Advanced Control for Applications最新文献

{"title":"Hunter–Prey Optimization Algorithm for Optimal Allocation of PV, DSTATCOM, and EVCS in Radial Distribution Systems","authors":"Soundarya Lahari Pappu,&nbsp;Varaprasad Janamala,&nbsp;A. S. Veerendra","doi":"10.1002/adc2.231","DOIUrl":"https://doi.org/10.1002/adc2.231","url":null,"abstract":"<div>\u0000 \u0000 <p>This research article instigates a seminal approach for optimizing reactive power in renewable energy sources (RES) and electric vehicles (EVs) coalescing distribution systems, using the innovative Hunter–Prey Optimization (HPO) algorithm in conjunction with DSTATCOM as a reactive power compensator. The proposed methodology aims to minimize losses, enhance voltage stability, and improve overall system performance by simultaneously optimizing reactive power flows in photovoltaic RES (PV_DG), EV charging stations (EVCS), and DSTATCOMs within the distribution system. Simulations carried on IEEE-33, IEEE-69, and IEEE-118 test bus systems in MATLAB environment demonstrate that the HPO-based approach achieves a 91.47% and 96.61% reduction in real power losses and an improvement in voltage profile with a minimum voltage value of 0.991 and 0.994 p.u. (respectively for IEEE-33 and 69 bus systems), compared to traditional algorithms. These results highlight the lofty performance of the HPO method, effectively addressing the challenges posed by the integration of RES and EVs along with DSTATCOM.</p>\u0000 </div>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.231","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Particle Swarm Optimization Algorithm Based Fuzzy PID Controller Design for Speed Tracking Control of Separately Excited DC Motor","authors":"Dessale Akele Wubu,&nbsp;Ayodeji Olalekan Salau,&nbsp;Girma Kassa Alitasb","doi":"10.1002/adc2.237","DOIUrl":"https://doi.org/10.1002/adc2.237","url":null,"abstract":"<div>\u0000 \u0000 <p>Fuzzy logic control is the most common method utilized to tune proportional integral derivative (PID) controller parameters online. However, proportional integral derivative controllers often perform poorly in the control of nonlinear and/or complicated systems, such as direct current motors, where the model parameters are not exactly known if the scaling factors are not properly selected besides the membership function and rule sets in a fuzzy logic controller design. Finding the most suitable scaling factors for complex systems where the model parameters are not exactly known or nonlinear systems is a challenging task. Furthermore, traditional trial and error techniques of determining appropriate scaling factors are experience based, time consuming, and may not always provide optimal response. In this paper, a particle swarm optimization algorithm is suggested for optimizing the input and output gains of the fuzzy PID controller. The robustness and effectiveness of the suggested controller was validated using MATLAB/Simulink. The performance of the suggested controller is compared with the Ziegler Nichols and Particle Swarm Optimization Algorithm tuned PIDs, and fuzzy PID controllers. The simulation result show that the fuzzy PID controller whose scaling factor was tuned using particle swarm optimization outperforms the other controllers in avoiding disturbance and has a better trajectory tracking capability.</p>\u0000 </div>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.237","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142860583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilization of Hydrogen Using Hydrogen Storage Alloys","authors":"Hiroyuki Taniguchi,&nbsp;Hideki Tokuyama,&nbsp;Nobuhito Tsurui","doi":"10.1002/adc2.230","DOIUrl":"https://doi.org/10.1002/adc2.230","url":null,"abstract":"","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.230","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142868943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing Electric Vehicle Charging Systems With a Versatile Bidirectional Buck Boost DC to DC Converter Integrated With Solar Photovoltaic Technology","authors":"D. Arun Kumar,&nbsp;A. Ramkumar,&nbsp;S. Rajendran","doi":"10.1002/adc2.233","DOIUrl":"https://doi.org/10.1002/adc2.233","url":null,"abstract":"<div>\u0000 \u0000 <p>Renewable energy-based electric vehicle (EV) charging systems have become increasingly popular in recent years, particularly in commercial and industrial environments. This study looks at a broad-spectrum bidirectional buck boost DC to DC converter employing solar photovoltaic (PV) technology. This combination is intended for usage in vehicle to grid (V2G) and grid to vehicle (G2V) modes for electric car applications. In both operating modes, the converter attains a high-voltage transfer gain ratio (VTGR) without any theoretical output voltage restrictions. It provides evidence on suitable nature for EV applications with versatility, redundancy, and practicality. The theoretical evaluation was verified by the development and testing of a 500 W experimental model. A peak efficiency of 97.8% and 97.4% in V2G and G2V modes is indicated by the data, confirming the usefulness and efficacy of this integrated strategy. These results show that the bidirectional buck boost DC to DC converter, when combined with the suggested integration of PV and EV, improves V2G-G2V operations in EV charging systems and is both practicable and feasible.