Controller Tuning Method Research Articles

A GWO-Based Indirect IMC-PID Controller for DC-DC Boost Converter

A PID controller design using an internal model control (IMC) approach is a well-established method for controller tuning in a DC-DC boost converter. This study introduces an innovative implementation of a novel indirect Internal Model Control (IMC) strategy for PID controller design, tailored specifically for a DC-DC boost converter. While the indirect IMC approach has been documented in prior research, its application to boost converters signifies a substantial contribution to the field. The proposed method simplifies the tuning process by focusing exclusively on the plant shifting parameter ψ, thereby eliminating the need for an IMC filter. Optimal tuning is achieved through the Grey Wolf Optimization (GWO) method, which enhances the controller’s stability, robustness, and transient response in the presence of disturbances commonly encountered in boost converter operation. Extensive simulations are performed in a MATLAB Simulink environment to compare the performance of the GWO-based indirect IMC-PID controller with traditional PID and IMC-PID designs. Performance is assessed based on transient response parameters and performance indices, such as IAE, ISE, ITAE, and ITSE. Results reveal that the GWO-optimized indirect IMC-PID controller significantly outperforms conventional controllers, demonstrating enhanced servo and regulatory behaviors.

TDOF PID Controller for Enhanced Disturbance Rejection with MS-Constraints for Speed Control of Marine Diesel Engine

This study proposes a two-degree-of-freedom PID controller design and tuning method based on a simple pole placement approach to enhance servo and regulatory performance while ensuring the stability of diesel engines. In the modeling of the control target, the actuator is analytically modeled. In contrast, the type of model for the diesel engine is derived analytically, and its parameter estimation uses operational data from naval ships. The proposed controller consists of a PID controller to improve regulatory performance and a set-point filter to enhance servo response. PID controller parameters consist of the parameters of the controlled plant model and a single tuning variable. At the same time, the set-point filter comprises the controller parameters and a single weighting factor. To ensure the robust stability of the controller, the controller parameters are tuned based on the maximum sensitivity. To verify the effectiveness of this study, simulations for the speed control of a diesel engine with inherent nonlinearity were conducted under three scenarios. Performance was quantitatively analyzed using the integral of time-weighted absolute error, 2% settling time, 2% recovery time, specified maximum sensitivity, and maximum peak response value, and was compared with Skogestad’s IMC and Lee’s IMC. Based on evaluation indices, the proposed controller demonstrated superior performance in both servo and regulatory responses compared to the two existing control techniques while ensuring stability.

Optimizing olefin purification: An artificial intelligence-based process-conscious PI controller tuning for double dividing wall column distillation

This study investigates the light olefin separation using dual dividing wall columns (DWCs) and compares various proportional-integral (PI) controller tuning methods. A novel process-conscious reinforcement learning (RL) approach, utilizing Deep Deterministic Policy Gradient (DDPG), is developed by incorporating domain-specific knowledge into the reward function to ensure compliance with critical process variables and product purity. The DDPG-based PI tuning is evaluated against traditional methods such as Aspen’s recommended initial tuning, Ziegler-Nichols (ZN), and Cohen-Coon (CC). The result shows that the DDPG method significantly enhances control stability and accuracy, reducing error by factors of 11.9, 2.3, and 1.6 compared to Aspen, ZN, and CC, respectively. Additionally, DDPG demonstrates superior energy efficiency, consuming 13% less energy than the next best method. It also reduces purification costs by up to 13.5% and CO2 emissions by 20% compared to other methods. This study highlights the potential of integrating advanced RL techniques into industrial process control, delivering substantial improvements in stability, energy efficiency, economic, and environmental performance.

A Novel Simplified PID Controller Tuning Method for Exact Maximum Sensitivity Specification

Many PID (Proportional plus Integral plus Derivative) controller tuning methods are proposed in the control literature based on different closed-loop specifications. Also, tuning techniques, based on the maximum sensitivity specification, have been proposed in the literature. In this paper, a novel PID controller design method, based on maximum sensitivity, has been proposed. In this work, the PID controller is viewed as a gain and dynamic part and tuned separately. The PID controller dynamic part is tuned using one of the existing popular tuning methods. The tuned dynamic part is cascaded with the process. After that, the PID controller gain is tuned for the maximum sensitivity specification. The maximum sensitivity versus controller gain graph can be generated. The user can choose the controller gain for the desired maximum sensitivity specification. The popular Ziegler & Nichols and IMC (Internal Model Control) methods tune the dynamic part of the system in this work. These proposed techniques can achieve the desired maximum sensitivity by tuning the controller gain in the subsequent stage. Many illustrative instances are considered to display the applicability and the proposed technique’s simplicity.

