PID controller Dotaz Zobrazit nápovědu
This paper presents a comprehensive study on the implementation and analysis of PID controllers in an automated voltage regulator (AVR) system. A novel tuning technique, Virtual Time response-based iterative gain evaluation and re-design (V-Tiger), is introduced to iteratively adjust PID gains for optimal control performance. The study begins with the development of a mathematical model for the AVR system and initialization of PID gains using the Pessen Integral Rule. Virtual time-response analysis is then conducted to evaluate system performance, followed by iterative gain adjustments using Particle Swarm Optimization (PSO) within the V-Tiger framework. MATLAB simulations are employed to implement various controllers, including the V-Tiger PID controller, and their performance is compared in terms of transient response, stability, and control signal generation. Robustness analysis is conducted to assess the system's stability under uncertainties, and worst-case gain analysis is performed to quantify robustness. The transient response of the AVR with the proposed PID controller is compared with other heuristic controllers such as the Flower Pollination Algorithm, Teaching-Learning-based Optimization, Pessen Integral Rule, and Zeigler-Nichols methods. By measuring the peak closed-loop gain of the AVR with the controller and adding uncertainty to the AVR's field exciter and amplifier, the robustness of proposed controller is determined. Plotting the performance degradation curves yields robust stability margins and the accompanying maximum uncertainty that the AVR can withstand without compromising its stability or performance. Based on the degradation curves, robust stability margin of the V-Tiger PID controller is estimated at 3.5. The worst-case peak gains are also estimated using the performance degradation curves. Future research directions include exploring novel optimization techniques for further enhancing control performance in various industrial applications.
The paper is focused on the computation of all possible robustly stabilizing Proportional-Integral-Derivative (PID) controllers for plants with interval uncertainty. The main idea of the proposed method is based on Tan's (et al.) technique for calculation of (nominally) stabilizing PI and PID controllers or robustly stabilizing PI controllers by means of plotting the stability boundary locus in either P-I plane or P-I-D space. Refinement of the existing method by consideration of 16 segment plants instead of 16 Kharitonov plants provides an elegant and efficient tool for finding all robustly stabilizing PID controllers for an interval system. The validity and relatively effortless application of presented theoretical concepts are demonstrated through a computation and simulation example in which the uncertain mathematical model of an experimental oblique wing aircraft is robustly stabilized.
- Klíčová slova
- Interval systems, Oblique wing aircraft, PI control, PID control, Robust stabilization,
- Publikační typ
- časopisecké články MeSH
With the rapid growth of sensor networks and the enormous, fast-growing volumes of data collected from these sensors, there is a question relating to the way it will be used, and not only collected and analyzed. The data from these sensors are traditionally used for controlling and influencing the states and processes. Standard controllers are available and successfully implemented. However, with the data-driven era we are facing nowadays, there is an opportunity to use controllers, which can include much information, elusive for common controllers. Our goal is to propose a design of an intelligent controller-a conventional controller, but with a non-conventional method of designing its parameters using approaches of artificial intelligence combining fuzzy and genetics methods. Intelligent adaptation of parameters of the control system is performed using data from the sensors measured in the controlled process. All parts designed are based on non-conventional methods and are verified by simulations. The identification of the system's parameters is based on parameter optimization by means of its difference equation using genetic algorithms. The continuous monitoring of the quality control process and the design of the controller parameters are conducted using a fuzzy expert system of the Mamdani type, or the Takagi-Sugeno type. The concept of the intelligent control system is open and easily expandable.
