Integral Time Absolute Error Research Articles

PID controller for microsatellite yaw-axis attitude control system using ITAE method

The need for effective design of satellite attitude control (SAC) subsystem for a microsatellite is imperative in order to guarantee both the quality and reliability of the data acquisition. A proportional-integral-derivative (PID) controller was proposed in this study because of its numerous advantages. The performance of PID controller can be greatly improved by adopting an integral time absolute error (ITAE) robust controller design approach. Since the system to be controlled is of the 4 th order, it was approximated by its 2 nd order version and then used for the controller design. Both the reduced and higher-order pre-filter transfer functions were designed and tested, in order to improve the system performance. As revealed by the results, three out of the four designed systems satisfy the design specifications; and the PD-controlled system without pre-filter transfer function was recommended out of the three systems due to its structural simplicity, which eventually enhances its digital implementation.

Desain Metode PID-Simulated Annealing Sebagai Kontrol Temperatur Pada Inkubator Bayi

This study compares 2 controllers, the On-Off controller and the PID-Simulated Annealing which is a PID control whose parameters are tuned using the simulated annealing method. Both methods are applied to the incubator accompanied by 3 disturbances in the form of variations in the outside air temperature which affect the temperature inside the incubator. The performance of the two controllers is calculated using the Integral Time Absolute Error (ITAE) criteria. The results showed that the average ITAE between On-Off and PID-Simulated Annealing controls was 534,925 and 1,894. These results it can be concluded that the PID-Simulated Annealing control is the most effective control in regulating the temperature of the air inside the incubator and can maintain the air temperature from interference due to outside air temperatures.

A data-driven approach for trajectory-based aircraft operation with controlled time of arrival and along-track wind effects

Trajectory-based aircraft operation and control is one of the hot issues in air traffic management. However, the accurate mechanism modeling of aircraft is tough work, and the operation data have not been effectively utilized in many studies. So, in this work, we apply the model-free adaptive iterative learning control method to address the time-of-arrival control problem in trajectory-based aircraft operation. This problem is first formulated into a trajectory tracking problem with along-track wind disturbance. Through rigorous analysis, it is shown that this method, combined with point-to-point iterative learning control (ILC) strategy, can effectively deal with the arrival time control problem with multiple time constraints. Then, the terminal ILC strategy is applied, aiming to resolve the same problem with a time constraint at the end point. Compared with the PID (Proportional Integral Derivative) type ILC, the proposed method improves control performance by 11.15% in root mean square of tracking error and 9.32% in integral time absolute error. The sensitivity and flexibility of the data-driven approach is further verified through numerical simulations.

Optimal Fuzzy Logic Control for Temperature Control Based on Social Spider Optimization

Fuzzy Logic Controller (FLC) is useful for many applications like industrial, home, military and medical applications, so one of main application is temperature control of A proposed controller combines the advantages of controller structure and fuzzy inference for air heater temperature control applications. The input variables of the PDFLC-SSO are error and change of error, while its output is the control signal. PDFLC-SSO has seven membership functions. These functions are triangular shaped. Centroid method (CM) is selected for the defuzzification process. The universe of discourse range is used from (-1 to 1) for each input and output. Temperature heater model was utilized to test the controller; the gain factors was tuned using trial and error method and SSO algorithm to reach the optimum response with minimum settling time, minimum peak overshoot and minimum Integral Time Absolute Error (ITAE). Carried out simulations showed an average improvement in measurements using ITAE. ITAE is 7.46% for a constant set-value using PDFLC-SSO, while it is 9.55 for a constant set-value using PDFLC.

Investigation and performance comparison of ride comfort on the created human vehicle road integrated model adopting genetic algorithm optimized proportional integral derivative control technique

This context exhaustively investigates the ride comfort performance index on the proposed active suspension vehicle system. Ride comfort in terms of occupants (includes driver and passenger) head acceleration, sprung mass vertical and pitching accelerations is considered. For this examination, a 14-degree-of-freedom human vehicle road integrated system model was extensively developed. Then, an active suspension system composed of a hydraulic actuator and proportional-integral-derivative controller is incorporated into the developed vehicle model to enhance the ride comfort. Besides, the designed controller needs to satisfy other vehicle performance indices like vehicle stability and ride safety. Accordingly, the controller parameters were optimally tunned with the help of genetic algorithm technique, on the basis of integral time absolute error criterion. The objective function was created on the basis of minimizing the integral time absolute error of sprung mass displacement, suspension working space and tire deflection responses. The entire response of human vehicle road integrated model, with the proposed active suspension system and passive suspension system on various random road surfaces (A, B, C, D and E with respect to ISO 8608) with five constant speeds (20, 40, 60, 80 and 100 kmph), was compared via surficial presentation. Furthermore, the comfort measures such as root mean square and vibration dose value from ISO 2631-1 were adopted to evaluate the severity between the occupants via head acceleration response. The simulation results showed that the suggested active suspension system significantly improved the ride comfort with guaranteed vehicle stability and ride safety.