Graphical tuning method of PID controller for systems with uncertain parameters based on affine algorithm

AbstractFor systems with uncertain parameters, it is very important to find a controller that can satisfy the preset robustness. The traditional method often ignores the influence of parameter coupling on the set boundary system when substituting the original system with the boundary system group, resulting in the calculated controller value region being too conservative. In this article, noise information is introduced based on affine algorithm to describe uncertain system parameters. Then, based on Kharitonov theorem, a new grouping method for boundary systems is proposed. This method takes the parameter coupling information into account when determining the boundary system, and avoids the problem of interval conservation. On this basis, a virtual phase margin tester is introduced to ensure that the obtained controller parameter range can make the system meet the specific robustness requirements. The results obtained in this article are general and strictly proved. Finally, examples are provided to illustrate the design process and verify the feasibility and efficacy of the proposed approach.

Pairing voltage-source converters with PI tuning controller based on PSO for grid-connected wind-solar cogeneration

This paper introduces a novel method to improve the efficiency of grid-connected wind-solar cogeneration systems. It involves the integration of Voltage-Source Converters (VSCs) with a Proportional-Integral (PI) tuning controller that has been optimized using Particle Swarm Optimization (PSO). Integrating renewable energy sources into power grids presents a set of challenges in terms of ensuring stability and optimizing power flow. VSCs are essential for effectively managing power flow between renewable sources and the grid. The PI controller is vital in maintaining voltage levels and ensuring stable operation. Conventional PI controller tuning methods commonly rely on heuristic approaches, which might only partially optimize performance across various operational conditions. In order to tackle this issue, PSO is utilized to fine-tune the parameters of the PI controller automatically. This results in a significant reduction in system deviations and a notable improvement in efficiency, even when faced with fluctuating wind and solar conditions. The simulation results conducted in MATLAB/Simulink confirm the effectiveness of the proposed approach in enhancing system stability and reducing response times. The PI controller optimized using PSO showcases exceptional adaptability to varying environmental and grid conditions, resulting in minimized power fluctuations and improved grid reliability. This study makes a valuable contribution to the field of renewable energy integration. It provides valuable insights into enhancing the performance of grid-connected wind-solar cogeneration systems through advanced control techniques and optimization algorithms such as PSO.

Experimentally validated analytical single parametric FOTID control for time-delayed fractional order processes

In current studies, non-integer order (NIO) plants with dead time have gained the significant attention of many researchers in the area of control theory. However, the design methods for fractional order controller tuning suffer from a lack of direct systematic tuning strategies due to a higher number of tuneable parameters. Most of the works on such design are optimisation-based whereas the analytical solutions are achieved with assumptions and approximations leading to compromised closed-loop robustness. This paper proposes a simple analytical design of a fractional-order tilt-integral-derivative (FOTID) controller for time-delayed NIO processes with a single tuneable parameter. Explicit tuning rules in terms of plant parameters are derived with user-defined stability margins. To prove the efficiency of the proposed control law, simulation comparisons with recently developed tuning rules are included. Lastly, the proposed control law is tested through experiments in a two-tank level loop for real-time validation.

A comparative study on PI-PD controller design using stability region centroid methods for unstable, integrating and resonant systems with time delay

In this paper, controller tuning methods based on stability region centroid methods reported in the literature are used to design PI-PD controllers for unstable, integrating and resonant systems with time delay. By analyzing the stability boundary locus (SBL) for the PD controller, which is utilized in the inner loop of this structure, the controller parameters are obtained using three methods which are the Weighted Geometric Center (WGC), Centroid of Convex Stability Region (CCSR), and Stability Triangle Approach (STA). These techniques were applied analytically, step by step. For the closed loop transfer function obtained in the inner loop of the controlled system, these three methods were utilized to design the PI controller in the outer loop, individually. Unit step responses of the controlled system, using PI-PD gains determined by each method, have been obtained. Furthermore, a disturbance of a certain time and amplitude was added to the systems to test the disturbance rejection behavior and the robustness performance of the methods. Perturbed responses were obtained through changing the model parameters at a certain rate. Time domain performance metrics were analyzed to compare the responses. The simulations were evaluated using settling time, rise time, and percentage overshoot as the assessment criteria. As a result of this study, the effectiveness of three methods, namely WGC, CCSR, and STA, in controller design for unstable, integrating, and resonant time-delay systems has been demonstrated. In addition, a comparison of time domain performance metrics is presented for the nominal and perturbed systems. Based on these comparisons, it is concluded that the methods outperform each other only in some time response performance measures. The presented results showed the advantages of these methods over each other in terms of some performance criteria. The contribution of this study to the literature is the comparative analysis of these three analytical methods.

