Proportional Integral Derivative With Filter Research Articles

Angle stability improvement using optimised proportional integral derivative with filter controller

Load inconsistency has disrupted the power system, causing rotor angle fluctuation that leads to angle instability in the system. This research suggests an innovative proportional integral derivative with filter (PIDF)-based thyristor-controlled series compensator (TCSC) controller that utilise an evolutionary programming sine cosine algorithm (EPSCA) for hybrid optimisation to increase the angle stability of the power system. The challenge of the PIDF-TCSC design is transformed into an optimal control problem with respect to performance indices, such as the maximum imaginary part of system eigenvalues, damping ratio and damping factor, where another multi-objective function is utilised to determine the best stabiliser settings. Eigenvalue analysis is used to conduct the stability study in a linearised paradigm of the single-machine infinite-bus (SMIB) network. The resilience of the PIDF controller was tested using a SMIB power network under various operating circumstances. Simulation results are used to evaluate the system's effectiveness with the proposed optimised PIDF-TCSC controller to that of the system using the proportional integral derivative, proportional integral, and base case PIDF-TCSC approaches. The research findings demonstrate the efficacy of EPSCA in implementing PIDF-TCSC motif and its excellent resilient performance for improving power system stability as related to other strategies in various situations.

Optimization of the different controller parameters via OBL approaches based artificial ecosystem optimization involving fitness distance balance guiding mechanism for efficient motor speed regulation of DC motor

This study proposes a new optimization approach, which is called as artificial ecosystem optimization algorithm with fitness-distance balance guiding mechanism by using opposite based learning methods (FDBAEO_OBLs) for the speed regulation of direct current (DC) motor. The performance of the proposed FDBAEO_OBL algorithm is tested in two different experimental studies. In the first experimental study, the proposed approach is tested in the CEC2020 benchmark test functions and the FDBAEO algorithm, which included the best OBL approach, is determined using non-parametric Wilcoxon and Friedman statistical analysis methods. Second, the parameters of proportional integral derivative (PID), tilt integral derivative (TID), proportional integral derivative with filter (PIDF), tilt integral derivative with filter (TIDF), fractional-order proportional integral derivative (FOPID), fractional-order proportional integral derivative with filter (FOPIDF), proportional integral derivative with fractional-order filter (PIDFF) and fractional-order proportional integral derivative with fractional-order filter (FOPIDFF) controller structures to be used in DC motor closed loop speed control are determined with FDBAEO_OBL, and the performances of the controllers are investigated. Integral absolute error (IAE), integral time absolute error (ITAE), integral time squared error (ITSE) and integral squared error (ISE) performance indices are used as the objective function of the operation process in which the control parameters are determined. According to the comparative step response results of the controller structures, the four best controller structures for DC motor speed regulation are determined. The performances of these controllers are examined under different simulation conditions and according to the results obtained, it is seen that the best controller structure is FOPIDFF. The FDBAEO_OBL algorithm, which is used in both benchmark test functions and DC motor speed regulation, shows an effective, durable and superior performance in finding the optimal solution values during the optimization.

Modeling and virtual simulation of the boost chopper by DCM using the optimal PIDF control

This work introduces an improved method for modeling and simulating the Boost Converter utilizing Duty Cycle Modulation (DCM) regulated by an optimum PIDF (Proportional-Integral-Derivative with Filter) regulator. We optimized the characteristic parameters of the PIDF regulator for a second-order system generated from its transfer function by using a mix of theoretical study and simulation using the Matlab/LQR tool. The conventional PID parameters in the time domain were converted into their corresponding LQR (Linear Quadratic Regulator) counterparts, allowing for the solution of the Riccati problem and the creation of an optimum state trajectory model. The results of analog virtual simulations done in a Multisim environment indicate that the system has improved dependability. It maintains a high level of accuracy in a stable condition, with no static error and a reaction time of 1.5 ms, without any overshooting. The effectiveness of the optimum PIDF control in regulating the DCM Boost Converter is highlighted by the system's strong ability to handle changes in load during transient states within a time frame of 300 ms. This study represents a substantial enhancement compared to conventional PID-based approaches, providing valuable knowledge about the possible uses in power electronics and control systems.

