PI Parameter Tuning Research Articles

Research on dynamic PI parameter tuning of double-fed wind turbine based on ant colony algorithm

Considering the drawbacks of flexible adjustment of PI controller control parameters in the constant pressure control system of doubly fed fans, a PI controller control parameter flexible adjustment method considering ant colony optimization algorithm (ACO) is proposed. This method uses the proportional coefficient and integration time parameters in the PI controller as the ants in the ant colony optimization algorithm, and the ultimate optimization goal is to control the absolute error integration function. During the control process, the parameters of the PI controller are dynamically adjusted. When the electrified wire netting IR-drop and wind velocity changes, a comparative analysis of the dynamic tuning PI controller parameters and the non-dynamic tuning method was conducted. At last, the simulation studies have shown that the constant voltage control system using the PI parameter Flexible adjustment control method found on ACO can rapidly improve the grid voltage stability of double-fed wind turbines and reduce response time.

MTPA Control for PMSM Velocity-specified Position Tracking Based on the Principle of Backstepping Control

In this paper, a control method based on the backstepping control is proposed to address the issues of uncontrollable speed and complex PI parameter tuning in the traditional PID position control of PMSM. By comparing with id=0 control, MTPA control enables the IPMSM to maximize the utilization of reluctance torque. The dq current relationship under MTPA control is established using a formulaic method. Based on this, a position, speed, and current backstepping controller is designed, which adds a degree of freedom to the speed control during the position control process while ensuring the stability of the control system. Simulation results demonstrate fast dynamic response, small steady-state error, and minimal parameter adjustments, thus verifying the correctness and effectiveness of this method.

Parameter adaptive model predictive control strategy of NPC three-level virtual synchronous generator

The Virtual Synchronous Generator (VSG) emulates the characteristics of a synchronous generator to provide inertia and damping for renewable energy systems. In the case of using the NPC three-level converter structure, traditional control methods require complex dual-loop control and internal PI parameter tuning. Furthermore, although fixed-parameter VSG control can provide inertia and damping when a significant power load is switched in an islanded microgrid, it cannot guarantee frequency regulation performance. To address these issues, this paper proposes an NPC three-level VSG parameter adaptive finite control set model predictive control strategy. This method eliminates the need for dual-loop control and PI parameter tuning. By incorporating angular velocity deviation and its rate of change into adaptive adjustment, a Tracking-Differentiator (TD) is designed to calculate the rate of change of angular velocity. This approach avoids frequent fluctuation of adaptive parameters during load power switching and improves the frequency stability of the microgrid. The effectiveness of the proposed strategy is validated through simulation and experimental verification.

A methodology to implement a closed-loop feedback-feedforward level control in a laboratory-scale flotation bank using peristaltic pumps

This paper describes the implementation of a level control strategy in a laboratory-scale flotation system. The laboratory-scale system consists of a bank of three flotation tanks connected in series, which mimics a flotation system found in mineral processing plants. Besides the classical feedback control strategy, we have also included a feedforward strategy to better account for process disturbances. Results revealed that the level control performance significantly improves when a feedforward strategy is considered.This methodology uses peristaltic pumps for level control, which has not been extensively documented even though: (1) peristaltic pumps are commonly used in laboratory-scale systems, and (2) the control implementation is not as straightforward as those control strategies that use valves. Therefore, we believe that this paper, which describes a proven methodology that has been validated in an experimental system, can be a useful reference for many researchers in the field.•Preparation of reagents to ensure that the froth stability of the froth layer is representative of an industrial flotation froth.•Calibration of instruments – convert the electrical signal from PLCs to engineering units.•Tuning PI parameters using SIMC rules by performing step-changes in each flotation cell.

Direct Torque Control of Induction Motor by Using Particle Swarm Optimization Technique

This paper is based on an efficient and reliable evolutionary approach of particle swarm optimization (PSO) using direct torque control (DTC) of induction motor. In order to resolve the problem of parameter variation the PI controllers are generally used in industrial plants because it is uncomplicated and robust. However, there is a problem in changing PI parameters. So, the engineers are looking for automatic tuning procedures. In traditional direct torque-controlled induction motor drive, there is generally undesired torque and ripple in form of flux. So Tuning PI parameters (Kp, Ki) are critical to DTC system to improve the performance of the system. In this paper, particle swarm optimization (PSO) is planned to correct the parameters (Kp, Ki) of the speed controller in order to get improved performance of the system and also responsible to run the machine at base speed.