</p>\u0000 </div>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.233","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862034","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Real-Time Model Predictive Control of Air-Conditioners Through IoT—Results From an Experimental Setup in a Tropical Climate","authors":"H. Shamachurn,&nbsp;M. Seebaruth,&nbsp;N. S. Kowlessur,&nbsp;S. Z. Sayed Hassen","doi":"10.1002/adc2.232","DOIUrl":"https://doi.org/10.1002/adc2.232","url":null,"abstract":"<div>\u0000 \u0000 <p>There is an increasing demand for air-conditioners (ACs) to maintain a comfortable indoor environment for all types and sizes of buildings including commercial, industrial, and office spaces. Such ACs are mostly operated by traditional ON–OFF controllers to maintain a temperature setpoint. Extensive control engineering knowledge resulting from experiments on actual buildings is needed before the wide application of an advanced control methods, such as model predictive control (MPC), which are more effective and energy-efficient than the traditional controllers. Simulation studies on the application of control may provide promising results, but the corresponding experimental validations may prove otherwise. User-friendly experimental setups to investigate the performance of real-time advanced control on an actual building and its HVAC system is scarce. This paper details the design, implementation and testing of a user-friendly, remote and autonomous test bed to acquire measured data through an IoT platform, and to control ACs in real time through MATLAB Thingspeak. Measurement and data acquisition equipment are installed in a two-zone concrete building in Mauritius. MPC of the indoor air temperature achieved an AC temperature setpoint tracking RMSE which was 0.7°C lower than that achieved by the built-in ON/OFF AC control. The test bed also revealed that portable air-conditioners are not very efficient, given that the maximum cooling efficiency achieved in this work was only 60%. It also provided valuable insights based on the experiments carried out, in terms of improvements to sensing and data acquisition. Control engineers can implement such a test bed for the development and application of advanced controllers as per their needs and applications.</p>\u0000 </div>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.232","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142861570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Efficient parameter estimation for second order plus dead time systems in process plant control","authors":"Mahua Pal,&nbsp;Kumardeb Banerjee,&nbsp;Bivas Dam","doi":"10.1002/adc2.229","DOIUrl":"10.1002/adc2.229","url":null,"abstract":"&lt;p&gt;Designing a controller for a process plant typically modeled as a first or second-order system with dead time involves an efficient and accurate estimation of its parameters. Since many process plants are characterized as second-order plus dead time (SOPDT) overdamped or critically damped systems, this study presents a straightforward parameter estimation method using transient response data from a step input at three specific time instants. Two-time domain performance indices (PIs), &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;T&lt;/mi&gt;\u0000 &lt;mi&gt;R&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; (= &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mfrac&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;90&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mfrac&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; for system dead time = 0 and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;mfrac&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;90&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;5&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mo&gt;−&lt;/mo&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;5&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;mspace&gt;&lt;/mspace&gt;\u0000 &lt;/mrow&gt;\u0000 &lt;/mfrac&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; for system dead time ≠ 0; &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;5&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;, &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;10&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mn&gt;90&lt;/mn&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; are respectively the times at which the response reaches 5%, 10% and 90% of the steady-state response) and &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;f&lt;/mi&gt;\u0000 &lt;mi&gt;r&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt; (reciprocal of rise time &lt;span&gt;&lt;/span&gt;&lt;math&gt;\u0000 &lt;mrow&gt;\u0000 &lt;msub&gt;\u0000 &lt;mi&gt;t&lt;/mi&gt;\u0000 &lt;mi&gt;r&lt;/mi&gt;\u0000 &lt;/msub&gt;\u0000 &lt;/mrow&gt;&lt;/math&gt;) are proposed in this work. Correlations are established between these PIs and the pa","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.229","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141828816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal installation of DG in radial distribution network using arithmetic optimization algorithm","authors":"Indrajit Dey,&nbsp;Provas Kumar Roy","doi":"10.1002/adc2.227","DOIUrl":"10.1002/adc2.227","url":null,"abstract":"<p>The purpose of this work is an arrangement of distributed generation (DG) in radial distribution networks (RDNs) in an adequate way. An efficient method, named arithmetic optimization algorithm (AOA) is used for that purpose. The intention for effective DG posting is to decrease the power loss and upgrade the voltage shape and voltage steadiness magnification in RDNs. The demonstration of the suggested AOA method has been made on 33-bus, 69-bus, 85-bus, and 118-bus RDNs for optimum orientation and