Conventional Tuning Methods Research Articles

Advanced Controllers Implementation for Speed Control Analysis of Two Mass Drive System

The speed control of two mass drive systems is presented in this paper. For the purpose of analysis, PI, Linear Matrix Inequality controller and Internal Model Controller are chosen. Tuning of PI controller is achieved by Zeigler Nichols method, whereas the LMI and IMC are adapted with the conventional method of tuning. The various simulations are carried out in order to analyze the performance index of these controllers and to fix the best controller, and the results are compared

A Comparative Analysis of SIMC-PID with Other Conventional Techniques for Automobile Vehicle Air Conditioning System Control

Decreasing the thermal increase inside vehicles and safeguarding suitable vehicular temperature levels may result in improved vehicle fuel economy, reliability and passenger comfort. However, getting suitable techniques to attain this has been a great challenge to the system engineers. Although, the use of conventional techniques have proffered a great insight in solving the problem of temperature control in air conditioning system, however, they suffered from inefficient and non-lasting solution to the heat generated within the cabin walls. Thus, in this present paper, a Simple Internal Model Control based Proportional Integral Derivative (SIMC-PID) controller for automobile vehicle temperature is proposed. The SIMC method is based on the internal model control (IMC) theory and proposes a simple methodology for the tuning of the PI and PID industrial controllers. The suggested approach is compared with the conventional tuning methods such as Zeigler-Nichols, Cohen-Coon and Chien-Hrones-Reswick based on energy conservation and mass balance principles. Results obtained showed that the proposed SIMC-PID method could be of great significance in controlling the air-conditioning system temperature compared with the conventional tuning techniques.

A New Methodology for a Retrofitted Self-tuned Controller with Open-Source FPGA.

Servo systems are feedback control systems characterized by position, speed, and/or acceleration outputs. Nowadays, industrial advances make the electronic stages in these systems obsolete compared to the mechanical elements, which generates a recurring problem in technological, commercial and industrial applications. This article presents a methodology for the development of an open-architecture controller that is based on reconfigurable hardware under the open source concept for servo applications. The most outstanding contribution of this paper is the implementation of a Genetic Algorithm for online self tuning with a focus on both high-quality servo control and reduction of vibrations during the positioning of a linear motion system. The proposed techniques have been validated on a real platform and form a novel, effective approach as compared to the conventional tuning methods that employ empirical or analytical solutions and cannot improve their parameter set. The controller was elaborated from the Graphical User Interface to the logical implementation while using free tools. This approach also allows for modification and updates to be made easily, thereby reducing the susceptibility to obsolescence. A comparison of the logical implementation with the manufacturer software was also conducted in order to test the performance of free tools in FPGAs. The Graphical User Interface developed in Python presents features, such as speed profiling, controller auto-tuning, measurement of main parameters, and monitoring of servo system vibrations.

Ultra-low-loss tunable piezoelectric-actuated metasurfaces achieving 360\xb0 or 180\xb0 dynamic phase shift at millimeter-waves

Phase shifting metasurfaces typically consist of an ordered metallic geometry that is patterned onto a dielectric substrate and incorporate active devices or materials that enable dynamic tuning. Existing methods at mm-wave and submillimeter bands typically suffer from high losses, which are predominantly produced by the inherent limitations of the tuning elements or materials. This report presents a new, ultra-low-loss and phase-tunable, reflection type metasurface design, which outperforms previously reported technologies in terms of phase shifting and loss. The proposed technique utilizes a variable air cavity, formed between a periodic array and a ground plane, which is controlled by means of a piezoelectric actuator. Two metasurface designs are presented and experimentally tested. Firstly, a square patch element metasurface that is capable of achieving a continuous 180° phase shift across a wide bandwidth, between 35 and 65 GHz. Also presented is a double-cross element metasurface that provides full 360° phase control between 57 and 62 GHz. The variable air cavity is controlled by means of a piezoelectric actuator that supports and varies the height of a ground plane, providing highly accurate, millisecond, displacement. Unlike conventional tuning methods, the tuning mechanism, in this case the moving ground plane, introduces no additional sources of loss and enables an average loss performance of 1 dB. Full-wave simulations are presented and experimentally validated with measurements of both metasurface prototypes. The proposed approach is scalable from microwave up to THz frequencies, due to the electro-mechanical and low loss nature of the tuning.