Aircraft Pitch Control via Filtered Proportional-Integral-Derivative Controller Design Using Sinh Cosh Optimizer

An innovative approach to controlling aircraft pitch is shown in this research. This approach is accomplished by adopting a proportional-integral-derivative with filter (PID-F) mechanism. A novel metaheuristic approach that we propose is called the sinh cosh optimizer (SCHO), and it is intended to further optimize the settings of the PID-F controller that is used in the aircraft pitch control (APC) configuration. An in-depth comparison and contrast of the recommended method is carried out, and statistical and time domain assessments are utilized in order to ascertain the success of the method. When it comes to managing the APC system, the SCHO-based PID-F controller delivers superior performance compared to other modern and efficient PID controllers (salp swarm based PID, Harris hawks optimization based PID, grasshopper algorithm based PID, atom search optimization based PID, sine cosine algorithm based PID, and Henry gas solubility optimization based PID) that have been published in the literature. When compared to alternative approaches of regulating the APC system, the findings demonstrate that the way that was presented is among the most successful as better statistical (minimum of 0.0033, maximum of 0.0034, average of 0.0034 and standard deviation of 5.1151E−05) and transient response (overshoot of 0%, rise time of 0.0141 s, settling time of 0.0230 s, peak time of 0.0333 s and steady-state error of 0 %) values have been achieved.

Stabilization of isolated hybrid microgrids with electric vehicle-based energy storage systems using a fractional order proportional-integral-derivative control

ABSTRACT Electric vehicles (EVs) are considered to be the most promising technology upgrades in the coming years to reduce the carbon emission, since the EVs could replace the conventional combustion vehicles as well as mitigate power fluctuations in power grids. This paper focuses on addressing the frequency stability issues in isolated hybrid grids (IHGs) by introducing a fractional order proportional-integral-derivative (FOPID) control for grid-connected power converters. A particle swarm optimization (PSO) technique is adopted to optimize the parameters of the controllers. The advantages of the proposed control method over the conventional proportional-integral-derivative (PID) control, proportional-integral with proportional-derivative (PI-PD) control, and proportional-integral-derivative with filter (PIDF) control schemes are verified by simulation case studies. Besides, a modified virtual rotor concept (MVRC) is proposed in this paper to enhance the inertia of the system. Furthermore, the performance of using EVs to regulate the frequency of IHGs is compared to the superconducting magnetic energy storage (SMES) units, capacitive energy storage (CES) units, and redox flow batteries (RFB) under fixed and variable load conditions.

A Novel Ultra Local Based-Fuzzy PIDF Controller for Frequency Regulation of a Hybrid Microgrid System with High Renewable Energy Penetration and Storage Devices

A new ultra-local control (ULC) model and two marine predator algorithm (MPA)-based controllers; MPA-based proportional-integral-derivative with filter (PIDF) and MPA-based Fuzzy PIDF (FPIDF) controllers; are combined to enhance the frequency response of a hybrid microgrid system. The input scaling factors, boundaries of membership functions, and gains of the FPIDF con-troller are all optimized using the MPA. In order to further enhance the frequency response, the alpha parameter of the proposed ULC model is optimized using MPA. The performance of the pro-posed controller is evaluated in the microgrid system with different renewable energy sources and energy storage devices. Furthermore, a comparison of the proposed MPA-based ULC-PIDF and ULC-FPIDF controllers against the previously designed controllers is presented. Moreover, a vari-ety of scenarios are studied to determine the proposed controller’s sensitivity and robustness to changes in wind speed, step loads, solar irradiance, and system parameter changes. The results of time-domain simulations performed in MATLAB/SIMULINK are shown. Finally, the results demonstrate that under all examined conditions, the new ULC-based controllers tend to further enhance the hybrid microgrid system’s frequency time response.