Compatibility of objective functions with simplex algorithm for controller tuning of HVDC system

This work aims to tune multiple controllers at the same time for a HVDC system by using a self-generated (SG) simulation-based optimization technique. Online optimization is a powerful tool to improve performance of the system. Proportion integral (PI) controllers of Multi-infeed HVDC systems are optimized by the evaluation of objective functions in time simulation design (TSD). Model based simulation setup is applied for rapid selection of optimal PI control parameters, designed in PSCAD software. A multiple objective function (OF), i.e. Integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE), integral time square error (ITSE), and integral square time error (ISTE), is assembled for testing the compatibility of OFs with nonlinear self-generated simplex algorithm (SS-SA). Improved control parameters are achieved after multiple iterations. All OFs generate optimum responses and their results are compared with each other by their minimized numerical values. Disturbance rejection criteria are also proposed to assess the designed controller performance along with robustness of system. Results are displayed in form of graphs and tables in this paper.

다변수 제어성능 최적화를 위한 유전자 알고리즘 기반 발전소 PID 제어 파라미터 튜닝 기법

PID controllers are widely used in the power plant control system. Generally, to calculate PID control parameters, the dynamic characteristics should be identified by investigating the variation of the process value according to the variation of the controller output. Based on this characteristics, several tuning methods can be applied to minimize the cumulative error based performance index. The applicability of ITAE(Integral Time Absolute Error) tuning method which has been studied for decades is determined by the range of time-delay/time-constant ratio. By using this method the fast rising time can be expected, but overshoot and oscillation are inevitable. These effects may lead to shorter life spans of the power plant materials because of excessive movement of the parts. To solve these problems, this paper proposed a PID tuning technique that minimizes cumulative error and overshoot simultaneously by applying genetic algorithm. The performance of the proposed PID tuning technique was verified using power plant simulator, and the performance was excellent compared with ITAE tuning method.

A Gain Scheduling Control of Incompressible Airfoil Flutter Tuned by the Population Decline Swarm Optimizer—$$P_{D}SO$$

The phenomenon of flutter is a self-excited aeroelastic vibration which can occur on flexible aerodynamic structures moving within a fluid domain, whereby the structure absorbs energy from the fluid; this phenomenon is related to variations in configuration with respect to the relative wind that the structure undergoes as a consequence of its oscillations. Based on the aeroelastic model of a three-degree-of-freedom airfoil, an adaptive controller for flutter suppression is designed and investigated in this work. A population decline swarm optimization $$P_{D}SO$$ is used to find the optimal parameters of the controller to set a gain scheduling approach to make the control adaptive in velocity. The integral of time absolute error is minimized to attribute a greater weight to the divergence error that can manifest far after the disturbing instant. Numerical results are reported to show how the gain scheduling control allows to obtain damped oscillation beyond the critical speed without destructive picks.

Error minimization of positive output luo converter using various optimization techniques

DC-DC converters are widely used in many consumer electronic devices such as computers, medical equipment, battery chargers, cellular phones and many Industrial drives. These electronic devices require different voltage levels which is supplied from battery or some external supply. In multiple battery mission voltage decays as its stored energy is drained and requires large saving space. The switched DC-DC converters overcome these drawbacks and also regulate the output voltage for different power levels efficiently. This paper elaborates the structure of Luo converter with optimized PI controller. Positive Output Elementary Luo Converter (POELC) is designed for boost operation by choosing the appropriate duty cycle. The PI controller parameters are optimized using Cuckoo and Crow search algorithms. The proposed control methods are investigated for the transient and steady state region. The sensitivity of these controllers to supply load and line disturbances are also studied along with the servo response are presented. The controller incorporates a Luo converter is evaluated in terms of Integral Time Square Error (ITSE) and Integral Time Absolute Error. Dynamic modelling of the power converter is derived by using state space averaging method. The simulation model of the Luo converter with its control circuit is implemented in MATLAB/SIMULINK. Experimental result shows that Cuckoo PI controller has significantly performance improvement in comparison with both the conventional and Crow PI controller.