A novel grey decision-DE optimized internal model controller for vibration control of nonlinear uncertain aeroelastic blade system

In this paper, a novel grey decision-differential evolution (GD-DE) optimized internal model controller is proposed for the control of nonlinear aeroelastic blade system (ABS) under time-varying uncertainties and control saturations. Two-port internal model control structure is presented for saturation compensation. The filter parameter of the controller is optimally tuned by proposed GD-DE algorithm, which is designed based on the grey decision incidence theory and differential evolution algorithm. The superiority of GD-DE optimized tuning technique is verified, compared to conventional IMC tuning method and other evolutionary algorithm based techniques. The robustness is analysed by comprehensive simulations from time-invariant uncertainties to large periodic or random time-varying uncertainties. The realistic condition with input/output disturbances is also involved. Simulation results show that the proposed controller outperforms existing adaptive IMC controller and other advanced controllers with greatly improved dynamic performance, stronger robustness and better saturation compensation on various conditions.

Bacteria foraging optimisation algorithm based optimal control for doubly‐fed induction generator wind energy system

In this study, an optimisation method, based on bacteria foraging, is investigated to tune the parameters of the proportional–integral (PI) controllers in a doubly-fed induction generator (DFIG) wind energy system connected to the grid. The generator is connected to the grid directly at the stator and through the back-to-back converter at the rotor. The control system includes PI controllers, at the rotor side, to regulate the rotor currents and PI controller to regulate the dc-link voltage for efficient power transfer. The control parameters, of three PI controllers, are optimised offline using the bacteria foraging optimisation algorithm and a modelled DFIG wind energy system. Various performance criteria, based on the tracking errors, are used to assess the efficiency of the optimisation method. Furthermore, the conventional tuning method and genetic algorithm optimisation method are conducted and compared to the bacteria foraging optimisation method to demonstrate its advantages. The optimised control parameters are evaluated on a DFIG wind energy experimental setup. Experimental and simulation results are provided to validate the effectiveness of each optimisation method.

Optimal interface controller design for haptic system

Haptic technology is the future oriented technology having wide applications in various field from medical, military and pilot training to video games and smartphones. In medical, it can prove a major asset for training the surgeon. The key performance issues in a haptic system are stability and transparency. This paper presents the design of haptic interface controller (HIC) for a 1-DOF haptic system designed to be used by surgical practitioners. The designed controller emphasizes on stability and transparency under the presence of uncertainty and delay. The optimal parameter of HIC has been selected using Genetic Algorithm (GA) and modified Particle Swarm Optimization (m-PSO). The performance of the designed controller is evaluated in terms of performance measure and compared with the conventional tuning method.

Design of coupled inductors using split winding scheme for bridgeless SEPIC

A bridgeless single-ended primary inductance converter (SEPIC) is a highly preferred single-stage front-end AC–DC converter for applications requiring a wide variation of DC voltage because it also gives improved performance in terms of the quality of supply current. This study presents the design of coupled inductors for the bridgeless SEPIC using the split winding scheme. With coupling incorporated the required value of self-inductances of the input and output inductors for the same performance is reduced. Also, they can be wound on the same core, thereby resulting in a reduction in size. The conventional method of tuning the coupling coefficient by adjusting the air-gap is tedious. A split winding scheme for the distribution of windings over three limbs of E-core for obtaining the desired coupling coefficient is presented. The split winding scheme for the design of coupled inductors for bridgeless SEPIC converter rated for 500 W, 20 kHz is illustrated. The effect of coupling on the volume, weight, cost, and efficiency of the converter is compared with the conventional SEPIC converter without coupling for a similar performance. The performance of the proposed converter is evaluated using MATLAB/Simulink simulation and experimental results with a laboratory prototype rated for 500 W.

PID Controller Tuning using ACO Algorithm for AVR Systems

This paper features an effective technique to device the parameters of PID controllers for utilization together with an Automatic Voltage Regulator System (AVR). The quintessential goal is to acquire a good load disturbance response by minimizing the performance index/(Integral time square error). Simultaneously, the transient response is assured by limiting maximum overshoot, settling time and rise time of the step response to minimal values. For achieving these goals, optimum and quick tuning of the parameters (Kp, Ki, and Kd) is essential. In an effort to accomplish the aforementioned, the paper put forth an algorithm developed based on the Ant Colony Optimization technique (ACO) to decide optimal gains of PID controller and for getting optimal performance within an AVR system. Simulation results establish superior control response may be accomplished in comparison with methods like conventional tuning method (trial and error) and built-in genetic algorithm (GA) took-kit.e.

Analysis of Model-Based Tuning Method of PID Controller for Excitation Systems Considering Measurement Delay

In this paper, a model-based tuning method for a PID controller of excitation systems based on a simplified model that considers measurement delay is proposed. The conventional model-based tuning method, which has been studied previously, uses a simplified excitation system model that ignores all the delay components. However, since the rms voltage measurement can take hundreds of milliseconds to calculate depending on the system settings, this delay cannot be ignored when the required response needs to be as fast as the measurement delay. Furthermore, the linearity of the measurement method is not taken into account because the measurement delay has already been ignored. Therefore, in this paper, a simplified model that considers measurement delay and its linearity is proposed, and a model-based tuning method of PID controllers for two kinds of excitation systems is proposed and compared with the conventional method by analysis. To verify the analysis and proposed tuning method, experiments are conducted for both excitation systems.