- Klíčová slova
- PID controller, artificial intelligence, expert systems, fuzzy methods, genetic algorithms, intelligent controller, optimization, softcomputing,
- Publikační typ
- časopisecké články MeSH
A programmable logic controller (PLC) executes a ladder diagram (LD) using input and output modules. An LD also has PID controller function blocks. It contains as many PID function blocks as the number of process parameters to be controlled. Adding more process parameters slows down PLC scan time. Process parameters are measured as analog signals. The analog input module in the PLC converts these analog signals into digital signals and forwards them to the PID controller as inputs. In this research work, a field-programmable gate array (FPGA)-based multiple PID controller is proposed to retain PLC scan time at a lower value. Concurrent execution of multiple PID controllers was assured by assigning separate FPGA hardware resources for every PID controller. Digital input to the PID controller is routed by the novel idea of analog to digital conversion (ADC), performed using a digital to analog converter (DAC), comparator, and FPGA. ADC combined with dedicated PID controller logic in an FPGA for every closed-loop control system confirms concurrent execution of multiple PID controllers. The time required to execute two closed-loop controls was identified as 18.96000004 ms. This design can be used either with or without a PLC.
- Klíčová slova
- PI control, analog to digital conversion, data acquisition, field programmable gate arrays, programmable logic controller, scan time,
- Publikační typ
- časopisecké články MeSH
This article deals with the calculation of all robustly relatively stabilizing (or robustly stabilizing as a special case) Proportional-Integral-Derivative (PID) controllers for Linear Time-Invariant (LTI) systems with unstructured uncertainty. The presented method is based on plotting the envelope that corresponds to the trios of P-I-D parameters marginally complying with given robust stability or robust relative stability condition formulated by means of the H∞ norm. Thus, this approach enables obtaining the region of robustly stabilizing or robustly relatively stabilizing controllers in a P-I-D space. The applicability of the technique is demonstrated in the illustrative examples, in which the regions of robustly stabilizing and robustly relatively stabilizing PID controllers are obtained for a controlled plant model with unstructured multiplicative uncertainty and unstructured additive uncertainty. Moreover, the method is also verified on the real laboratory model of a hot-air tunnel, for which two representative controllers from the robust relative stability region are selected and implemented.
- Klíčová slova
- -infinity norm, PID controllers, Robust control, Robust performance, Robust relative stability, Robust stability, Unstructured uncertainty,
- MeSH
- nejistota * MeSH
- Publikační typ
- časopisecké články MeSH
Steam condensers are vital components of thermal power plants, responsible for converting turbine exhaust steam back into water for reuse in the power generation cycle. Effective pressure regulation is crucial to ensure operational efficiency and equipment safety. However, conventional control strategies, such as PI, PI-PDn and FOPID controllers, often struggle to manage the nonlinearities and disturbances inherent in steam condenser systems. This paper introduces a novel multistage controller, TDn(1 + PIDn), optimized using the diligent crow search algorithm (DCSA). The proposed controller is specifically designed to address system nonlinearities, external disturbances, and the complexities of dynamic responses in steam condensers. Key contributions include the development of a flexible multi-stage control framework and its optimization via DCSA to achieve enhanced stability, faster response times, and reduced steady-state errors. Simulation results demonstrate that the TDn(1 + PIDn) controller outperforms conventional control strategies, including those tuned with advanced metaheuristic algorithms, in terms of settling time, overshoot, and integral of time weighted absolute error (ITAE). This study marks a significant advancement in pressure regulation strategies, providing a robust and adaptive solution for nonlinear industrial systems.