Optimal Design and Tuning of Novel Proportional Integral Derivative with Filter Thyristor-Controlled Series Compensator Stabiliser Using a New Hybrid Technique

This paper proposes a novel robust thyristor-controlled series compensator (TCSC) controller based on proportional integral derivative with filter (PIDF) and uses a new hybrid optimisation evolutionary programming sine cosine algorithm (EPSCA) to improve the power system’s angle stability. The problem of the PIDF-TCSC design is transformed into an optimisation problem based on performance indices, such as damping factor, damping ratio, and eigenvalues, where the multi-objective function is employed to obtain the optimal stabiliser parameters. To examine the robustness of PIDF-TCSC, it was tested on a single-machine infinite-bus power system under different operating conditions. The performance of the system with the PIDF-TCSC controller was compared with the simulation results, and the results obtained with the proposed EPSCA were compared with those obtained with SCA, moth flame optimisation, and EP-based PIDF-TCSC methods. Simulation results showed the effectiveness of EPSCA for the PIDF-TCSC design and the superior robust performance for the enhancement of power system stability compared with other techniques in different cases.

Impact of Spotted Hyena Optimized Cascade Controller in Load Frequency Control of Wave-Solar-Double Compensated Capacitive Energy Storage Based Interconnected Power System

The concept of automatic generation control has an immense role in providing quality power in an interconnected system. To obtain quality power by controlling the oscillations of frequency and tie-line power, a proper controller design is necessary. So, an innovative endeavor has been undertaken to enforce a two-stage controller with the amalgamation of a proportional-derivative with filter (PDN) (integer-order) and a fractional order integral-derivative (FOID), i.e., PDN(FOID). In an effort to acquire the controller’s gains and parameters, a bio-inspired meta-heuristic spotted hyena optimizer is applied. Various examinations manifest the excellence of PDN(FOID) over other controllers such as integral, proportional–integral, proportional–integral-derivative filter, and fractional order PID from perspectives concerning the diminished amount of peak anomaly oscillations, and the instant of settling for a three-area system. The system includes thermal–bio-diesel in area-1; a thermal–geothermal power plant in area-2; and a thermal–split-shaft gas turbine in area-3. It is also observed that the presence of renewable sources such as wave power plants and photovoltaics makes the system significantly better compared to the base system, when assessed individually or both together. Action in a combination of capacitive energy storage with duple compensation is also examined using the PDN(FOID) controller, which provides a noteworthy outcome in dynamic performance. Moreover, PDN(FOID) parameter values at a nominal condition are appropriate for the random patterns of disturbance needed for optimization.

Optimizing the PID Controller by Using the Genetic Algorithm

This paper aims to develop a Proportional Integral Derivative (PID) controller for the Automatic Voltage Regulator (AVR) of the Synchronous Generator, Automatic Voltage Regulator is responsible for keeping the output voltage of the Generator constant and stable. The Automatic Voltage Regulator system can be represented by a fourth order Transfer Function. The parameters of the controller are evaluated by using the Genetic Algorithm tuning method, for this method the Genetic Algorithm Optimization toolbox in MATLAB is used. A PID controller and a PID Filter controller are developed in order to come up with the optimum controller design for the system. The performance of the Genetic Algorithm based controller has been compared with the classical Ziegler-Nichols based controller. The results show that the Genetic Algorithm based controller outperforms the Ziegler-Nichols based controller, the optimum controller design is achieved by the GA based PID filter controller.

An improved RUN optimizer based real PID plus second-order derivative controller design as a novel method to enhance transient response and robustness of an automatic voltage regulator

It is crucial to maintain the terminal voltage of a power network in order to reach a desired power quality. In this regard, a system called automatic voltage regulator (AVR) holds a significant role as it allows the adjustment of the terminal voltage. However, an AVR system requires an efficient control technique in order to provide stability. Considering this requirement, a new method is presented in this paper for transient response enhancement and robustness of the automatic voltage regulator (AVR) system. In that sense, the structure of a recently developed metaheuristic algorithm named Runge Kutta optimizer (RUN) is improved. The improved RUN (iRUN) optimizer is obtained by integrating the pattern search (PS) method into the original form of the RUN optimizer. The constructed iRUN optimizer is proposed as an efficient tool to tune a real proportional-integral-derivative (PID) plus second-order derivative (PIDD2) controller employed in an AVR system. In the proposed control mechanism, a performance index known as ZLG is used as an objective function. The proposed iRUN optimizer based real PIDD2 controller is comparatively demonstrated to be superior in terms of transient response and robustness against other available and recently reported methods based on PID, PID with filter (PID-F), PID acceleration (PIDA), fractional order PID (FOPID) and PID plus second-order derivative (PIDD2) controllers that are respectively tuned with metaheuristic optimizers of stochastic fractal search algorithm, Archimedes optimization algorithm, whale optimization algorithm, Henry gas solubility optimization and particle swarm optimization. The proposed method is shown to achieve no overshot and less rise and settling times compared to listed methods. It is also shown to be sufficiently robust in case of potential variations that may occur in the parameters of the system. The superiority is further demonstrated using thirty good performing and recently reported different methods that adopt different controllers and metaheuristic optimizers, as well. All comparative analyses confirm the excellent capability of the proposed iRUN optimizer based real PIDD2 controller for the AVR system control.

