line method for gas temperature as well as concentration extraction was proposed by using iterations with a fuzzy proportional–integral-derivative (PID) controller in tunable diode laser absorption spectroscopy (TDLAS). Usually, two or more spectral lines are essential to extract temperatures from coupled gas concentration and pressure. The proposed method utilized the line shape of a single absorption spectrum to decouple gas parameters along the laser path simultaneously and simplified the optical implementations. Differential equations of the Voigt profile were introduced at multiple wavenumbers to extract gas parameters from a single spectral line. A fuzzy PID controller was utilized to iteratively achieve the single spectral line from widely existed overlapping spectra. A relative temperature error within 2.5% at reference temperatures ranged from 300 to 2300 K was achieved by using the spectral line of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7444.35\,\,{\mathrm {cm}}^{-1}$ </tex-math></inline-formula> from noise free data. At low temperatures below 350 K, the proposed method using the single spectral line of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7181.14\,\,{\mathrm {cm}}^{-1}$ </tex-math></inline-formula> yielded smaller errors in noisy cases, and the temperature errors were verified within 5 °C on the water-based thermostat below 100 °C using the single spectral line. Experiments of axisymmetric counterflow flames at different heights were also implemented. The proposed method effectively reconstructed distributions of flame temperature and water vapor concentration inside, by only using a single spectral line of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$7444.35\,\,{\mathrm {cm}}^{-1}$ </tex-math></inline-formula> .

LQG, PID controller, ANN for single axis gimbal actuator

Gimbal or other stable platforms have structures that move according to its functions. This is for the purpose of keeping track of the goals to the fullest. Tracking targets can become difficult as the subject moves further and further away and they are out of the gimbal’s allowable viewing range. Besides, under the influence of noise signals form outside space, it becomes even more difficult to observe the gimbal’s targets. To overcome above disadvantages, this paper is presented an adjustment method to limit above risks. Adjusting Linear Quadratic Gaussian (LQG) for expensive gimbal systems, noise signals are processed purely by Kalman filters to improve the function of observing targets. In addition, proportional- integral-derivative (PID) controller, artificial neural network in this case is also considered to verify the effectiveness of control methods listed below. In particular, ANN is the most effective control method today to deal with unwanted signals. These unwanted signals can cause worsening conditions during the operation of systems.Therefore, artificial network (ANN) is a solution to information and communication security problems. Simulation is done by Matlab. Novelty of the work: no previous research has been published for this genre. The study of this genre with the use of artificial intelligence is suggestive of the study of artificial intellligence technologies at a higher level. This category is also a suggestion for studying a smoother control method based on existing data.

Comparative Study of Different Controllers for Levitating Ferromagnetic Material

The purpose of the analysis is to levitate and stabilize a spherical ball of magnetic levitation system at the desired position using various controllers and determine the one which gives better performance. The ball which is used to levitate is a ferromagnetic material such as stainless steel. This study talks about the proportional derivative controller, proportional integral derivative (PID) controller, and linear quadratic regulator (LQR) controller in place of a physical system. The transient response of the magnetic levitation system can be modified for desirable results due to the implementation of the controller. Simulation and experimental methods are used to verify the results. Both the techniques have been made to stabilize the ball position in the desired position. PID and LQR are designed to achieve the ball position to the desired level, and it is observed that the LQR controller gives the best result.

Modeling and Controller Design for Temperature Control of Heat Exchangers in Power Plants

A heat exchanger is a device that transfers heat from one place to another. Because it can withstand a wide range of temperature and pressure, the power plant heat exchanger is widely employed in chemical and petroleum facilities. A heat exchanger is a device that transfers heat from one place to another. Plant with strong nonlinearity and low dynamics; as a result it is tough to model and manage its dynamics. There are two types of heat exchanger models in this study. For selecting an appropriate model, controllers are used. Controller. (Physical model) is the first model. Generated from genuine heat exchanger plant parameters Second, there's Dead Time plus a Second Order (SOPDT model)This is obtained from the heat exchanger's response. While The controllers are made up of fuzzy proportional controllers. Proportional integral (FPD) controller and derivative (FPD) controller applied to the model as a derivative (PID) controller Their comments are compared to those of the others. Keywords Power Plant Heat Exchanger, Modelling, Fuzzy Control.