SIGNATURE PSO: MODIFIED PARTICLE SWARM OPTIMIZATION DENGAN FUZZY SIGNATURE DAN IMPLEMENTASI PADA OPTIMALISASI KENDALI LQR

Particle Swarm Optimization (PSO) is an optimization that is simple and reliable to complete optimization. In this method, the distribution of particles through global search and local search is the key obtained through searching with PSO through the inertia parameter. This paper describes the method of changing the weights on PSO using fuzzy signatures. In this paper, the method used to solve the problem of optimizing the LQR control parameters on the stabilization of a double inverted pendulum. Performance evaluation is done by another weight change algorithm. Integral Time Absolute Error (ITAE) 7% compared to other algorithms. PSO signatures have resilience and are optimal in fulfilling these interests .

Simulation model of speed control DC motor using fractional order PID controller

DC motor speed can be achieved by changing the armature voltage fed through converter that generally employed with conventional PID. However, conventional PID controller has some disadvantages such as the high starting overshoot and sensitivity to controller gains. On the other hand, fractional order PID has potential to accomplish what conventional PID cannot. In this study, fractional order PID controller was applied to control speed of DC motor. By calculated error that occurred by reference speed and actual speed, fractional order PID brought motor run at desired speed. The parameters of fractional order PID controller (proportional constant, integral constant, derivative constant, derivative order and integral order) are optimally tuned by using Genetic Algorithm, and the optimization performance target is based on Integral Time Absolute Error (ITAE) criterion. Oustaloup’s approximation method is used to approximate the fractional order differentiator and integrator. This controller performances are tested in simulation mode using MATLAB/Simulink. Speed response of motor DC are compared between fractional order PID and conventional PID controller. The result of fractional order PID controller could reduce overshoot, settling time and steady state error. With this result, show that fractional order PID controller perform better than conventional PID controller.

Multi-Verse Optimizer for Model Predictive Load Frequency Control of Hybrid Multi-Interconnected Plants Comprising Renewable Energy

This paper presents a recent metaheuristic optimization approach of multi-verse optimizer (MVO) to design load frequency control (LFC) based model predictive control (MPC) incorporated in large multi-interconnected system. The constructed system comprises six plants with renewable energy sources (RESs). MVO is employed to determine the optimal parameters of MPC-LFC to achieve the desired output of the interconnected system in case of load disturbances. The presented system comprises reheat thermal, hydro, photovoltaic (PV) model with maximum power point tracker (MPPT), wind turbine (WT), diesel generation (DG), and superconducting magnetic energy storage (SMES). The integral time absolute error (ITAE) of the frequencies and tie-line powers deviations is proposed as objective function. The effects of governor dead zone and generation rate constraint (GRC) of thermal plants are considered. The performance of the proposed MPC optimized via MVO is compared with the other designed via intelligent water drops (IWD) and genetic algorithm (GA). Additionally, the robustness of the proposed MPC-LFC based MVO with variation of the system parameters is presented. The obtained results confirmed the superiority and reliability of the proposed controller compared to the others.

A Matignon’s Theorem Based Stability Analysis of Hybrid Power System for Automatic Load Frequency Control Using Atom Search Optimized FOPID Controller

The large-scale penetration of intermittent Renewable Energy (RE) sources such as wind and solar power generation may cause a problem of frequency aberration of interconnected Hybrid Power System (HPS). This occurs when the load frequency control of interconnected system is unable to compensate the power balance between generation and load demand. Also owing to the enhancement of future transport, the Plug-in Electric Vehicle (PEV) plays a significant role to customer at demand side. Thus, the PEV can act as a power control to compensate the power balance in Renewable Energy integrated power system. This paper presents a physics inspired Atom Search Optimization (ASO) algorithm for tuning the parameters of Fractional Order Proportional-Integral-Derivative (FOPID) controller for Automatic Load Frequency control of HPS. In this proposed work, an attempt has been made to analyze the frequency stability of HPS using Matignon's theorem. The interconnected HPS consists of reheat thermal power system, RE sources such as wind and solar thermal power generation associated with energy storage devices namely aqua electrolyzer, fuel cell and electric vehicle. The gain and fractional terms of the controller were obtained by minimizing the Integral Time Absolute Error of interconnected system. The robustness of ASO-tuned FOPID controller is tested on two-area HPS that was modelled using MATLAB/Simulink. The results obtained were then compared with other fractional order and classical integer order controllers. From the simulation results, it is inferred that the proposed ASO-tuned FOPID controller gives superior transient and steady-state response compared with other controllers. Moreover, the self-adaptiveness and robustness of the controller was validated to account for the change in RE power generations and system parameters. Furthermore, the effectiveness of the method is proved by comparing its performance with the recent literature works. The real-time applicability of proffered controller is validated in hardware-in-the-loop simulation using Real Time Digital Simulator.