An Investigation of Gate Voltage Oscillation and its Suppression for SiC MOSFET

Silicon Carbide (SiC) MOSFET has undergone a rapid development and commercialization in recent years due to its superior features. However, the mainstream commercial SiC MOFESTs are often fitted to packages that are previously designed for silicon-based devices, which brings oscillation issues at faster switching speed. This paper investigates the gate oscillation based on the parasitic parameter analysis of equivalent SiC MOSFET circuit, where the influences of di/dt and dv/dt are discussed and compared. Moreover, the paper recommends a guideline for the acceptable gate oscillation for SiC MOSFET based on the data from manufacturers and carries out detailed comparisons of the conventional gate driver tuning methods. It is found that the external gate-source capacitor provides better switching performance and gate oscillation suppression than the tuning of gate resistor. The analysis and the switching performance are verified from the experimental results based on Cree CAS300M12BM2 SiC MOSFET Module.

Parameter Estimation and an Extended Predictive-Based Tuning Method for a Lab-Scale Distillation Column.

The present study proposes a new PI controller tuning method using extended predictive control (EPC). The PI controller parameter values are calculated using the EPC controller output and its closed-loop response. This provides a simple and an effective tuning strategy which results in an improved closed-loop response compared to conventional tuning methods. The tuning methodology is applicable for single input single output and multi input multi output stable processes. Simulation and experimental results reveal the efficacy of the method under plant uncertainty conditions.

Determination of Optimal Q-V Droop Controller Parameters for Three-Phase Modular UPS System Based on Genetic Algorithm (GA)

This paper presents an optimized reactive power-voltage (Q-V) droop controller parameters for three-phase modular uninterruptible power supply (UPS) based on genetic algorithm (GA). The main objective of this paper is to minimize the voltage regulation error when there are changes in loads. In addition to select the control parameters carefully to promote the performance of the system against disturbances. This is substantial to attain power sharing between different UPS units to balance sudden disturbances that happen when there are changes in loads. We propose a discrete proportional-integral controller which compares the output voltage with the reference value given by the droop control loops then generates suitable voltage vector signal to pulse-width modulation (PWM) inverter. The fitness function for the optimization problem is formulated by considering the sum of square errors in voltage. This fitness function converges to local minima during the iterative operation of the genetic algorithm. Thus, the optimal parameters of the voltage droop control can be discovered with great probability. Simulation of two parallel-connected three-phase UPS units are carried out using MATLAB/SIMULINK R2018a. Comparison between the conventional trial and error tuning methods and GA optimization is performed. The results show that GA succeeded to minimize the output voltage root mean square error (RMSE) and to enhance the power sharing capability when there is variation in loads.

Parameter effect analysis of particle swarm optimization algorithm in PID controller design

PID controller has still been widely-used in industrial control applications because of its advantages such as functionality, simplicity, applicability, and easy of use. To obtain desired system response in these industrial control applications, parameters of the PID controller should be well tuned by using conventional tuning methods such as Ziegler-Nichols, Cohen-Coon, and Astrom-Hagglund or by means of meta-heuristic optimization algorithms which consider a fitness function including various parameters such as overshoot, settling time, or steady-state error during the optimization process. Particle swarm optimization (PSO) algorithm is often used to tune parameters of PID controller, and studies explaining the parameter tuning process of the PID controller are available in the literature. In this study, effects of PSO algorithm parameters, i.e. inertia weight, acceleration factors, and population size, on parameter tuning process of a PID controller for a second-order process plus delay-time (SOPDT) model are analyzed. To demonstrate these effects, control of a SOPDT model is performed by the tuned controller and system response, transient response characteristics, steady-state error, and error-based performance metrics obtained from system response are provided.

Dynamics and Control of Liquid Level in Annular Conical Tank Process: Modelling and Experimental Validation

Objectives: The present work has been carried out to prove the superiority of IMC based PID control strategy over the conventional PID, based on simulation studies and experimental validation on an annular conical tank liquid level nonlinear process. Methods/Statistical Analysis: First principles based Mathematical Model of an annular conical tank liquid level nonlinear process has been developed based on the mass balances and outlet flow hydraulic characteristics. Linearization of the nonlinear model at a specific steady-state operating point led to the theoretical development of state-space and standard first order transfer function models. Open loop and closed loop experimental studies on a computer controlled physical setup were performed to identify the parameters of a FOPDT Model with variable gain and time constant. IMC based PID controller was designed and compared to the conventional PID controller. Findings: The variation in process parameters was attributed to two factors: (a) the variation in annular cross sectional area of the conical tank at different levels, and (b) the variation in outlet flow resistance. The IMC based PID controller has been shown to exhibit superior performance in terms of quantitative performance indices such as ISE, IAE, ITAE, rise time, settling time and percentage overshoot, at four different steady-states. Application/Improvements: Study of Modelling of annular conical tank process and a systematic methodology of process system identification from experimental setup have been reported. The advantages of IMC based PID controller design over the conventional PID tuning method has been experimentally verified. Keywords: Annular Flow Conical tank process, FOPDT model, System Identification, PID controller tuning, IMC based PID.

