Classical Integral Controller Research Articles

Adaptive Load Frequency Control in Microgrids Considering PV Sources and EVs Impacts: Applications of Hybrid Sine Cosine Optimizer and Balloon Effect Identifier Algorithms

The negative impacts of microgrids (µGs) on the load frequency highlight the importance of implementing a robust, efficient, and adaptable controller to ensure stability. This work introduces an adaptive load frequency control (LFC) for an isolated µG that includes a PV system and electric vehicles (EVs), which have a significant impact on frequency. This control utilizes a combination of sine cosine optimization (SCO) and balloon effect identifier (BEI) algorithms. The controller presented in this work transforms the LFC process into an optimization problem that is highly compatible with various random situations encountered in the control process. The suggested control method is a novel approach by utilizing SCO+BEI for adaptive LFC application, resulting in a highly efficient response. The effectiveness of the proposed adaptive controller is assessed under the conditions of 17 MW variable load, system parameters uncertainties, and installed PV systems of 6 MW. MATLAB / Simulink package is rummage-sale as a digital test environment. According to simulation results, the proposed adaptive controller succeeds in regulating the frequency and power of an islanded µG. To measure the efficiency of the proposed control scheme, a comparison between other control techniques (such as adaptive controller using Jaya+BEI and classical integral controller) is done. The findings of the studied scenarios assured that the not compulsory control method using (SCO+BEI) has an obvious superiority over other control methods in terms of frequency solidity in case of random load instabilities and parameter uncertainties. Finally, it can be said that the proposed controller can better ensure the safe operation of the µGs.

Frequency Stability Enhancement Using Differential-Evolution- and Genetic-Algorithm-Optimized Intelligent Controllers in Multiple Virtual Synchronous Machine Systems

In this paper, multiple virtual synchronous machines (VISMAs) with fuzzy proportional integral derivative (FPID) controllers optimized by differential evolution (DE) are proposed to maintain frequency stability in the grid in the presence of renewable penetration, such as wind and solar photovoltaic (PV) systems, residential loads, and industrial loads, by reducing the area control error in the objective function. Simulations are conducted using MATLAB/Simulink, and in the optimization process, the integral of the time-weighted absolute error (ITAE) is used as the objective function. In the work to obtain optimized values of renewable energy sources (RESs), fuzzy membership functions, controller gain parameters, and loads for system modeling, differential evolution and genetic algorithm (GA) methods are applied and the results were compared. It was shown that better results were achieved while FPID controllers were optimized by DE in the presence of multiple VISMAs than DE in the presence of single VISMAs and GA in multiple VISMAs. Moreover, the study is compared to integral control methods in which, compared to all controllers, the proposed controller reduces undershoot by 0.0674 Hz more than a single VISMAs, in which it is improved approximately by 97.82%. Similarly, the proposed controller improves the system settling time, rise time, and overshoot by more than 99.5% compared to the classical integral controller. To examine the robust operation of the system under the proposed controller, the system was run under a wide range of disturbances and uncertainties using random load perturbation of ± 20%, in which the proposed controller retains the system frequency by reducing or damping the system oscillation.

Combined depth and heading control and experiment of ROV under the influence of residual buoyancy, current disturbance, and control dead zone

AbstractTo improve the underwater control effect of a Remotely Operated Vehicle (ROV) with residual buoyancy, current disturbance, and control dead zone, the depth and heading combined control of ROV is studied to improve the control accuracy of the control system. First, the heading control with fixed depth is divided into heading control and depth control. The tanh‐sigmoid‐surface control laws for designed degrees of freedom are designed by using tanh function. To suppress the influence of residual buoyancy and control law dead zone in depth control, and to offset the influence of control law dead zone of ROV thruster control, a reserved control quantity is introduced to map the depth deviation and control dead zone with residual buoyancy into a control deviation quantity. An adaptive amplification factor method is proposed for the amplification factors of depth control, speed control, and heading control. The proportional coefficient is adopted to make that the balance among rise time, convergence speed, and overshoot can be achieved by adjusting the proportional coefficient. Then the corresponding tanh‐sigmoid‐surface controller module is designed in MOOS‐IvP environment to track the desired heading and depth. The proposed controller refines fuzzy rules and reduces the complexity of parameter adjustment. Compared with the classical proportional, integral, and derivative control method, the experiment results show that the proposed method can resist the influence of residual buoyancy, current disturbance, and control dead zone and has a better control effect with less control error in depth and heading determination.