CBO-based PID-F controller for Load frequency control of SPV integrated thermal power system

In this article, a maiden attempt is made to design a colliding bodies optimization (CBO) algorithm based proportional-integral-derivative-filter (PID-F) controller for load frequency control (LFC) of hybrid power systems. The CBO is based on collision between objects and the laws of energy and momentum, which simplifies its application compared to the several complex optimization algorithms. In addition to this, it does not depend on any internal parameter and provides a more straightforward formulation for minimum and maximum functions. A two-area interlinked solar photovoltaic system-reheated thermal power system is considered to establish the efficacy of the proposed approach. The controller gains are computed using CBO with the integral of time multiplied absolute error performance criteria. It is observed from the results that the proposed method significantly improves the system response and provides a better solution for the LFC problem. Finally, the optimized controller's robustness is tested by including load perturbations and parametric variations.

Stability of microgrid cluster with Diverse Energy Sources: A multi-objective solution using NSGA-II based controller

The stability of microgrids with increased penetration of renewables is a major concern. This is mainly due to their intermittent nature varying from time to time. While designing the stabilisers, the amplitude of the control signals is not given due consideration. This work develops frequency controller systems for a microgrid cluster composed of several energy sources. In addition to the frequency deviation in microgrids, the aspect of controller output signals has also been considered. A dynamic model of four microgrids linked with tie-lines is developed. The frequency stability is ensured utilising a fractional order controller using the Non-dominated Sorting Genetic Algorithm - II (NSGA-II). The multi-objective problem is formulated with opposing objectives as frequency deviation and the controller output signal for determining the controller. The performance is compared with Tilt Integral Derivative (TID), TID with filter (TIDF), Proportional Integral Derivative (PID) and PID with filter (PIDF) controllers. Besides, the superiority of the algorithm is analysed by comparing the results with those from other algorithms in the literature. The effectiveness is analysed under numerous scenarios of load and renewable uncertainties. Further, the sensitivity investigation has also been performed by varying the internal parameters within the range of ±40%.

Implementation of a Decoupled Digital Feedback Control Architecture on an Arduino - Free RTOS Real-Time Embedded System for Input Delay Robotic Servomechanisms

This paper presents an experimental study on a real-time embedded system of a decoupled PIDF (Proportional Integral, Derivative with Filter) digital control architecture for robotic input delay servomechanisms. The test bench includes an Arduino Uno board integrating a specific microcontroller, a robot arm with four degrees of freedom and DC servo motor seals, a Free RTOS preemptive scheduler for pseudo parallelism of tasks and a console ensuring interactivity with the user. The choice of decoupled digital control parameters in terms of proportional, integral, derivative with filter and sampling time gains has been based on the controller tuning techniques available in the literature for SISO (Single-Input Single-Output) input delay servomechanisms. The prototype implanted in the card occupies 26% of the storage space and 18.80% of the dynamic memory. The results show the attached robotic servomechanisms that converge quickly and as precisely as possible to the desired values of joint variables. Regardless of the non-linear effects on the robot arm, especially the input delay, strict tracking of the trajectory is observed. This demonstrates the high precision of the proposed decoupled control architecture. The different positions of the robotic servo system have been represented in Cartesian space using MATLAB 2019-Ra software. They have been listed using the geometric model of the robot arm.