Fractional Order PID Controller Design for Multivariable Systems using TLBO

Abstract The multivariable systems have to control by using multiloop controllers and each closed loop controller has unique characteristics. The successful model structure for design of control system is extremely subject to the accurate choice of the tuning parameters ( K_p, K_i, K_d, \lambda, \mu ) of the controller. The choice of optimal tuning parameters of Fractional Order PID (FOPID) controller leads to accurate controlling of desired level in multivariable system. Here, for multivariable system, a FOPID controller design based on the advanced optimization technique called Teaching Learning based optimization (TLBO) algorithm is proposed. The goal of paper is (i) The elimination of interaction between the control loops and (ii) Reference tracking along the disturbance in each loop. These objectives are satisfied by using four cost function, namely, integral absolute error (IAE), integral square error (ISE), integral time absolute error (ITAE) and integral time square error (ITSE). Out of these cost functions, ITAE based FOPID controller design using TLBO algorithm provides better performance in terms of fast reference tracking and disturbance elimination in the loop. Moreover, the comparative analysis of convergence characteristics of each objective of the controller by using TLBO is presented. The simulation study confirms that the TLBO algorithm based FOPID controller for multivariable systems (2 × 2) are more robust and exhibits superior response with respect to other algorithm.

Ant colony optimization technique tuned controller for frequency regulation of single area nuclear power generating system

Obtaining energy from the power generating unit is a more critical issue in recent days due to the sudden increasing load demand than that of the past. In this proposed work the Load Frequency Control (LFC) of nuclear power system is studied by implementing the Proportional Integral Derivative (PID) controller as a secondary controller. The controller gain values are optimized by utilizing Ant Colony Optimization Technique (ACOT) by considering three different cost functions (Integral Absolute Error (IAE), Integral Time Absolute Error (ITAE) and Integral Square Error (ISE). Also, the effect of different energy storage units Hydrogen Aqua Electrolyzer (HAE), Superconducting Magnetic Energy Storage (SMES), Redox Flow Battery (RFB) is also verified by considering one percent step load disturbance in the investigated system. Finally, the simulation result obviously shows that ITAE cost function gives better result in terms of minimal domain specification parameters with good stability. Also, SMES improves the performance of system over HAE and RFB energy storage unit.

Microprocessor-based performance indices analysis of individual systems distributed motion control strategies

This paper objective is to analyze individual systems performance indices of a developed synchronization control for bi-axial system speed control/speed synchronization by using two strategies (cross-coupling technique and master–slave technique) with two permanent magnet direct current (PMDC) motors. Two prototypes of the previously developed microprocessor-based PMDC motor are used. The control algorithms are implemented using ARDUINO Mega board after installing MATLAB supporting package for it. First, the system identification procedure is carried out using a pseudo-random binary sequence test and the transfer function is derived. Then, optimal tuning of the Proportional-Integral controller is performed based on the multiple-application Simpson’s 1/3 rule with the performance indices as objective functions of the tuning algorithm. After that, both cross-coupling and master–slave speed synchronization algorithms are implemented. Finally, a comparison is made for their performance indices. The integral absolute error, integral square error, integral time absolute error and integral time square error performance indices are used for the comparison purpose. Introducing the analysis of the performance indices values for individual systems is the main contribution of this paper. Larger values of the performance indices resulted in master–slave strategy on slave PMDC motor due to the time delay needed for this motor to follow the master speed.