Daily Peak Load Forecasting by Artificial Neural Network using Differential Evolutionary Particle Swarm Optimization Considering Outliers

Abstract This paper proposes an Artificial Neural Network (ANN) based daily peak load forecasting method by differential evolutionary particle swarm optimization (DEEPSO) considering outliers. When outliers exist in the training data, forecasting accuracy of daily peak load forecasting can be affected by the outliers. Therefore, engineers have removed the outliers from training data so far and it is a heavy burden for engineers. Utilization of evolutionary computation has a possibility to solve this problem. Moreover, forecasting accuracy may be improved using evolutionary computation techniques instead of the conventional stochastic gradient descent (SGD) with outliers. The proposed weights tuning method by DEEPSO is compared with the conventional weights tuning methods by SGD and PSO for verification of the efficacy of the proposed method.

Swarm-Intelligence Tuned Current Reduction for Power-Assisted Steering Control in Electric Vehicles

In electric vehicle technology, battery energy conservation is paramount due to the dependency of all system operations on the available battery. The proportional, integral and derivative (PID) controller parameters in the electric power assisted steering system for electric vehicle need to be tuned with the optimal performance setting so that less current is needed for its operation. This proposed two methods under the umbrella of swarm-intelligence technique namely particle swarm optimization (PSO) and ant colony optimization (ACO) in order to reduce current consumption and to improve controller performance. The investigation involves an analysis on the convergence behavior of both techniques in search for accurate controller parameters. A comprehensive assessment on the assist current supplied to the assist motor of the system is also presented. Investigation reveals that the proposed controllers, PID-PSO and PID-ACO are able to reduce the assist current supplied to the assist motor as compared to the conventional PID controller. This study also demonstrate the feasibility of applying both swarm-intelligence tuning method in terms of reduced time taken to tune the PID controller as compared to the conventional tuning method.

Research on optimization of hydraulic turbine governor based on PSO algorithm

Due to the complex structure of the turbine control system, poor dynamic performance and difficult stability, the conventional PID tuning method widely used in the turbine governor is becoming increasingly difficult to meet the actual control requirements. Based on the structure and mathematical model of the turbine control system, this paper introduces the PSO (Particle Swarm Optimization Algorithm) to optimize the PID parameters of the turbine governor based on ITAE as the fitness function. The simulation results show that the PSO algorithm is an effective parameter optimization method for the turbine governor, which has better dynamic performance compared with the conventional PID control.

3D FEM simulation of tool wear in ultrasonic assisted rotary turning

In this study, a model is developed to predict tool wear and heat distribution on tool faces in conventional, rotary, and ultrasonic assisted rotary tuning methods. To model the flank wear rate, a modified Usui wear rate model which includes tool clearance angle, is proposed. As well as the simulation, a series of experiments is conducted to validate the model, by comparison of the predicted and measured flank wear rates, which are shown to be in good agreement. According to the results of the simulation, localized heat in the tool-chip contact zone during conventional turning is distributed in the circumference of the tool cutting edge in rotary turning. Due to the existence of disengagement periods in ultrasonic-assisted rotary turning, the total time for thermal conduction in the contact zone decreases, resulting in a significant reduction in tool wear.

To design and develop a fuzzy based power flow controller for the stability improvement of a power system

With the growth and development of power electronics in the field of power system enumerates the new and efficient forms of controlling the power. This paper deals with a systematic approach to design an Interline Power Flow Controller (IPFC) for multi-machine infinite bus power system is proposed. It is an independent controller system which is suitable for an individual line compensation of a multiline power system. A Simulink model of an IPFC based multi-machine system along with fuzzy is developed. The outcomes obtained were compared with the conventional method of tuning the proposed controller to confirm the effectiveness and robustness of the developed controller. The analysis of an IPFC is assuring the response towards the system’s operation. In this proposed scheme, the controller is designed with the series and shunt configuration of an interline power flow controller using fuzzy technology. The two types of configuration in the designed system are manipulated in which most of the compensation in a multiline system is provided by means of the series controller, the shunt controller which is used for the real power compensation. The simulation of a designed system is done using MATLAB software-Simulink.