Novel tuning rules for IMC-high-order PID load frequency controller of power systems

The problem of load frequency control (LFC) for power grids has received widespread attention in power industrial control. Ensuring the stability of the frequency is the primary concern that constrains the development of the electric power system. This paper presents a novel internal model control (IMC)- proportional-integral-derivative (PID) controller design method for LFC control systems, centered on pole-zero conversion. This method aims to simplify the system model's complexity and improve the system's performance. The IMC controller is approximated as a PID series compensator (high-order PID), with exact tuning formulas provided for various scenarios. These include single-area without or with reheat turbines, hydro turbines with transient droop compensators, wind turbines, and gas turbines. The tuning formulas are characterized by a single parameter, determined under robustness constraints and integrated time absolute error (ITAE). The proposed tuning method considers the generator rate constraint (GRC) and applies to multi-area single-source and multi-area multi-source power systems. The results of the simulation confirm that the controller tuning method presented in this paper has significant advantages over the existing design methods concerning robustness and anti-interference performance.

Using LQR controller for vertical position control on EAST

Vertical position control is essential for stabilizing plasma with elongated configurations. The EAST tokamak is equipped with a set of in-vessel control (IC) coils dedicated to this purpose. Currently, a PD controller with fixed parameters is used for the vertical position control of EAST plasma. However, the response of the plasma in the vertical position changes with changes in plasma configuration, which can result in different control parameter requirements. It is essential to develop a model-based fast-tuning control algorithm for ensuring stability in the vertical position under different configurations. In this study, a model-based vertical position controller tuning method based on a linear quadratic regulator algorithm (LQR) is proposed. Compared with contemporary PD controllers, the proposed model-based LQR controller can enable adjusting controller parameters based on the response of the system, achieving stable control under different vertical position responses. In the EAST experiment, the model-based LQR controller achieved stable control under a shot with a continuously increasing growth rate and reached a maximum controllable vertical displacement growth rate of 968 s−1. The robustness of the system was also demonstrated in a free drift experiment. The new vertical displacement control method can be adapted to different system states and plasma configurations and improve the controllability and safety of future devices.

Towards efficient control synthesis for nonlinear wave energy conversion systems: impedance-matching meets the spectral-domain

Existing studies within the literature that focus on designing parametric energy-maximizing controllers for Wave Energy Converter (WEC) systems predominantly rely on the impedance-matching (IM) principle, originally developed for linear time-invariant systems. Alternatively, iterative optimization routines are commonly employed for nonlinear WECs. However, these approaches often face a trade-off between effectiveness in maximizing energy extraction and computational efficiency. To address this limitation, this study proposes a computationally efficient controller tuning method for analogous synthesis in the case of nonlinear WECs. The proposed approach combines a statistical linearization technique known as spectral-domain modeling with the IM principle, to synthesize a Proportional–Integrative (PI) controller for a nonlinear WEC. Furthermore, a comparison is performed with two other synthesis methods: one based on a standard (i.e. linear) frequency-domain representation of the WEC that incorporates the IM principle, and the other employing a gradient-free optimization routine applied to the nonlinear time-domain model of the WEC for PI parameter tuning through exhaustive numerical search. A discussion on the effectiveness of each tuning method in maximizing energy absorption is provided, including an appraisal of their associated computational time requirements. Numerical analyses demonstrate that the proposed method, which integrates spectral-domain modeling and IM, can achieve (almost) optimal PI controller design for a nonlinear WEC. Furthermore, this study addresses the inaccuracies inherent in the frequency-domain approach and significantly reduces the computational time compared to the exhaustive search procedure. The findings of this research represent a significant advancement towards the development of simple, effective, and efficient IM-based techniques for synthesis of controllers in nonlinear WEC systems

High Bandwidth Current Regulator Design for PMSM Based on Frequency Sweep Correction

How to automatically correct controller para- metric mismatch and improve motor current closed-loop bandwidth in gain scheduling is an important issue for general motor drives. This paper firstly introduces the frequency domain tuning method of current controller. Then, the time delay identification and model parameters self-correction method based on frequency sweep is introduced to avoid the influence caused by parameter mismatch between plant and controller model. On this basis, phase lead module combined with active resistance term, is designed as a prefilter for current regulator, so as to achieve faster current dynamic response and improve disturbance rejection. Finally, the parameter setting for proposed current regulator is introduced to better practice. Experiments for different permanent magnet synchronous machines are carried out on a miniature drive system, the results fully verify the effectiveness of proposed scheme.