Utilization of electric vehicles in combined voltage‐frequency control of multi‐area thermal‐combined cycle gas turbine system using two degree of freedom tilt‐integral‐derivative controller

AbstractThis paper conveys the unified control pattern of frequency and voltage of interconnected multi‐area power system through the automatic load frequency control (ALFC) loop and automatic voltage regulator (AVR) loop. Each area includes a single‐stage reheat thermal plant, combined cycle gas turbine (CCGT) plant, and electric vehicles (EVs). Pertinent generation rate constraint for thermal and CCGT plant and governor dead band for the thermal plant is considered. A maiden attempt has been made to introduce the two degree of freedom tilt‐integral‐derivative (2DOFTID) controller for both the ALFC and AVR loops. In this study, a meta‐heuristic algorithm called Harris Hawks optimization (HHO) is implemented to optimize the controller parameters. Study divulges that performance of the 2DOFTID controller predominates when compared with TID and proportional‐integral‐derivative with filter (PIDF) controller apropos time‐domain indices. By juxtaposition, the superiority of the proposed algorithm and performance index is observed. Also, improved system dynamics were independently exhibited by the influence of the lumped EV model and AVR. For the predominance of the 2DOFTID controller, different patterns of disturbances such as random and sinusoidal varying load perturbation have been investigated. Eventually, the sensitivity studies were accomplished to determine the sturdiness of the proposed controller for substantial variations in the system parameters.

An Integral Tilt Derivative Control Strategy for Frequency Control in Multimicrogrid System

The multimicrogrid system is a complicated nonlinear system, which brings performance degradation due to deficient damping under the unexpected fluctuation in power generation due to the presence of renewable sources, dynamically changing loading conditions, and parameter variations. Owing to this, to provide consistent electric power with superlative attribute, sturdy and intelligent control techniques are amazingly imperative in the automatic generation control of microgrid (MG). The application of imperialist competitive algorithm (ICA)-based fractional-order integral proportional derivative with filter (IPDF), i.e., integral tilt derivative with filter controller (ITDF) controller in frequency control in two areas interconnected MG (isolation mode) with renewable penetration, is a novel work. A maiden attempt of the ICA is proposed to optimize the gains of the ITDF controller utilizing the integral time absolute error criterion. To demonstrate the supremacy of ICA, its outcomes are contrasted with two existing optimization strategies, namely the genetic algorithm and the particle swarm optimization. The effectiveness of the proposed controller is revealed by contrasting the dynamic responses of multi microgrid (MMG) with proportional integral derivative with filter (PIDF) and tilt integral derivative with filter (TIDF) controllers. At last, a sensitivity investigation is performed to exhibit the power of the studied strategy to wide variations in the MG parameters, magnitude as well as the location of step/random load disturbance. The proposed MMG is simulated in MATLAB/Simulink environment.

PIDF(1+FOD) controller for load frequency control with SSSC and AC–DC tie‐line in deregulated environment

In this study, a maiden application of cascade proportional–integral–derivative with filter (PIDF) and one plus fractional-order derivative (1+FOD), i.e. PIDF(1+FOD) controller is proposed for the load frequency control mechanism. The main purpose of the cascade and fractional order controller is to increase the degree of freedom and reject the disturbances faster. A novel attempt has also been made to model a static synchronous series compensator (SSSC) with AC tie-line and HVDC tie-line. Here SSSC and HVDC tie-line are used to regulate and increase the power transfer capabilities between interconnected areas. Furthermore stored energy in the HVDC tie-line is utilised to improve the system dynamics by inertia emulation control strategy. An evolutionary salp swarm algorithm-based optimisation technique is adopted to optimise control parameters. The performance of the proposed controller is tested on a two-area hydro-thermal interconnected power system in deregulated environment. First, the effectiveness AC–DC-SSSC tie line is shown over AC-SSSC and alone AC tie-line with proposed PIDF(1+FOD) controller followed by the supremacy of proposed PIDF(1+FOD) over classical controllers. Finally, sensitivity is analysed by variation in system parameters, which shows the robustness of the proposed controller.