Design of Rated Power Control Strategy of Wind Turbine Based on Particle Swarm Optimization

In view of the reduction of wind turbine operating efficiency caused by wind speed measurement errors, this paper proposes a rated power control strategy for wind turbines for practical applications; in order to solve the problem that the pitch PI controller parameters of wind turbines are not easy to calculate and tune in the process of design and optimization, this paper proposes a complete set of methods for parameter tuning of pitch control PI controllers for wind turbines. This paper establishes a Bladed-Matlab co-simulation platform, uses Bladed software to build a complete model of a 2MW wind turbine, and designs a rated power control strategy for wind turbines. After the wind turbine model is linearized at different wind speed points by applying Bladed software, the linearized model for PI parameter tuning is obtained, and then the optimal PI parameters for each wind speed point are set by using particle swarm algorithm. According to the variation law between the PI parameters and the pitch angle obtained before, the PI parameters are adjusted adaptively by variable gain PI control. The simulation results show the superiority of the control strategy and parameter tuning method used in this paper.

Dynamic performance improvement of single‐phase PWM converters with power hysteresis control scheme

This study presents a direct power control (DPC) scheme with pulse width modulation module and two hysteresis comparators, for the application in single-phase PWM converters to overcome the drawbacks of conventional proportion-integration-based DPC (PI-based DPC), including poor dynamic performance and complexity of tuning PI parameters. According to the outputs of inner-loop power hysteresis controllers, the proposed DPC scheme divides d-q reference frame into four sectors. In each sector, the dynamic power components are estimated to be equivalent as the outputs of PI controllers in PI-based DPC. The proposed DPC scheme provides a new solution of non-linear hysteresis control to achieve fast dynamic performance with constant switching frequency. Additionally, due to inductance parameter mismatch, the effect on powers is analysed in detail, and an inductance parameter on-line estimation method is present and discussed. A comprehensive comparison of conventional table-based DPC, PI-based DPC and the proposed DPC methods has been conducted in this study, including steady-state performance with respect to different factors, and dynamic response under different extreme conditions. The experimental results have verified the effectiveness of the proposed DPC scheme.

Inertia Identification and PI Parameter Tuning of PMSM Servo Drives

The goal of this paper is to improve the performance of permanent magnet synchronous motor(PMSM) servo system by identification of the inertia parameter and auto-tuning of PI parameters. The method relies on the speed acceleration and deceleration response produced by speed ramp signals applied to a speed-controlled servo. The proposed method relies on simple numerical calculations, thus make the proposed scheme more practical. After the knowledge of the inertia parameter, the tuning of the speed control loop can be performed. The experimental results verified that the proposed identification scheme can estimate inertia parameters accurately and effectively and the control system tuned can achieve good dynamic performance.

Improvise 3-Level DTC of Induction Machine using Constant Switching Frequency Method by Utilizing Multiband Carrier

This paper presents the advantage of using optimal PI parameter tuning strategy of constant switching method in the three phase Direct torque control (DTC) scheme. The DTC system is known to offer fast decoupled control of torque and flux via a simple control structure. Nevertheless, DTC system has two major drawbacks, which are the variable inverter switching frequency and high torque output ripple. The major factorthat contributes to these problems the usage of hysteresis based comparators to control the output torque. The implementation of PI based constant switching method in DTC able to solve these problems while retaining the simple control structure of conventional DTC. The combination usage of 3-level CHMI in this system can further minimize the output torque ripple by providing greater number of vectors. This paper presents detail explanation and calculationof optimal PI parameter tuning strategyconsecutively to enhance the performance of 3-level DTC system. In order to validate the feasibility, the proposed method compared with convention DTC system via simulation and experiment results.

Distributed generation system control strategies with PV and fuel cell in microgrid operation

Control strategies of distributed generation (DG) are investigated for different combination of DG and storage units in a microgrid. In this paper the authors proposed a microgrid structure which consists of a detailed photovoltaic (PV) array model, a solid oxide fuel cell (SOFC) and various loads. Real and reactive power (PQ) control and droop control are developed for microgrid operation. In grid-connected mode, PQ control is developed by controlling the active and reactive power output of DGs in accordance with assigned references. Two PI controllers were used in the PQ controller, and a novel heuristic method, artificial bee colony (ABC), was adopted to tune the PI parameters. DGs can be controlled by droop control both under grid-connected and islanded modes. Droop control implements power reallocation between DGs based on predefined droop characteristics whenever load changes or the microgrid is connected/disconnected to the grid, while the microgrid voltage and frequency is maintained at appropriate levels. Through voltage, frequency, and power characteristics in the simulation under different scenarios, the proposed control strategies have demonstrated to work properly and effectively. The simulation results also show the effectiveness of tuning PI parameters by the ABC.

