IFAC Journal of Systems and Control最新文献

{"title":"A generalized Routh–Hurwitz criterion for the stability analysis of polynomials with complex coefficients: Application to the PI-control of vibrating structures","authors":"Anthony Hastir ,&nbsp;Riccardo Muolo","doi":"10.1016/j.ifacsc.2023.100235","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100235","url":null,"abstract":"<div><p>The Routh–Hurwitz criterion is one of the most popular methods to study the stability of polynomials with real coefficients<span>, given its simplicity and ductility. However, when moving to polynomials with complex coefficients, some generalization exist but are either incorrect or inapplicable to most practical cases. To fill this gap, we hereby propose a directed generalization of the criterion to the case of complex polynomials, broken down in an algorithmic form, so that the method is now easily accessible and ready to be applied. Then, we demonstrate its use to determine the external stability of a system consisting of the interconnection between a rotating shaft and a PI-regulator, obtaining the necessary and sufficient conditions to achieve stabilization of the system.</span></p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100235"},"PeriodicalIF":1.9,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134656016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimentally validated frequency shifted internal model cascade control strategy for magnetic levitation system","authors":"Arunima Sagar ,&nbsp;Rahul Radhakrishnan ,&nbsp;G. Lloyds Raja","doi":"10.1016/j.ifacsc.2023.100234","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100234","url":null,"abstract":"<div><p><span>Magnetic levitation<span><span> systems (MLS) provide friction-less, dependable, quick, and affordable operations in a variety of real life applications. One of the often-employed control strategies for the MLS is traditional cascade control, which uses </span>internal model control (IMC)-based proportional–integral–derivative (PID) and proportional–integral (PI) controllers in its primary and secondary loops, respectively. Though this control structure succeeds in achieving levitation, it falls short in terms of set point tracking and disturbance rejection performance. To overcome this limitation, a bi-loop frequency shifted IMC proportional–derivative (FSIMC-PD) strategy is used in the primary loop retaining the conventional IMC-based PI controller in the secondary loop. Routh stability constraints are used to build the PD controller for stabilizing the MLS. Once the MLS is stabilized, an FSIMC-based </span></span>PID controller<span> for reference tracking is designed for the outer loop. In addition to simulation-based performance comparison of IMC-based PID-PI cascade scheme and the proposed scheme, experimental validation is also carried out on a laboratory scaled MLS setup. Furthermore, performance evaluation based on metrics like the integral of absolute error, integral of square error, integral of time weighted absolute error, total variation of the control signal and its maximum value are also carried out to vindicate the effectiveness of the suggested design. Robust stability analysis is carried out in addition to Nyquist stability considerations to vindicate that the FSIMC-based design is capable of yielding stable closed-loop response amid uncertainties in plant model parameters.</span></p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100234"},"PeriodicalIF":1.9,"publicationDate":"2023-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"92043306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Addition and intersection of linear time-invariant behaviors","authors":"Antonio Fazzi ,&nbsp;Ivan Markovsky","doi":"10.1016/j.ifacsc.2023.100233","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100233","url":null,"abstract":"<div><p>We define and analyze the operations of addition and intersection of linear time-invariant systems in the behavioral setting, where systems are viewed as sets of trajectories rather than input–output maps. The classical definition of addition of input–output systems is addition of the outputs with the inputs being equal. In the behavioral setting, addition of systems is defined as addition of all variables. Intersection of linear time-invariant systems was considered before only for the autonomous case in the context of “common dynamics” estimation. We generalize the notion of common dynamics to open systems (systems with inputs) as intersection of behaviors. This is done by proposing trajectory-based definitions. The main results of the paper are (1) characterization of the link between the complexities (number of inputs and order) of the sum and intersection systems, (2) algorithms for computing their kernel and image representations and (3) a duality property of the two operations. Our approach combines polynomial and numerical linear algebra computations.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100233"},"PeriodicalIF":1.9,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49745263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Observer based stabilization of linear time delay systems using new augmented LKF","authors":"V. Dev. Deepak,&nbsp;N.K. Arun,&nbsp;K.V. Shihabudheen","doi":"10.1016/j.ifacsc.2023.100231","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100231","url":null,"abstract":"<div><p><span>This paper addresses the stabilization problem of linear time-varying delay systems with unmeasurable states. A novel augmented Lyapunov–Krasovskii functional (LKF) is proposed that effectively accounts for the impact of time delays<span>, and an observer based stabilization controller is developed employing linear matrix inequality (LMI) based optimization technique. The utilization of extended reciprocally convex matrix inequality (ERCMI) is employed in this work to establish less conservative stabilization conditions within the framework of linear matrix inequalities (LMIs). By formulating a </span></span>convex optimization<span> problem, the observer gain and controller gains are determined. Simulation results are used to validate the design, and two numerical examples are considered to prove the usefulness of the proposed method over existing methods.