Optimization of basic PID control algorithm based on genetic algorithm and Matlab

This paper investigates how to optimize the basic PID algorithm by using population genetic forms. "In traditional PID control, the tuning of PID parameters mostly relies on the experience of the tuner. The main purpose of this paper is to use an algorithm that can automatically tune its parameters to self-tune a PID controller for an actual model." Based on the principle of genetic algorithm, this paper compares the traditional PID controller tuning methods to study the trend of the PID parameters during the iteration process as well as the trend of the PID controller adaptability. Through the principle of the algorithm and the iterative output, as well as in the code set the weights occupied by different performance indicators, it can not only flexibly adjust the degree of adaptation and make the algorithm more flexible, but also prove that the use of genetic algorithms for the rectification of the PID is more adaptable and convenient, with promising research prospects

A PID Tuning Method for Hexapod Gait Control Based on Genetic Algorithm

Hexapods are widely used in the field of rescue robots that transport in complex terrains which are difficult for traditional wheeled robots to traverse. Currently, the method for hexapod gait control is often PID, a classical method that is universally exploited in all control systems in general. However, the fine-tuning of PID’s hyper-parameters(i.e. kp, ki and kd) mainly rely on chances and the experience of tuners. Therefore, it is both urgent and critical to find an automatic way to get through the tuning process and return optimal results. Aiming at this, this paper puts forward a novel approach to adjust these parameters with genetic algorithm. It first builds a computational model of the hexapod, then the terrain, then designates the input, output and constants of the system, builds the PID closed loop, and finally tunes it using genetic algorithm. The approach described in the paper leads to optimal results in a reasonable amount of time. This makes having hexapods walk on uneven terrain with ease and automacy an alluring possibility.

Review of PID control design and tuning methods

Owing to the fact that PID controllers have a simple and fixed form and good robustness, they are widely used in industrial production. However, the complexity and non-linearity of control systems affect the use of a traditional PID controller. Therefore, how to design a stable PID controller that does not require an accurate mathematical model or how to adjust the parameters of the PID controller have become hot topics of research today and in the future. PID controllers are outlined in this study, such as position PID controllers, incremental PID controllers, differential prior PID controllers, fuzzy PID controllers. Besides, two different PID controller rectification methods are described: the model-based parameter self-tuning method and the rule-based self-tuning method. What is more, this paper also compares these PID controllers, and clarifies the advantages and disadvantages of each PID controller. And at the end, it predicts the prospect of PID controllers and PID controller rectification methods. PID has a great development prospect, and its future research direction is not only to study new algorithms, but also needs to study how to combine the excellent existing PID controllers to make up for their shortcomings.

A Study of PI Controller Tuning Methods Using the Internal Model Control Guide for a Ship Central Cooling System as a Multi-Input, Single-Output System

Since the variable-speed seawater pump and the three-way valve of a ship’s central cooling system are forms of feedback from the same output signal, these controllers may cause interference when they are not coordinated. Therefore, studying an efficient control tuning method for a central cooling water system is necessary. In this study, a central cooling water system is modeled using Matlab Simulink by utilizing an actual operation dataset, and unknown parameters are estimated for fine-tuning. The simulation model is then verified using the second operating dataset. Additionally, transfer functions are developed for the freshwater output temperature against the three-way valve openness input and the electrical power frequency input to the seawater pump motor, supposing that the two systems are independent. Then, the two PI controllers are tuned using internal model control (IMC) filters. Moreover, the modified internal model control tuning method is suggested, using the character of the central cooling system, which has a large time constant for the heat exchanger system with the seawater pump and a small time constant for the three-way valve system. This method simplifies the tuning of the two combined PI controllers, enhancing the seawater pump’s overall efficiency and the three-way valve’s operation. This study presents the proposed tuning methods based on the IMC filter and modified IMC guide, which confirmed the simple determination of the gain values of the PI controller with the efficient control of the rotational speed of the seawater pump and the three-way valve with reasonable control of the freshwater outlet temperature.