Improved stochastic fractal search algorithm and modified cost function for automatic generation control of interconnected electric power systems

An improved stochastic fractal search algorithm (ISFS) and a modified cost function are proposed in this paper to skillfully handle the issue of automatic generation control (AGC) of power systems. Most employed power system models namely two-area non-reheat thermal power system with and without governor dead band nonlinearity, and three-area hydro-thermal power plant with generation rate constraints are considered to be controlled by a PID controller. Then the gains of this controller are optimized with SFS and ISFS individually by minimizing the value of cost function proposed. This function consists in minimizing the integral time absolute error (ITAE) and also the time rates of frequency and tie-line power deviations. After recognizing the supremacy of SFS tuned PID controller over some existing methods in improving settling time and oscillations of frequency and tie-line power deviations, ISFS tuned PID controller is shown to promote the system performance further to compete with some other control schemes of higher degree and complexity available in the literature. This outcome has unveiled the superior tuning ability of ISFS over the original version of SFS. Also, convergence curves of the algorithms are analyzed from which it is observed that the speed of convergence for ISFS is remarkable.

Optimal fractional order PID controller design using Ant Lion Optimizer

Abstract This paper uses a nature inspired metaheuristic algorithm based on the behavior of ant lions named as Ant Lion Optimization (ALO) to design the fractional order PID controller (FOPID) for controlling first order and higher order systems. The ALO is used to optimize the parameters of the FOPID controllers. This algorithm is based upon the hunting behavior of ant lions which is described by five important phases of hunting the ants: random walk, building trap, entrapments of ants in traps, sliding ants towards the antlion, catching the prey and rebuild the trap. ALO algorithm based fractional order PID controller is proposed for delay system and also for higher order system. To obtain the optimal computation, different performance indices such as IAE (Integral Absolute Error), ISE (Integral Squared Error), ITAE (Integral Time Absolute Error), ITSE (Integral Time Squared Error) are considered for the optimization. As the delay system exhibits non-minimum phase characteristic, to improve gain and phase margin, the ALO based fractional order PID is optimally designed by considering different objective functions such as IAE, ISE, ITAE and ITSE. All the simulations are carried out in Simulink/Matlab environment. The proposed method has superiority value in terms of transient and frequency responses as compared with other methods, which has been demonstrated by illustrative examples.

BAT ALGORITHM IMPLEMENTATION TO OPTIMALLY DESIGN THE STABILIZER POWER SYSTEM ON THE SUPPA GENERATOR

One of the control devices that can be used to strengthen the performance of PLTU Suppa is the installation of Power System Stabilizer. The problem of using Power System Stabilizer (PSS) in generator excitation is how to determine the optimal PSS parameter. To overcome these problems, the authors use a method of intelligent bats to design PSS. Bat's algorithm will work based on the specified destination function, which is an Integral Time Absolute Error (ITAE). In this research, we will see the deviation response of velocity and the rotor angle of the suppa generator in case of interference. The results of the analysis show that the uncontrolled system produces oscillation overshoot speed of -0.02437 pu to 0.006517 pu, conventional PSS about -0.02186 pu to 0.004623 pu and with PSS Bat overshoot of -0.01507 pu up to 0.0006223 pu. A loop for rotor angle response shows good results with reduced oscillation and rapidly leading to steady-state conditions. From the analysis results can be concluded, the performance of suppa generator is increased with the installation of Power System Stabilizer with optimal PSS parameters, with parameters respectively Kpss = 32.2077, T1 = 0.0173, T2 = 0.0401, T3 = 0.9174, T4 = 1.2575.

Comparative Performance Evaluation of Fractional Order PID Controller for Heat Flow System Using Evolutionary Algorithms

The main objective of the paper is to design of Fractional order PID (FOPID) controller for heat flow system using evolutionary algorithms. The recent developed metaheuristic algorithms such as Ant Lion Optimizer (ALO), Grey Wolf Optimizer (GWO) and Moth Flame Optimizer (MFO) are used in the FOPID design. The FOPID design for heat flow system is formulated as an optimization problem to minimize different indices error such as Integral Absolute Error (IAE), Integral Squared Error (ISE), Integral Time Absolute Error (ITAE), Integral Time Squared Error (ITSE). The evolutionary algorithm based FOPID control performances are compared with PID control performance for the heat flow system. In addition, the proposed methods have superiority value in terms of transient and frequency domain analysis than the traditional and PID methods. Comparative performance evaluation of meta-heuristic based FOPID design for heat flow system has not carried out before.