AGC of multi area power system based PSO under deregulated conditions

In This research PIDF (Proportional Integral Derivative with Filter) is suggested to control the ACE (area control error) signal of automatic generation control circuit (AGC) for two-area multi units system under deregulated conditions, each area consist of two thermal reheat units with physical GRC (generating rate constrain). The parameters of the PIDF controller are tuned using PSO (particle swarm optimization) technique. To improve the system performance, Redox Flow Batteries (RFB) is presented in one area and one of FACTS components IPFC (Inter Line Power Flow Controller) is installed in tie line. The performance of the proposed controller is assessed under different working conditions of deregulated power market. Finally, a comparison will be made on the system response when testing with varying the load conditions and system parameter through MATLAB environment 2015Rb.

Generalised proportional–integral–derivative filter

In this study, the filtering problem is investigated for both linear and non-linear systems. A new generalised proportional–integral–derivative filter (GPIDF) is proposed by introducing the idea of proportional–integral–derivative (PID) control. It utilises the past, current and future information to estimate the current state in order to achieve a better filtering performance. Besides, the GPIDF provides a unified structure to accommodate a variety of filtering scenarios as its special cases, including the popular generalised Kalman filter. Based on the new proposed GPIDF structure, the optimal PID filter and extended optimal PID filter are designed using the minimum mean square error criterion at each time step. In addition, the practical strong robust proportional–integral filter and extended strong robust proportional–integral filter are developed without requirements of knowledge about model uncertainty. The developed filters are recursive and suitable for real-time online applications. Finally, two simulation studies are carried out to demonstrate the effectiveness and applicability of the authors' proposed methods.

Design Sensor-less PID Filter Controller for First Order Delays System

The dynamics of a first order delay system is highly nonlinear, time variant, uncertain and coupling effects. The main objectives to control of first order delay system are time response and acceleration measurements. The problem of acceleration measurements can be reduced, based on design sensor-less Proportional-Integral-Derivative (PID) filter controller in this research. Assuming unstructured uncertainties and structure uncertainties can be defined into one term and considered as an uncertainty and external disturbance, the problem of computation burden and large number of parameters can be solved to some extent. To solve the uncertainties acceleration measurements play an important role. In order to design sensor-less PID filter controller, an accurate PD surface and the derivative of PD surface plays important role. To design an accurate PD surface, stable and tuning surface slope is needed to form the structure of main PID controller. In this algorithm, the derivative of PD surface computes the second derivation of error. Regarding to this method, the challenge of system uncertainties and time response have been solved based on sensor-less acceleration linear filter controller. As this point if s = K1e + e + K2Σe is chosen as desired surface, if the dynamic of first order delay is derived to surface then the linearization can be realized. Because, when the system dynamic is on the surface is used the derivative of surface S = K1e + e + K2e is equal to the zero that is a decoupled and linearized closed-loop systems dynamics. Linearization and decoupling by the above method can be obtained in spite of the quality of the first order delay dynamic model.

Location Optimization of IPFC for Congestion Management using Cuckoo Search Algorithm

This paper presents a new methodology based on cuckoo search algorithm (CSA) for enhancing the performance of interline power flow controller (IPFC) under multiline transmission. In this approach we perform priority process through the contingency analysis for finding the severity of the line outage. For determining the severity, bus voltage limit violation, overloading of lines and power loss are taken into account. We are applying CSA to determine the optimal location and transmission congestion management of IPFC. An adaptive proportional integral derivative with filter (PIDF) controller is developed to control the deviation and power flow. The simulation is performed using MATLAB for two case studies using an IEEE 118-bus and IEEE 300-bus test system. Simulation results indicate that the location and parameters optimized by using CSA, minimizing the bus voltage abuse, congestion management, and overloaded lines. This method is designed in such a way that it improves the security of the power system. For further improvement of the system, the IPFC is placed in tie-line. The performance of PIDF controller has been studied under different conditions and the simulation result shows that PIDF performs better than PID controller. The performance of CSA is compared with other two optimization techniques such as particle swarm optimization (PSO) and genetic algorithm (GA) under both the IEEE 118-bus and IEEE 300-bus test systems. The result shows that the proposed CSA outperforms the other two models and it best suits the power system security.