A proportional, integral and derivative differential evolution algorithm for global optimization

The proportional, integral, and derivative differential evolution algorithm (PID-DE) is proposed as a new type of interdisciplinary metaheuristic evolutionary algorithm in this paper. The inspiration of PID-DE is derived from the classical proportional, integral, and derivative control method in engineering, and it is used in the framework of the differential evolution (DE) algorithm. To begin, the mathematical models of proportional search, integral search, and derivative search are established as the fundamental search operations. Five different types of optimizers that use a combination of these three basic operations and an additional mutation operation are presented. The selection and crossover methods in DE are then modified to maintain population diversity while also improving global search capacity, and a feedback strategy is established to adaptively adjust the subgroup member of each optimizer. Following that, an integrated high-accuracy, rapid-convergence, and stable metaheuristic is invented using the comprehensive information utilization principle and flexible parameter determination method. Five groups of experiments are studied to assess the overall performance of the proposed algorithm. The first test comprises 12 standard benchmark functions with minimum optima. In Tests 2 and 3, the 52 functions of Congress on Evolutionary Computation (CEC) 2014 and CEC 11 are evaluated using PID-DE under standard test conditions. Besides, three classic real-world engineering design problems and the CEC 2020 test suit are studied for the constrained optimization test. The experimental tests validate PID-DE’s higher accuracy and faster convergence speed in numerical optimization when compared with the representative approaches and top algorithms in the CEC competitions.

Type-2 fuzzy controller’s performance index. Case study: tank level control

This paper deals with the design and implementation of type-2 fuzzy controller, through a tank level control plant as a pilot system to analyze the response using performance indexes. The controller was developed using type-2 fuzzy logic from a mathematical approach and utilizing the identification of the process through a parametric method. Additionally, a classical proportional, integral, and derivative controller was used to generate the bases for the linguistic variables required by the fuzzy controller implementation. Finally, a statistical analysis of the transient and steady-state response margins is performed, which aims to provide a numerical index of the system response performance.

Disturbance-Observer-Based Frequency Regulation Scheme for Low-Inertia Microgrid Systems

This paper presents a disturbance observer approach for frequency regulation for a low-inertia microgrid system consisting of various distributed energy resources (DERs). The mismatch in load and generation is estimated using the disturbance observer and is used as a supplement to the classical integral controller to vary the set points of various controlled DERs. Since the disturbance-observer-based approach is an algorithm based on local frequency measurement, it reduces the capital expenditure in implementing additional sensors. Further, in case of microgrids, the communication infrastructure is mostly built with public networks, which can introduce random delays. Therefore, the performance of the proposed scheme is also tested in the presence of random communication delays. A sensitivity analysis is also presented to show that the performance of the proposed control scheme is much better than the integral controller even when there are variations in the system parameters. Finally, the proposed approach is tested in a laboratory-scale microgrid setup in which the frequency of a synchronous generator is controlled using the disturbance-observer-based approach. The results obtained in the experimental setup show that the proposed approach can be easily implemented in a real system in order to achieve adequate frequency control.

Mixed sensitivity H-infinity control of an adaptive optics system

Design of the controller of an adaptive optical system is very complex because its model is usually with uncertainty. To deal with uncertainty and to improve robust stability, the mixed sensitivity H∞ control has been introduced to design the controller. In order to testify the validity, wavefront aberration correction capability as well as the robust stability has been compared between the mixed sensitivity H∞ controller and the classic integral controller. The computer simulation results demonstrate that the system with the mixed sensitivity H∞ controller, though it cannot guarantee a better correction performance, has greater robust stability than the one with the classic integral controller. That is to say, greater robust stability is achieved at the expense of the correction capability in the system with H∞ controller. Moreover, the greater the uncertainty is, the more proceeds the mixed sensitivity H∞ controller will produce. It proves the efficiency of the mixed sensitivity H∞ controller in dealing with uncertainty in adaptive optics system.