capacity of DGs with distinct power factors (unity, fixed, and optimal). By using this projected technique, the execution of RDNs is improved with respect to voltage stability maximization, voltage fluctuation mitigation, and also reduction of real power loss. The AOA method which is recommended here, grants a better solution than several optimization techniques found in the literature. This recommended AOA technique provides the percentage improvement of power loss for case 1 to case 3 (65.50%, 86.48%, and 94.43%), (69.16%, 90.80%, and 98.10%), (44.57%, 66.61%, and 80.26%), and (60.34%, 88.80%, and 90.31%) for 33, 69, 85, and 118-bus systems, respectively. The percentage improvement in voltage deviation minimization for case 1 to case 3 are (99.53%, 99.83%, and 99.84%), (99.88%, 99.91%, and 99.92%), and (97.53%, 98.98%, and 99.16%) for 33, 69, and 118-bus systems, respectively. For different test systems (33, 69, and 118-bus) improvements in voltage stability index maximization for case 1 to case 3 are (31.33%, 31.80%, and 31.81%), (30.15%, 31.25%, and 31.25%), and (37.78%, 39.23%, and 40.88%), respectively.</p>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.227","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141641234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"To cascade feedback loops, or not?","authors":"Eduard Eitelberg","doi":"10.1002/adc2.228","DOIUrl":"10.1002/adc2.228","url":null,"abstract":"<p>Linear time invariant (LTI) block diagrams—and the associated transfer functions—are profoundly inadequate for multi-loop control system design. A practitioner has to have a thorough understanding of the physical uncertainties—and of their inter-dependencies—in the different parts of an interconnected system, or in a given block diagram. Lack of attention to, or understanding of, such causal interactions has led to ill-advised reliance on cascaded control in practice—and to consternation when cascading fails to yield the expected improvement over a single-loop design.</p>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.228","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel modulation for four-switch Buck-boost converter to eliminate the right half plane zero point","authors":"Xiaoyan Yuan,&nbsp;Kun Wang,&nbsp;Zhengtao Yang,&nbsp;Huafeng Cao","doi":"10.1002/adc2.223","DOIUrl":"https://doi.org/10.1002/adc2.223","url":null,"abstract":"<p>The four-switch Buck-Boost (FSBB) converter are widely used in combination with other isolated converter to extend the voltage range capability of the overall structure. When the converter operates in buck-boost mode and boost mode, it exhibits a right half plane zero (RHPZ) in the control to output transfer function. This characteristic would cause negative impact to stability of the converter. In order to eliminate the RHPZ, a novel modulation method is proposed in this paper. The buck mode is introduced to the modulation to adjust the voltage gain, and the corresponding average state space modeling for the FSBB with the proposed modulation is established. The simulation of the converter with the proposed modulation method and traditional modulation are presented. Finally, experiment results by hardware in the loop (HIL) platform is employed to verity the correctness of theoretical analysis results.</p>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.223","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and comparison of particle swarm optimization tuned Kalman filter based linear quadratic Gaussian controller and linear quadratic regulator for surface to air missile guidance system","authors":"Girma Kassa Alitasb,&nbsp;Getasew Mekonnen Beyene,&nbsp;Ayodeji Olalekan Salau","doi":"10.1002/adc2.226","DOIUrl":"https://doi.org/10.1002/adc2.226","url":null,"abstract":"<p>The study of missile guidance systems is a well-known nonlinear control engineering area of research. To enhance the control performance of a missle guidance system, several technologies have been proposed in existing works. To resolve the weighting matrix selection issue of a linear quadratic Gaussian (LQG) controller for the surface-to-air missile guidance control system, this study utilizes the particle swarm optimization (PSO) technique. Selecting the best state (Q) and input (R) weighting matrices is a significant difficulty in the design of the LQG controller for real-time applications since it affects the controller's performance and optimality. The weighting matrices are often chosen by a trial-and-error method that not only complicates the design but also does not yield optimal outcomes. Therefore, in this paper, a PSO method is developed and used in the design of the linear quadratic regulator (LQR) and LQG controllers for the surface-to-air missile control system to choose the elements of the Q and R matrices in the best possible way. Finally, a comparative analysis between the designed controllers was presented. The results shows that a good performance was achieved by using the proposed PSO-tuned design process. The LQG and LQR are designed by manually adjusting the weighting matrices and utilizing an intelligent procedure, PSO algorithm which achieved optimal results. Further results indicate that the designed controllers, the PSO tuned LQR and LQG achieved a better performance over the manually adjusted LQR and LQG controllers.</p>","PeriodicalId":100030,"journal":{"name":"Advanced Control for Applications","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/adc2.226","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142160205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}