</span></p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100231"},"PeriodicalIF":1.9,"publicationDate":"2023-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49745292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hierarchical perturbation compensation system with ERL sliding mode controller in a quadrotor","authors":"Walid Alqaisi ,&nbsp;Brahim Brahmi ,&nbsp;Jawhar Ghommam ,&nbsp;Maarouf Saad ,&nbsp;Vahé Nerguizian","doi":"10.1016/j.ifacsc.2023.100232","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100232","url":null,"abstract":"<div><p><span>This article addresses the problem of perturbation in Unmanned Air Vehicle (UAV) quadrotors. Three subsystems are designed to provide a continuous and precise estimation of perturbation and residual perturbation. The three subsystems form a Hierarchical Perturbation Compensator (HPC), which is built to compensate for system dynamics<span><span> uncertainties, non-modeled dynamics, and external disturbances. The </span>nonlinear control Exponential Reaching Law Sliding Mode (ERLSM) is utilized with the HPC. </span></span>Lyapunov stability analysis proves the stability of the entire compensator-controller system. This system has the ability to decrease unknown perturbation either external or internal. It also has the ability to maintain full control of the six-degree-of-freedom quadrotor. The system performance for position, altitude, and attitude control is demonstrated by analysis, simulation, and experiments.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100232"},"PeriodicalIF":1.9,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49745268","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive neural dynamic surface control of load/grid connected voltage source inverters with LC/LCL filters","authors":"Sajjad Shoja-Majidabad ,&nbsp;Majid Moradi Zirkohi","doi":"10.1016/j.ifacsc.2023.100230","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100230","url":null,"abstract":"<div><p><span><span>Utilizing passive filters<span> such as L, LC and LCL is preferred to cancel out high-frequency harmonics caused by pulse width modulation of voltage source </span></span>inverters<span>. However, the LC and LCL filters have shown better harmonic attenuation than the conventional L filter. Nevertheless, the control process of LC and LCL filters is more complicated due to their higher-order dynamics. The problem gets more challenging in the presence of uncertainties such as load and grid impedance variations. To overcome these challenges, two novel adaptive neural dynamic surface controllers are proposed for LC and LCL filters in the load and grid-connected modes, respectively. Meanwhile, the issue of </span></span>computational complexity<span> inherent in the conventional backstepping method is avoided here by utilizing the dynamic surface control<span> technique. Furthermore, the matched and unmatched uncertainties of LC/LCL filters are approximated via multi-input multi-output radial basis function<span> neural networks. Stability of the closed-loop systems is guaranteed by converging the tracking errors to a small neighborhood of the origin. Simulations are given to illustrate the effectiveness and potential of the proposed adaptive neural dynamic surface control methods under the load and grid impedance changes.</span></span></span></p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100230"},"PeriodicalIF":1.9,"publicationDate":"2023-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49767071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective control and optimization of a stand-alone photovoltaic power conversion system with battery storage energy management","authors":"Ghizlane Traiki,&nbsp;Abdelmounime El Magri,&nbsp;Rachid Lajouad,&nbsp;Omar Bouattane","doi":"10.1016/j.ifacsc.2023.100227","DOIUrl":"10.1016/j.ifacsc.2023.100227","url":null,"abstract":"<div><p><span><span><span>This paper addresses the problem of controlling a stand-alone photovoltaic (PV) energy conversion </span>system integrated with a </span>battery energy storage system<span><span>. The study focuses on a series association of PV panels<span><span>, a DC/AC converter, a Li-ion battery, and a DC load. The intermittent nature of PV power and frequent variations in load demand decrease battery lifetime and its charging performance. To mitigate these issues, an efficient battery charge controller is proposed to instantaneously balance the PV power flow delivered to the DC load and the battery, ensuring optimal utilization of PV power and appropriate battery charging. Based on available solar power, battery state of charge (SOC), and DC load demand The controller adapts to three charging modes, namely, </span>maximum power point tracking (MPPT) charging mode, constant current (CC) charging mode, and constant voltage (CV) charging mode. Additionally, a novel </span></span>energy management<span><span> algorithm is designed to ensure battery safety and determine the system’s mode of operation, considering weather conditions and load demand variations. Interestingly, no solar irradiation or battery SOC sensors are required for the implementation of the control system. Nonlinear and robust controllers are developed to provide the necessary control input laws for the management algorithm. The robustness and stability of the system are verified using the </span>Lyapunov theory. Furthermore, the paper quantifies the performance of the proposed strategy through a comparative analysis using integral of absolute error (IAE) indices against two conventional control approaches. Simulation results validate the effectiveness of the proposed controller strategy, demonstrating its high performance and ability to meet the specified objectives. This work presents an innovative approach to enhance the efficiency and reliability of stand-alone PV energy conversion systems with battery storage, offering promising prospects for sustainable </span></span></span>energy applications.