Pub Date : 2025-06-16DOI: 10.1016/j.ifacsc.2025.100320
Georg Stettinger , Patrick Weissensteiner , Nayel Fabian Salem , Marcus Nolte , Siddartha Khastgir
This paper presents a comprehensive impact assessment to explore the potential benefits of harmonized behaviour competencies (BC) for automated driving systems (ADS). Typically, ADS-equipped vehicles operate within certain boundaries specified by an operational design domain (ODD), utilizing the relevant implemented BCs. Nonetheless, many regulatory and standardization-relevant documents employ BC attributes in a non-harmonized manner. The study delves into BC-related activities and applications throughout the entire ADS life cycle, affecting all aspects of the ADS value chain, to gain a deeper understanding of the diverse needs of various stakeholders. BCs are linked to one of the four primary requirement sources at the system level. ADS-related BCs are defined through a multidisciplinary approach driven by their underlying core operating principle: the well-known sense-plan-act cycle. The crucial element within the BC specification is the identified manoeuvre pool, which forms the basis for implementing any route from point A to point B. The individual manoeuvres within the manoeuvre pool are defined by considering the needs of multiple stakeholders. They are based on three essential components: the initial condition, the expected manoeuvre, and the final condition. Furthermore, trustworthy behaviour competencies are specified, encompassing three pillars: robustness, ethics, and lawfulness. Following a detailed stakeholder analysis, several related applications are discussed to highlight the concrete advantages of implementing standardized BCs. The study concludes with a summary of the impact analysis, emphasizing key findings and action points. Lastly, a roadmap is proposed to integrate trustworthy BCs into future ADS. Concretely, the authors developed the following innovations within the scope of this article: (1) Concept for trustworthy behaviour competencies driven by law, ethics, and robustness. (2) Robustness is defined as passenger & ODD awareness and plannable & executable manoeuvre. (3) Manoeuvre pool necessary to implement an arbitrary route from point A to point B. (4) Manoeuvre specification via initial condition, expected behaviour, and final condition. (5) The potential benefits of harmonized behaviour competencies drive impact assessment.
{"title":"Exploring the potential of standardized behaviour competencies in automated driving systems","authors":"Georg Stettinger , Patrick Weissensteiner , Nayel Fabian Salem , Marcus Nolte , Siddartha Khastgir","doi":"10.1016/j.ifacsc.2025.100320","DOIUrl":"10.1016/j.ifacsc.2025.100320","url":null,"abstract":"<div><div>This paper presents a comprehensive impact assessment to explore the potential benefits of harmonized behaviour competencies (BC) for automated driving systems (ADS). Typically, ADS-equipped vehicles operate within certain boundaries specified by an operational design domain (ODD), utilizing the relevant implemented BCs. Nonetheless, many regulatory and standardization-relevant documents employ BC attributes in a non-harmonized manner. The study delves into BC-related activities and applications throughout the entire ADS life cycle, affecting all aspects of the ADS value chain, to gain a deeper understanding of the diverse needs of various stakeholders. BCs are linked to one of the four primary requirement sources at the system level. ADS-related BCs are defined through a multidisciplinary approach driven by their underlying core operating principle: the well-known sense-plan-act cycle. The crucial element within the BC specification is the identified manoeuvre pool, which forms the basis for implementing any route from point A to point B. The individual manoeuvres within the manoeuvre pool are defined by considering the needs of multiple stakeholders. They are based on three essential components: the initial condition, the expected manoeuvre, and the final condition. Furthermore, trustworthy behaviour competencies are specified, encompassing three pillars: robustness, ethics, and lawfulness. Following a detailed stakeholder analysis, several related applications are discussed to highlight the concrete advantages of implementing standardized BCs. The study concludes with a summary of the impact analysis, emphasizing key findings and action points. Lastly, a roadmap is proposed to integrate trustworthy BCs into future ADS. Concretely, the authors developed the following innovations within the scope of this article: (1) Concept for trustworthy behaviour competencies driven by law, ethics, and robustness. (2) Robustness is defined as passenger & ODD awareness and plannable & executable manoeuvre. (3) Manoeuvre pool necessary to implement an arbitrary route from point A to point B. (4) Manoeuvre specification via initial condition, expected behaviour, and final condition. (5) The potential benefits of harmonized behaviour competencies drive impact assessment.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"33 ","pages":"Article 100320"},"PeriodicalIF":1.8,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313352","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}