Implementing a suitable load frequency controller to maintain the power balance equation for a multi-area system with many power generating units poses a challenge to a power system engineer. Incorporation of renewable energy sources along with non-renewable units is another challenge while maintaining the stability of the system. Hence a robust intelligent controller is an essential requirement to achieve the objective of automatic load frequency control. This article introduces a novel and efficient controller designed for a three-control area within a deregulated multi-source energy system. The three areas include diverse power generation sources: Area 1 integrates thermal units, hydro units, and solar thermal power plants. In Area 2, there is a combination of distributed solar technology (DST) with thermal and hydro units. Area 3 incorporates a geothermal power plant alongside thermal and hydro unit. The proposed controller is a parallel combination of the tilted integral derivative controller (TID) and the integral derivative with a first-order filter effect (IDN). The controller's parameters are optimized using an advanced Coatis Optimization Algorithm (COA). High effective efficiency and absence of control parameters are the key advantages of Coatis Optimization Algorithm. The article highlights the superior performance of the newly developed TID + IDN controller in comparison to standalone TID and IDN controllers. This assessment is based on the observation of dynamic responses across different controller configurations. Additionally, the study examines the system's behaviour when incorporating energy storage units such as Redox Flow Batteries (RFB). Furthermore, the research investigates the system under various power transactions in a deregulated environment, considering generation rate constraints and governor dead bands. The proposed approach's robustness is demonstrated by subjecting it to extensive variations in system parameters and random load fluctuations. In summary, this paper presents an innovative TID + IDN controller optimized using a novel Coatis Optimization Algorithm within a three-area hybrid system operating in a deregulated context. Considering the poolco transaction and implementing the COA optimized TID + IDN controller with an error margin of 0.02%, the value of the objective function, ITAE for the transient responses is 0.1233. This value is less than the value obtained in other controllers optimized with different optimization techniques. In case of poolco transaction, the settling time of deviation of frequency in area-1, deviation of frequency in area-2, and deviation of frequency in area-3 are 8.129, 3.72, and 2.254 respectively. As compared to other controllers, the transient parameters are better in case of this proposed controller.
- Klíčová slova
- Coatis optimization algorithm (COA), Improved squirrel search algorithm (ISSA), Independent system operator (ISO), Integral derivative with a first-order filter effect (IDN), Integral time multiplied by absolute error (ITAE), Load frequency control (LFC), PID, Particle swarm optimization (PSO), Squirrel search algorithm (SSA), Tilted integral derivative controller (TID),
- Publikační typ
- časopisecké články MeSH
Load frequency control (LFC) plays a critical role in ensuring the reliable and stable operation of power plants and maintaining a quality power supply to consumers. In control engineering, an oscillatory behavior exhibited by a system in response to control actions is referred to as "Porpoising". This article focused on investigating the causes of the porpoising phenomenon in the context of LFC. This paper introduces a novel methodology for enhancing the performance of load frequency controllers in power systems by employing rat swarm optimization (RSO) for tuning and detecting the porpoising feature to ensure stability. The study focuses on a single-area thermal power generating station (TPGS) subjected to a 1% load demand change, employing MATLAB simulations for analysis. The proposed RSO-based PID controller is compared against traditional methods such as the firefly algorithm (FFA) and Ziegler-Nichols (ZN) technique. Results indicate that the RSO-based PID controller exhibits superior performance, achieving zero frequency error, reduced negative peak overshoot, and faster settling time compared to other methods. Furthermore, the paper investigates the porpoising phenomenon in PID controllers, analyzing the location of poles in the s-plane, damping ratio, and control actions. The RSO-based PID controller demonstrates enhanced stability and resistance to porpoising, making it a promising solution for power system control. Future research will focus on real-time implementation and broader applications across different control systems.