LabView<sup>Ⓡ</sup>기반 6축 수직 다관절 로봇의 파라미터 스케쥴링 프로그래밍에 관한 연구

As industrial robots come into wider use, their control techniques are being developed along with enhancements in their performance. Specially, the dynamic performance of a 6-axis articulated industrial robot is greatly changed according to the position and orientation of the robot. This means that the PI parameter tuning of the robot and orientation of the robot. This mconsidering the dynamic characteristics of robot mechanism. In this study, programming was applied to automatically conduct parameter scheduling for various robot motions. Using forward and inverse kinematics of RS2, we can divide the working envelope of RS2 into 24 subspaces. We then conduct the gain-tuning according to each subspace. Finally, we program the actual gain scheduling, in which the optimized gain-tuning for each subspace to be passed should be changed for various robot motions using .

Optimum Induction Motor Speed Control Technique Using Genetic Algorithm

Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using genetic algorithm strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for GA-PI controller.

Optimum Induction Motor Speed Control Technique Using Particle Swarm Optimization

Industrial processes are subjected to variation in parameters and parameter perturbations, which when significant makes the system unstable. In order to overcome this problem of parameter variation the PI controllers are widely used in industrial plants because it is simple and robust. However there is a problem in tuning PI parameters. So the control engineers are on look for automatic tuning procedures. In recent years, many intelligence algorithms are proposed to tuning the PI parameters. Tuning PI parameters using different optimal algorithms such as the simulated annealing, genetic algorithm, and particle swarm optimization algorithm. In this paper a scheduling PI tuning parameters using particle swarm optimization strategy for an induction motor speed control is proposed. The results of our work have showed a very low transient response and a non-oscillating steady state response with excellent stabilization. The simulation results presented in this paper show the effectiveness of the proposed method, with satisfied response for PSO-PI controller.

English

This paper deals with the direct torque control (DTC) of BLDC motor drives by using particle swarm optimization technique. BLDC motors have wide variety of advantages like higher speed ranges, higher efficiency, and better speed versus torque characteristics. Direct torque control (DTC) is one of the efficient methods used in variable frequency drives to control the BLDC motor. DTC offers many advantages like fast torque response, no need of coordinate transformation and less dependence on the rotor parameters. In DTC, the estimated flux magnitude and torque are compared with their reference values. The reference torque is generated from the output of the speed regulator (PI controller).Tuning PI parameters (Kp, Ki) are essential to DTC system to improve the performance of the system at low speeds. In conventional PI controller, the performance of the motor may cause unexpected torque disturbances. Particle swarm optimization (PSO) is proposed to adjust the parameters (Kp, Ki) of the speed controller in order to minimize torque ripple, flux ripple, and stator current distortion.The simulation results of BLDC drive employing conventional PI and PSO based PI controllers is compared and evaluatedunder various load disturbances in the MATLAB/simulink environment.

English

This paper presents a new direct torque control (DTC) strategy for BLDC motor based on speed behaviour of PI and SMC based DTC of BLDC motor. In conventional direct torque controlled BLDC motor drive, there is usually undesired torque and flux ripple. So tuning PI parameters(Kp, Ki) are essential to DTC system to improve the performance of the system. PI controller is widely used in motor control system due to the simple control structure. In conventional PI controller, the performance of the motor may cause unexpected torque disturbances. To overcome the problems with PI controllers, in this paper, sliding mode controller is proposed to resolve the speed tracking problem for DTC of BLDC motor drive. The simulation results of DTC of BLDC motor drive with PI & SMC controllers are compared in the MATLAB/simulink environment.

Comparative Analysis of Genetic Algorithm and Fuzzy Logic Based Automatic Generation Control of Multi Area Power Systems

This paper illustrates the application of fuzzy logic FL) to automatic generation control (AGC) of a two area thermal power system and compares its performance with genetic algorithm (GA) based PI controller. The PI controller parameters are redesigned by the application of fuzzy logic. To verify the performance of the fuzzy based AGC, the task of tuning PI parameters is reformulated as an optimization problem for the application of GA. A comparison between the proposed fuzzy logic and GA based controllers, in terms of three time domain performance indices are presented.

PI Parameter Tuning by Specifying Disturbance Response in Chemical Process Control

This paper presents a method of PI control parameter tuning based on the estimated maximum step disturbance and the allowable peak value of the controlled variable and shows its effectiveness and limitation by simulation studies. This method is very useful to tune control parameters for chemical processes where limitations on loss prevention and quality control are represented by peak values of controlled variables.