Pub Date : 2025-06-10DOI: 10.1016/j.ifacsc.2025.100319
Md Akib Hasan , Md Showkot Hossain , Mohd Azrik Roslan , Azralmukmin Azmi , Leong Jenn Hwai , Ahmad Afif Nazib , Noor Syafawati Ahmad
The increasing integration of renewable energy sources has accelerated the adoption of microgrids, necessitating efficient power-sharing and control techniques for reliable operation. This study proposes an optimized droop control technique for parallel inverters in islanded AC microgrids, focusing on improving system efficiency. Conventional droop methods often encounter challenges in power-sharing accuracy under varying load conditions due to mismatched feeder impedances and differing power loss characteristics of distributed generators (DGs). To address these issues, the proposed method dynamically adjusts droop coefficients using Particle Swarm Optimization (PSO) to optimize power distribution, reduce circulating currents, and improve energy conversion efficiency while maintaining system modularity. A system-level microgrid efficiency model is designed to identify optimal operating points under diverse load profiles. Comparative analysis demonstrates that the proposed PSO-based controller consistently outperforms conventional droop methods, achieving system efficiency improvements ranging from 0.11% to 0.52% across various load conditions and power factors. Simulation results from PSIM and MATLAB/Simulink further highlight reduced circulating currents, enhanced energy conversion efficiency, and improved system stability. These findings underscore the potential of PSO-driven control as a scalable and communication-free solution for efficiency optimization in decentralized microgrids.
{"title":"Optimized droop control strategy for efficiency improvement in islanded AC microgrid","authors":"Md Akib Hasan , Md Showkot Hossain , Mohd Azrik Roslan , Azralmukmin Azmi , Leong Jenn Hwai , Ahmad Afif Nazib , Noor Syafawati Ahmad","doi":"10.1016/j.ifacsc.2025.100319","DOIUrl":"10.1016/j.ifacsc.2025.100319","url":null,"abstract":"<div><div>The increasing integration of renewable energy sources has accelerated the adoption of microgrids, necessitating efficient power-sharing and control techniques for reliable operation. This study proposes an optimized droop control technique for parallel inverters in islanded AC microgrids, focusing on improving system efficiency. Conventional droop methods often encounter challenges in power-sharing accuracy under varying load conditions due to mismatched feeder impedances and differing power loss characteristics of distributed generators (DGs). To address these issues, the proposed method dynamically adjusts droop coefficients using Particle Swarm Optimization (PSO) to optimize power distribution, reduce circulating currents, and improve energy conversion efficiency while maintaining system modularity. A system-level microgrid efficiency model is designed to identify optimal operating points under diverse load profiles. Comparative analysis demonstrates that the proposed PSO-based controller consistently outperforms conventional droop methods, achieving system efficiency improvements ranging from 0.11% to 0.52% across various load conditions and power factors. Simulation results from PSIM and MATLAB/Simulink further highlight reduced circulating currents, enhanced energy conversion efficiency, and improved system stability. These findings underscore the potential of PSO-driven control as a scalable and communication-free solution for efficiency optimization in decentralized microgrids.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"33 ","pages":"Article 100319"},"PeriodicalIF":1.8,"publicationDate":"2025-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144587719","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}
Pub Date : 2025-06-07DOI: 10.1016/j.ifacsc.2025.100318
Chenxuan Sheng , Guobao Liu , Huai Liu , Siyu Xia
This paper focuses on the issue of adaptive fuzzy control for nonlinear systems with actuator faults and unknown control directions. Command filtering techniques are integrated with the Nussbaum function to address the issue of complexity explosion and to compensate for the effects of unknown control directions. This approach effectively compensates for filtering errors. In the presence of actuator faults and disturbances, an actuator fault compensation auxiliary system is designed to resolve the signal mismatch between the controller and the actuator. By utilizing Lyapunov stability theory and backstepping control methods, it is proven that the tracking error can ultimately converge to a small neighborhood near the origin. Furthermore, in accordance with the control design, all signals within the system remain bounded. Finally, the effectiveness of this control strategy can be validated through simulations of a circuit containing a nonlinear controlled source and nonlinear pendulum model.