Improvement in the rollover stability of a liquid-carrying articulated vehicle via a new robust controller

In this paper, in order to improve the roll stability of an articulated vehicle carrying a liquid, an active roll control system is utilized by employing two different control methods. First, a 16-degree-of-freedom non-linear dynamic model of an articulated vehicle is developed. Next, the dynamic interaction of the liquid cargo with the vehicle is investigated by integrating a quasi-dynamic liquid sloshing model with a tractor–semitrailer model. Initially, to improve the lateral dynamic stability of the vehicle, an active roll control system is developed using classical integral sliding-mode control. The active anti-roll bar is employed as an actuator to generate the roll moment. Next, in order to verify the classical sliding-mode control performance and to eliminate its chattering, the backstepping method and the sliding-mode control method are combined. Subsequently, backstepping sliding-mode control as a new robust control is implemented. Moreover, in order to prevent both yaw instability and jackknifing, an active steering control system is designed on the basis of a simplified three-degree-of-freedom dynamic model of an articulated vehicle carrying a liquid. In the introduced system, the yaw rate of the tractor, the lateral velocity of the tractor and the articulation angle are considered as the three state variables which are targeted in order to track their desired values. The simulation results show that the combined proposed roll control system is more successful in achieving target control and reducing the lateral load transfer ratio than is classical sliding-mode control. A more detailed investigation confirms that the designed active steering system improves both the lateral stability of the vehicle and its handling, in particular during a severe lane-change manoeuvre in which considerable instability occurs.

Distributed load frequency control in an interconnected power system using ecological technique and coefficient diagram method

This paper presents a load frequency control (LFC) design, using both of coefficient diagram method (CDM) and ecological optimal technique (ECO) in a multi-area power system. The proposed controller has been designed to reduce the effect of uncertainties owing to variations in the parameters of governors and turbines as well as load disturbance. Each local area controller is designed independently, such that, stability of the overall closed-loop system is guaranteed. The CDM structure is built on the frequency response model of multi-area power system, and physical constraints of the governors and turbines are considered. Also, the standard Kalman filter technique has been employed to estimate the full states of the system including the area frequency deviation, these states has been employed by the (ECO) state feedback optimal controller to produce the optimal control signal. Digital simulations for three-area power systems are provided to validate the effectiveness of the proposed scheme. From the simulation results, it is shown that, considering the overall closed-loop system performance with the proposed CDM+ECO technique, robustness is demonstrated in the face of uncertainties due to governors, turbines parameters variation and loads disturbances. A performance comparison between the proposed controller, CDM alone, and a classical integral controller (I) scheme is carried out, confirming the superiority of the proposed CDM+ECO technique.

ROBUST PID CONTROLLER DESIGN FOR BALL AND BEAM SYSTEM USING CLASSICAL LOOP-SHAPING TECHNIQUE

In this paper, classical loop-shaping technique-based robust proportional, integral and derivative (PID) control for ball and beam system, a particular example of double integrator with time delays is investigated.

Modelling and control of actuators with built-in position controller

This paper addresses the set-point control of actuators integrated with built-in controller, which presents steady-state error (SSE) under certain load. To eliminate the SSE, a model of the actuatorplus-controller system is established and identified, a switched adaptive controller is developed to work with the embedded one, considering the physical constraints, a switching control strategy is proposed. Implementation of the proposed controller and control strategy shows the ability of error elimination and the robustness under different operational conditions, with comparison to classic integral controller.

Decentralized load frequency control in an interconnected power system using Coefficient Diagram Method

This paper presents a new load frequency control (LFC) design, using the Coefficient Diagram Method (CDM) in a multi-area power system. The CDM controller has been designed to reduce the effect of uncertainties owing to variations in the parameters of governors and turbines as well as load disturbance. Each local area controller is designed independently, such that, stability of the overall closed-loop system is guaranteed. The CDM structure is built on the frequency response model of multi-area power system, and physical constraints of the governors and turbines are considered. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. From the simulation results it is shown that, considering the overall closed-loop system performance with the proposed CDM technique, robustness is demonstrated in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller, model predictive controllers (MPC), and a classical integral control (I) scheme is carried out, confirming the superiority of the proposed CDM technique.

Model predictive based load frequency control_design concerning wind turbines

This paper presents a load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system in the presence of wind turbines. In the studied system, each local area controller is designed independently such that stability of the overall closed loop system is guaranteed. A frequency response model of multi-area power system including wind turbines is introduced. A physical constraints of the governors and turbines are considered in the model. The model was employed in the MPC structures. Digital simulations for a two area power system are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and load disturbances. Also, it was denoted that wind turbine has a positive effect on the total response of the system. A performance comparison between the proposed controller with and without the participation of the wind turbines and a classical integral control scheme is carried out for confirming the superiority of the proposed MPC technique in the presence of the participation of the wind turbines.