Research on position/force hybrid control of an FFHD robot with EHS-actuators

An Electro-Hydraulic Servo (EHS) Four-Footed Heavy-Duty (FFHD) robot is designed and developed in this work. An integration layout cylinder design scheme for the non-lightweight EHS four-footed robot with high loads and hip joint torques is proposed, and a mathematical element analysis model for a parallel EHS cylinder system is derived. Multiple inherent characteristics of the parallel-executed cylinder integration system model are then further explored. Based on the controllable functional requirements of interconnected joints and the influence reduction in internal force coupling, a force/position hybrid control scheme for the parallel-executed cylinder is determined, and the force/position signal module design unit is used to solve the force/position hybrid control in reverse. The implementation process of magnetic flux compensation and speed compensation is discussed in detail, considering the inherent requirements of the EHS-executed cylinder force control unit module. A compliant controller is then applied to the EHS-executed cylinder force unit module, and the proportional integral derivative (PID) controller is determined in the EHS-executed cylinder position control unit module. The compound control strategy proposed in this paper is verified on a parallel EHS platform. The experimental verification results reveal that the values of position/force attenuation amplitude and lag phase are no greater than 10.0% and 20°, respectively. The feasibility of the interconnected implementation of the proposed hybrid control scheme is then analyzed. The conclusions obtained in this research provide relevant insights for the application of FFHD robot control systems.

Modelling and Control of a Dosing Pump for Water Treatment Plants

This paper presents modelling and control of a dosing pump for effective production of high quality potable water for public consumption and utilisation. A mathematical model of a dosing pump is described in this study. Furthermore, the application of a model predictive control (MPC) algorithm to control the dosing pump in order to hold the output variable of the pump as close as possible to the set point without violating the constraints of pump input and output variables is examined. Simulations results of the servo-control and regulatory-control responses of MPC, Proportional Integral (PI) and Proportional Integral Derivative (PID) control algorithms show that MPC performs best when compared with the PI and PID controllers.

Speed Regulation of a Permanent Magnet DC Motor with Sliding Mode Control Based on Washout Filter

The accuracy of control systems applied to motors is influenced by uncertainties and abrupt variations of the load and system parameters. Some robust control strategies have been proposed in the literature for responding to disturbances and uncertainties, parametric variations, and non-linearities, adding complex control rules and considerable computational efforts. Therefore, this paper presents the application of a sliding mode control method based on a washout filter (SMC-w) for speed control in a permanent magnet DC motor. In addition, the dynamic behavior of the SMC-w is evaluated under changes in the reference speed and load torque. The response of the control system under variations of the speed reference signal and load torque were studied. The results were contrasted with conventional proportional integral derivative (PID) control to evaluate the efficiency and improvement of the SMC-w. The qualitative shape of the transient response of the speed and current concerning changes in the reference speed is symmetric for the SMC-w controller, but the values of overshoot, settling time, and steady-state error are different. This technique has a great potential for industrial application as it controls efficiently with low computational cost and a simple design, which benefits its implementation in practical environments.

A Novel Grey Wolf Optimizer Based Load Frequency Controller for Renewable Energy Sources Integrated Thermal Power Systems

The frequency value should be kept constant to ensure and maintain synchronization in power systems. When the balance between generation and load is interrupted, the frequency value increases or decreases. This frequency deviation may lead to serious problems in the power system. Therefore, a design of a controller is required to keep the system frequency and tie-line power variations within specified limits, which is called automatic generation control (AGC) or load frequency control (LFC). This paper aims to determine the optimal controller parameters used in the LFC for a two-area non-reheat thermal power system integrated with various renewable energy sources (RES) such as photovoltaic (PV) and wind energy systems. The proposed controller is a PI–(1 + DD) controller which is a combination of proportional, integral, and double derivative controllers. The optimal gains of the proposed controller are determined by the Grey Wolf Optimization (GWO) algorithm. Moreover, the performance of the PI–(1 + DD) controller is tested under various scenarios such as different step load perturbations, random load changes, system parameters and RES variation. The results show that the PI–(1 + DD) controller provides an improvement of about 40% in system frequency overshoot and about 45% in settling time compared to other controllers.

MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink

In this paper, a battery charging model is developed for solar PV system applications. As a means of photovoltaic power controlling system, buck-boost converter with a Maximum Power Point Tracking (MPPT) mechanism is developed in this paper for maximum efficiency. This paper proposed a novel combined technique of hybrid Particle Swarm Optimisation (PSO) and Salp Swarm Optimization (SSO) models to perform Maximum Power Point Tracking mechanisms and obtain a higher efficiency for battery charging. In order to retrieve the maximum power from the PV array, the Maximum Power Point Tracking mechanism is observed which reaches the maximum efficiency and the maximum power is fed through the buck-boost converter into the load. The buck-boost converter steps up the voltage to essential magnitude. The energy drawn from the PV array is used for the battery charging by means of an isolated buck converter since the buck-boost converter is not directly connected to the battery. The Fractional Order Proportional Integral Derivative (FOPID) controller handles the isolated buck converter and battery to enhance the efficiency obtained through the Maximum Power Point Tracking mechanism. The simulation results show higher steady efficiency by using the hybrid PSOSSO algorithm in all stages. The battery is charged without losing the efficiency obtained from the hybrid PSOSSO algorithm-based Maximum Power Point Tracking mechanism. The higher efficiency was obtained as 99.99% at Standard Test Conditions (STC) and 99.52% at PV partial shading conditions (PSCs) by using the new hybrid algorithm.

Power Stability and Frequency Control Techniques of DG for a High Penetration Wind-Based Energy Storage System Using Integral–Derivative Controller

Distributed generation (DG) has environmental as well as economic benefits and develops new concepts to make the power network more effective and minimize pollution in the environment. Being the fluctuation behavior of renewable energy sources (RESs), generation, balance, and demand is not an easy task to control because it is not desirable to have a constant power generation from RESs due to natural prospects. As a result, the dynamic stability of power flow and control of frequency is becoming more challenging due to the high penetration impacts of RESs. In this article, we have proposed a control algorithm with two scenarios for a high-penetration/hybrid diesel wind-based energy storage system to maintain the dynamic stability of power flow and control the frequency in the overall power system. The results show, using an integral–derivative (I–D) controller, the transient time of wind power flow and the fluctuation rate of frequency are reduced significantly compared to the prior research of publication. To regulate the network frequency, a storage system (battery) was used to store the excess energy without throwing it to the secondary/dump load (DL) and minimize the wastage of power produced by the wind turbine. The battery was supplied the excess wind power when there is a high load demand.

Analysis of tilt integral derivative controller-based automatic load frequency control of multi-area multi-source system

Analysis of tilt integral derivative controller-based automatic load frequency control of multi-area multi-source system

Analysis of tilt integral derivative controller-based automatic load frequency control of multi-area multi-source system

Analysis of tilt integral derivative controller-based automatic load frequency control of multi-area multi-source system

Novel load frequency control scheme for hybrid power systems employing interline power flow controller and redox flow battery

ABSTRACT This article proposes a novel load frequency control (LFC) scheme for hybrid power systems (HPS) in the presence of Interline Power Flow Controller (IPFC) and redox flow battery (RFB). Due to the vagueness nature of solar energy and wind energy sources present in the HPS, the LFC problem is a critical task in HPS. For this study, a fuzzy proportional integral derivative (FPID) controller with hybrid salp swarm algorithm and pattern search algorithm (hSSA-PS) is used to optimize the controller parameter of the HPS system under random and stochastic environments. The usefulness of the proposed hSSA-PS algorithm is established over salp swarm algorithm (SSA), genetic algorithm (GA) and Particle swarm optimization (PSO) algorithms. The performance of the system under study is evaluated with/without the presence of IPFC and RFB. It is observed that system performance is improved with the presence of an IPFC controller and RFB. The robustness of the proposed controller is justified by conducting sensitivity analysis. It is noticed that in presence of the proposed FPID controller the reduction in ITAE/IAE/ISE values is 92.18%, 90.84 and 98.52% as compared to PID controller and 31.42%, 86.90% and 90% as compared to PID controller in the occurrence of IPFC and RFB under stochastic environment. The robustness of the proposed controller is justified by conducting a sensitivity analysis. Also, the outperformance of the suggested controller is contrasted with some advanced controllers reported in some recent papers.