An efficient method for unsteady hydrofoil simulations, based on Non-Linear Dynamic Lifting Line theory

This paper presents a Non-linear Dynamic Lifting Line (NDLL)-based method for analysing hydrofoil vessels in waves. The method is validated, and its utility is demonstrated in a case study.The NDLL accounts for dynamic and 3D effects through a panellized wake and allows the evaluation of the pressure distribution on hydrofoils. Improved models are presented for wake deformation, wake composition, hydrofoil interaction, and the viscous core of vortex wake models. Furthermore, an efficient way of accounting for Green function terms through a matrix interpolation method is presented.Validation is performed by comparison with aerodynamic and hydrodynamic experiments and new 3D RANS simulations. The RANS simulations focus on geometries and operating conditions deemed representative of hydrofoiling fast ferries. Predictions of steady and dynamic lift, drag, wake velocities and cavitation inception are evaluated, and results correspond well with the benchmark data.A simulator framework is introduced, which integrates the hydrodynamic model with kinetics, kinematics, and control system models. This enables analyses of free-running vessels under active control, including assessments of resistance, motions, and the hydrofoil pressure distribution.The case study constitutes a qualitative verification of the simulator and flight control tuning methods, and reveals the possibility of negative added resistance in waves.

Online auto-tuning of multiresonant current controller with nature-inspired optimization algorithms and disturbance in the loop approach

This paper presents a novel tuning method of a complex multiresonant current controller (MRCC). An online auto-tuning process is proposed to provide optimal coefficients suitable for the real-time operation of a grid-connected power converter. The time-consuming and inaccurate simulation stage based on the model of the plant is omitted. A novel function of constraints has been introduced into the optimization scheme to ensure the desired behavior of the control system. In this solution, the noise level of a control signal and the rise time of controlled currents are directly defined. To the author’s best knowledge, it is the first time when such a solution is proposed. Next, the most commonly used meta-heuristic optimization algorithms were applied to solve this particular optimization problem. Another original concept presented in the paper is the application of the disturbance-in-the-loop (DiL) approach. In this method, the distorted phase voltages are emulated during the tuning stage, and optimal coefficients of MRCC are selected in the off-grid operation of the power converter. The proposed solution ensures safe and efficient online tuning of the MRCC for an extremely simple performance index. As a result, the high-performance operation of the grid-connected inverter is achieved. A brief stability analysis based on Lyapunov’s stability theory is included. Experimental results obtained for grid-connected inverter indicate superior disturbance attenuation and current tracking. Advantages of the proposed approach are exhibited when compared to two analytical reference solutions.

ANALYSIS OF NON-INTERACTING LEVEL PROCESS USING VARIOUS PI CONTROL SETTINGS: A COMPARATIVE STUDY

This study presents a comparative analysis of different proportional-integral (PI) controller tuning methods for the control of a non-interacting liquid level process. Four different PI controller tuning methods, Ziegler-Nichols, Cohen-Coon, Tyreus-Luyben, and Internal Model Control, are evaluated based on their ability to track setpoint changes and reject disturbances. The simulation results show that all four tuning methods can provide satisfactory performance, but the Internal Model Control method outperforms the others in terms of all performance metrics evaluated. The Ziegler-Nichols method produces the worst performance, while the Cohen-Coon and Tyreus-Luyben methods perform better but still have limitations. This study highlights the importance of choosing the appropriate tuning method for liquid level control systems.

A Novel PI-PD Controller Tuning Method based on Neutrosophic Similarity Measure for Unstable and Integrating Processes with Time Delay

Integrating systems and unstable systems are two types of systems that are widely used in various industries, including control engineering and electrical engineering. However, controlling these systems can be a daunting task due to their inherent complexity. To address this challenge, the PI-PD controller structure has been widely adopted in the industry, as it has proven to be very successful in controlling integrating and unstable systems. In this paper, a new design method is proposed to determine the optimal controller parameters in the control of integrating and unstable systems with time delay. The design method utilizes a Genetic Algorithm-based optimization technique, which incorporates a new objective function that is based on the neutrosophic similarity measure. Two different types of plants have been chosen as examples in this study. The first plant is a time-delayed integrating system. The second plant is an unstable system, which means that the output signal is very sensitive to any changes or disturbances in the input signal. This study examines the parameter uncertainties of systems by comparing them with some design methods from the literature. The results are presented comparatively in figures and tables to show the superiority of the proposed method.