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100227"},"PeriodicalIF":1.9,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42547637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trajectory control of a hydraulic system using intelligent control approach based on adaptive prediction model","authors":"Dao Thanh Liem","doi":"10.1016/j.ifacsc.2023.100228","DOIUrl":"10.1016/j.ifacsc.2023.100228","url":null,"abstract":"<div><p><span>Electro-hydraulic actuators (EHAs) have become a preferred alternative to traditional hydraulic actuators with valve control systems due to their numerous advantages, making them an ideal choice for applications requiring high-precision force or position control. However, the highly complex nonlinear nature of EHAs makes modelling and controlling them a challenging task. To address this challenge, a new position control approach has been proposed for an EHA system<span><span> using a combination of a feedforward<span> online-tuning PID (FOPID) controller and an adaptive grey predictor (AGP), known as the feedforward online-tuning adaptive grey predictor (FOAGP). The FOPID controller is constructed based on PID controller and fuzzy logic algorithm to control the EHA system towards referred trajectory, while an updating rule that consists of robust checking terms optimizes its parameters online to minimize control error. The AGP predictor is an important aspect of the proposed approach. It consists of a self-tuning step size mechanism, which estimates the performance of the plant to tune the parameters of the controller and create an additive control signal that is used to counteract environment noises and perturbations. This approach significantly improves control performance by reducing the effect of disturbances and sensor noises on the system. The FOAGP approach was tested in simulation to investigate its effectiveness. The results showed that the proposed approach outperformed other existing control methods, with a higher accuracy and better control performance. One of the significant advantages of the FOAGP approach is its ability to learn and adapt to changing </span></span>system dynamics. The learning mechanism used in the FOPID controller allows the system to optimize its parameters online, which is especially useful in systems with varying operating conditions. The AGP predictor also continuously adjusts its parameters to accurately estimate the system output, making it an effective tool for controlling EHAs. The proposed approach offers a significant improvement in control performance, making it a better alternative to traditional control methods. This approach can be applied to various EHA systems, including those used in aerospace, automobile, and </span></span>robotic applications, among others.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100228"},"PeriodicalIF":1.9,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41320156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-based versus model-free feeding control and water-quality monitoring for fish-growth tracking in aquaculture systems","authors":"Fahad Aljehani ,&nbsp;Ibrahima N’Doye ,&nbsp;Taous-Meriem Laleg-Kirati","doi":"10.1016/j.ifacsc.2023.100226","DOIUrl":"https://doi.org/10.1016/j.ifacsc.2023.100226","url":null,"abstract":"<div><p><span>This paper proposes model-based and model-free control approaches to monitor the feeding rate and water quality for fish-growth tracking in aquaculture systems. The representative fish-growth model is revisited, which describes the total biomass change by incorporating the fish population density and mortality. Due to the challenging task of measuring the total fish biomass and population data, the new dynamic population model is validated with individual fish-growth data for </span>tracking control<span>. Ammonia exposure is a significant challenge in the fish-population growth tracking problem, affecting fish health and survival. To address this challenge, traditional and optimal controllers are first designed to track the weight reference within suboptimal temperature and dissolved oxygen (DO) profiles under various un-ionized ammonia (UIA) exposure levels by manipulating relative feeding. Then, a Q-learning approach is proposed to learn an optimal feeding-control policy from simulated data on fish-growth weight trajectories while managing ammonia effects. The proposed Q-learning feeding control prevents fish mortality and achieves good tracking errors for fish weight under UIA levels. However, it maintains a relative food consumption that potentially underfeeds fish. Finally, an optimal predictive algorithm that includes the temperature, DO, and UIA is proposed to optimize the feeding and water quality of the dynamic fish-population growth process, indicating that fish mortality is decreased and food consumption is reduced in all cases of UIA exposure.</span></p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"26 ","pages":"Article 100226"},"PeriodicalIF":1.9,"publicationDate":"2023-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49764245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation on the stability of networked-control integrated energy systems for frequency regulations","authors":"Manikandan S.","doi":"10.1016/j.ifacsc.2023.100219","DOIUrl":"10.1016/j.ifacsc.2023.100219","url":null,"abstract":"<div><p><span>This paper presents the stability analysis of integrated energy systems<span> under network environment. The networked-control integrated energy systems involve time-delay in the control loop. These time-delays are time-invariant or time-varying in nature. Further, it affects the stability and dynamic performance of the integrated energy systems. In this paper stability analysis of networked-control integrated energy systems are done using Lyapunov–Krasovskii functional and linear matrix inequality techniques. The maximum amount of time-delay that establishes the stability of the integrated energy systems is determined and controller is designed with concern to the time-delay. The effect of electric vehicles and </span></span>battery energy storage system in stability delay margins of integrated energy systems is also addressed and the numerical simulations are done to verify the effectiveness of the presented results.</p></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"25 ","pages":"Article 100219"},"PeriodicalIF":1.9,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44763134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}