Fractional Order PID Design Using Big Bang–Big Crunch Algorithm and Order Reduction: Application to Load Frequency Control

—A new technique for tuning a fractional order proportional integral derivative (FOPID) controller is presented and analyzed for load frequency control of power systems. The proposed technique involves model order reduction for model simplification, internal model control for initial estimation of PID gains to formulate a compact solution space required for big bang–big crunch (BB–BC) algorithm, which ascertains optimal FOPID parameters in the search space delineated via IMC technique. The beauty of the proposed approach is that it gives an innovative way to incorporate soft computing algorithms in control applications in such a manner that leads to reduction in randomness associated with heuristic techniques. To validate the effectiveness of the proposed scheme, it is implemented on a power system comprising of reheated turbine and a realistic model of IEEE 10 machine 39 bus New England system in presence of nonlinearities. A comprehensive comparative analysis with other recent controller design techniques, conducted in terms of simulation plots, performance indices and statistical parameters is a testimony to efficacy of proposed technique.

Comparative Analysis and Controller Design for BLDC Motor Using PID and Adaptive PID Controller

This paper describes the Adaptive PID (APID) controller design for speed control preference of Brushless Direct Current (BLDC) motor over the Proportional Integrative Derivative (PID) controller. A methodology of the Adaptive PID controller is proposed, which tunes the parameters automatically. Modeling of the BLDC motor was carried out using PID and Adaptive PID controller, respectively. The behavior of the BLDC motor is analyzed without a controller and by using the conventional PID controller and the new APID controller. Hence the result obtained is analyzed and compared by taking two cases. In the first case of constant speed, the PID controller gave large variability in the initial speed and could not track the desired speed. Also, applied torque could not track the desired speed due to a significant deviation in the actual motor speed. Whereas, in the case of APID, the controller gave small variability in the initial speed and could track the desired motor speed. In the second case of variable speed, the PID controller produced a random response at a variable speed. Whereas, in APID, the controller had an accurate response at variable speed, with no deviation. The result obtained shows that the APID controller provides effective, easier, and fast controlling of the BLDC motor. The output response of the BLDC motor is achieved, and the result is analyzed with the help of utilizing MATLAB and SIMULINK. Background: The BLDC motor is considerably used in the home, transportation, and industrial application. Objective: Comparative analysis of modeling and control of BLDC motor drives for the variable required speed. Methods: PID and APID controllers are used in this paper to operate the BLDC motor. Results: A Fixed and variable speed response of both APID and PID controlled BLDC motor is obtained. Conclusion: Response of the speed control of APID controlled BLDC motor is superior to PID controlled BLDC motor at variable speed.

Design and Development of ROSMC-Based Single-Stage Z Source Inverter for Power Quality Enhancement in Hybrid Electric Vehicle Applications

This research work focuses on the design and analysis of the single-stage reduced order sliding mode control (ROSMC)-based Z-source inverter (ZSI) using sinusoidal pulse width modulation (SPWM) technique for improving the output power quality. To enhance the ZSI output voltage, the shoot-through (ST) mode is executed. Reduced 2nd order model of ZSI is derived from original 6th order model using moment matching method to reduce the sensor requirements and complexity in controller design. The closed loop control is accomplished using cascade control technique to investigate the system’s dynamic response. A Genetic Algorithm (GA)-tuned Proportional Integral (PI) controller is used for the outer voltage control. GA-tuned PI/ROSMC-based SPWM control technique has been attempted for inner current control. Sinusoidal reference signal is generated by the inner current control loop. Internal Model Control (IMC)-tuned Proportional Integral derivative (PID) controller is used to minimise the effect of Right Half-Plane zero, and it also produces required shoot-through duty ratio (STDR). Simulation results illustrate that the ROSMC-based SPWM technique provides superior performance than GA-tuned PI-based SPWM control technique. An experimental prototype model of 2 kW ZSI, ROSMC-based SPWM control is implemented using SPARTAN-6 field programmable gate array. The simulation results are substantiated with the hardware results.