Decentralized model predictive‐based load‐frequency control in an interconnected power system concerning wind turbines

AbstractThis paper presents a load‐frequency control (LFC) design using the model predictive control (MPC) technique in a multi‐area power system in the presence of wind turbines (WTs). In the studied system, the controller of each local area is designed independently such that the stability of the overall closed‐loop system is guaranteed. A frequency response model of the multi‐area power system including WTs is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for a two‐area power system are provided to validate the effectiveness of the proposed scheme. The results show that with the proposed MPC technique the overall closed‐loop system performance shows robustness in the face of uncertainties due to governor and turbine parameter variation and load disturbances. A performance comparison between the proposed controller with WTs and MPC without WTs and a classical integral control scheme is carried out, confirming the superiority of the proposed MPC technique with WTs. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Decentralized model predictive based load frequency control in an interconnected power system

This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.

Integral Controller for the Plants with the Asymmetric Dynamics

The modification of the Integral controller adapted for control of plants with the asymmetric dynamics is presented. A feature of analyzed plants is that the dynamics of the plant output parameter during the rise and decay is different. The algorithm used in the proposed controller switches the value of integral constant of the controller when the sign of the error changes. This feature enables achieving improved transient performance of the analyzed control system as compared to the case when the classical Integral controller is used. The proposed controller is characterized by higher electromagnetic disturbance compatibility as compared to the asymmetric controllers that include Proportional and Derivative terms. The investigation of the control system based on the developed controller was performed using the electronic circuit simulation program Spice. Ill. 5, bibl. 7 (in English; summaries in English, Russian and Lithuanian).

A kriging interpolation strategy for the optimization of Acidithiobacillus ferrooxidans biomass production using fed-batch bioreactors

In this work, a procedure for the optimization of Acidithiobacillus ferrooxidans biomass production in fed-batch reactors using a model based on optimal spatial interpolation of experimental data is proposed. The approach is useful in those cases where specific growth and substrate consumption rates are unknown. Based on interpolation, the optimal values of biomass and substrate concentrations set points are obtained at the minimum of 2-dimensional cost function. In the fed-batch reactor biomass and substrate concentrations are controlled at their set points by changing the input flow and its concentration. We propose a minimum variance control strategy which improves the classical proportional plus integral control. Since the interpolation is optimal, the proposed linear control strategy allows obtaining a tight minimized upper bound of the variance error in the controlled variables.

A modified Taylor rule for dealing with demand shocks and uncertain potential macroeconomic output

A critical issue for central banks in modern economies is the inflation stabilization about a prescribed level. The best-known simple instrumental rule to guide monetary policy to control inflation is the Taylor rule, where the instrument (e.g., a short interest rate) responds to changes in the inflation and the output gaps. The objective of this paper is to introduce some modifications to the Taylor rule in order to improve its robustness with respect to uncertainties about potential output and unanticipated shocks. To this end, departing from feedback control theory, the Taylor rule is equipped with an adaptive control scheme to reject the adverse effects of shocks and to estimate the deviations of the potential output. It is shown that the proposed adaptation procedure is equivalent to a classical integral feedback controller whose characteristics and implementation issues are well understood in practical control engineering. Singular perturbation methods are used to establish the stability properties of the resulting control system.

FUZZY BASED FAULT DETECTION AND CONTROL FOR 6/4 SWITCHED RELUCTANCE MOTOR

Prompt detection and diagnosis of faults in industrial systems are essential to minimize the production losses, increase the safety of the operator and the equipment. Several techniques are available in the literature to achieve these objectives. This paper presents fuzzy based control and fault detection for a 6/4 switched reluctance motor. The fuzzy logic control performs like a classical proportional plus integral control, giving the current reference variation based on speed error and its change. Also, the fuzzy inference system is created and rule base are evaluated relating the parameters to the type of the faults. These rules are fired for specific changes in system parameters and the faults are diagnosed. The feasibility of fuzzy based fault diagnosis and control scheme is demonstrated by applying it to a simulated system.

Contact transition control via joint acceleration feedback

Stable and controllable transition from free motion to constrained motion is of central importance for robots in contact with the environment in many applications. In this paper, a joint acceleration feedback control scheme of high bandwidth is employed to damp oscillations during the contact transition when the approaching speed does not vanish. In this control scheme, a classical integral force controller is refined by means of joint acceleration and velocity feedback. This is intended to achieve a stable contact transition without need of adjusting the controller parameters adaptive to the unknown or changing environments. Extensive experiments are conducted on the third joint of a three-link direct-drive robot to verify the proposed scheme for the environments of various stiffnesses, including elastic (sponge), less-elastic (cardboard), and hard (steel plate) surfaces. Results are also compared with those by the transition control without the acceleration feedback. The proposed scheme is shown to be promising in terms of robustness, stability and adaptability.