- Klíčová slova
- Automatic generation control (AGC), Firefly algorithm, Load frequency control, PID control schemes, Porpoising, Rat swarm optimization,
- Publikační typ
- časopisecké články MeSH
The EuroFlow PID consortium developed a set of flow cytometry tests for evaluation of patients with suspicion of primary immunodeficiency (PID). In this technical report we evaluate the performance of the SCID-RTE tube that explores the presence of recent thymic emigrants (RTE) together with T-cell activation status and maturation stages and discuss its applicability in the context of the broader EuroFlow PID flow cytometry testing algorithm for diagnostic orientation of PID of the lymphoid system. We have analyzed peripheral blood cells of 26 patients diagnosed between birth and 2 years of age with a genetically defined primary immunodeficiency disorder: 15 severe combined immunodeficiency (SCID) patients had disease-causing mutations in RAG1 or RAG2 (n = 4, two of them presented with Omenn syndrome), IL2RG (n = 4, one of them with confirmed maternal engraftment), NHEJ1 (n = 1), CD3E (n = 1), ADA (n = 1), JAK3 (n = 3, two of them with maternal engraftment) and DCLRE1C (n = 1) and 11 other PID patients had diverse molecular defects [ZAP70 (n = 1), WAS (n = 2), PNP (n = 1), FOXP3 (n = 1), del22q11.2 (DiGeorge n = 4), CDC42 (n = 1) and FAS (n = 1)]. In addition, 44 healthy controls in the same age group were analyzed using the SCID-RTE tube in four EuroFlow laboratories using a standardized 8-color approach. RTE were defined as CD62L+CD45RO-HLA-DR-CD31+ and the activation status was assessed by the expression of HLA-DR+. Naïve CD8+ T-lymphocytes and naïve CD4+ T-lymphocytes were defined as CD62L+CD45RO-HLA-DR-. With the SCID-RTE tube, we identified patients with PID by low levels or absence of RTE in comparison to controls as well as low levels of naïve CD4+ and naïve CD8+ lymphocytes. These parameters yielded 100% sensitivity for SCID. All SCID patients had absence of RTE, including the patients with confirmed maternal engraftment or oligoclonally expanded T-cells characteristic for Omenn syndrome. Another dominant finding was the increased numbers of activated CD4+HLA-DR+ and CD8+HLA-DR+ lymphocytes. Therefore, the EuroFlow SCID-RTE tube together with the previously published PIDOT tube form a sensitive and complete cytometric diagnostic test suitable for patients suspected of severe PID (SCID or CID) as well as for children identified via newborn screening programs for SCID with low or absent T-cell receptor excision circles (TRECs).
- Klíčová slova
- EuroFlow, diagnosis, flow cytometric immunophenotyping, primary immunodeficiencies (PID), severe combined immune deficiency (SCID), standardization,
- MeSH
- HLA-DR antigeny analýza MeSH
- imunofenotypizace metody MeSH
- kojenec MeSH
- lidé MeSH
- novorozenec MeSH
- předškolní dítě MeSH
- primární imunodeficience diagnóza imunologie MeSH
- průtoková cytometrie metody MeSH
- T-lymfocyty imunologie MeSH
- těžká kombinovaná imunodeficience imunologie MeSH
- thymus imunologie MeSH
- Check Tag
- kojenec MeSH
- lidé MeSH
- mužské pohlaví MeSH
- novorozenec MeSH
- předškolní dítě MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- HLA-DR antigeny MeSH
Ensuring the stability and reliability of modern power systems is increasingly challenging due to the growing integration of renewable energy sources and the dynamic nature of load demands. Traditional proportional-integral-derivative (PID) controllers, while widely used, often fall short in effectively managing these complexities. This paper introduces a novel approach to load frequency control (LFC) by proposing a filtered PID (PID-F) controller optimized through a hybrid simulated annealing based quadratic interpolation optimizer (hSA-QIO). The hSA-QIO uniquely combines the local search capabilities of simulated annealing (SA) with the global optimization strengths of the quadratic interpolation optimizer (QIO), providing a robust and efficient solution for LFC challenges. The key contributions of this study include the development and application of the hSA-QIO, which significantly enhances the performance of the PID-F controller. The proposed hSA-QIO was evaluated on unimodal, multimodal, and low-dimensional benchmark functions, to demonstrate its robustness and effectiveness across diverse optimization scenarios. The results showed significant improvements in solution quality compared to the original QIO, with lower objective function values and faster convergence. Applied to a two-area interconnected power system with hybrid photovoltaic-thermal power generation, the hSA-QIO-tuned controller achieved a substantial reduction in the integral of time-weighted absolute error by 23.4%, from 1.1396 to 0.87412. Additionally, the controller reduced the settling time for frequency deviations in Area 1 by 9.9%, from 1.0574 s to 0.96191 s, and decreased the overshoot by 8.8%. In Area 2, the settling time was improved to 0.89209 s, with a reduction in overshoot by 4.8%. The controller also demonstrated superior tie-line power regulation, achieving immediate response with minimal overshoot.