{"title":"Adaptive command-filtered control for nonlinear systems with actuator faults and unknown control directions","authors":"Chenxuan Sheng , Guobao Liu , Huai Liu , Siyu Xia","doi":"10.1016/j.ifacsc.2025.100318","DOIUrl":"10.1016/j.ifacsc.2025.100318","url":null,"abstract":"<div><div>This paper focuses on the issue of adaptive fuzzy control for nonlinear systems with actuator faults and unknown control directions. Command filtering techniques are integrated with the Nussbaum function to address the issue of complexity explosion and to compensate for the effects of unknown control directions. This approach effectively compensates for filtering errors. In the presence of actuator faults and disturbances, an actuator fault compensation auxiliary system is designed to resolve the signal mismatch between the controller and the actuator. By utilizing Lyapunov stability theory and backstepping control methods, it is proven that the tracking error can ultimately converge to a small neighborhood near the origin. Furthermore, in accordance with the control design, all signals within the system remain bounded. Finally, the effectiveness of this control strategy can be validated through simulations of a circuit containing a nonlinear controlled source and nonlinear pendulum model.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"33 ","pages":"Article 100318"},"PeriodicalIF":1.8,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313353","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}
Air pollution affects 91% of the global population, causing approximately 4.2 million deaths annually, according to the World Health Organization. This study presents a comprehensive analysis of spatiotemporal air quality patterns in Ghaziabad, focusing on seasonal variations, aerosol characteristics, correlation analysis, machine learning-based modelling, sensitivity analysis, and short-term prediction of PM and PM10 concentrations using data from four monitoring stations (MS1, MS2, MS3, MS4). Alarming levels of PM10 and PM, frequently exceeding permissible standards, were observed, particularly at MS2, where industrial activities led to an 81.29% exceedance rate for PM10 with a maximum concentration increase of 447.23%. PM concentrations at MS2 reached /m3, representing a 501.55% increase. Meteorological circumstances, particularly during winter, significantly increased pollution levels. SO2 and ozone concentrations adhered to CPCB (Central Pollution Control Board) guidelines; nonetheless, winter months experienced a significant increase in overall pollutant levels. Positive correlations were identified between PM and PM10 with NO2 (r 0.54, r 0.51), CO (r 0.51, r 0.45), and SO2 (r 0.18, r 0.34), while negative correlations were noted with ozone (r −0.02, r −0.18), wind speed (r −0.17, r −0.20), and relative humidity (r −0.08, r −0.37). Solar radiation also showed a negative correlation (r −0.32, r −0.13). The study optimized predictive models for air quality forecasting using historical data. The XGBoost model outperformed others in predicting PM and PM10 concentrations, achieving the lowest Mean Absolute Error (MAE) and highest R2 values (PM: MAE /m
世界卫生组织（World Health Organization）的数据显示，全球91%的人口受到空气污染的影响，每年造成约420万人死亡。本研究对加兹阿巴德的时空空气质量模式进行了全面分析，重点关注季节变化、气溶胶特征、相关性分析、基于机器学习的建模、敏感性分析，并利用四个监测站（MS1、MS2、MS3、MS4）的数据对PM2.5和PM10浓度进行了短期预测。PM10和PM2.5的警戒水平经常超过允许的标准，特别是在MS2，工业活动导致PM10超标率为81.29%，最大浓度增加了447.23%。PM2.5浓度达到360.93μg/m3，增长501.55%。气象环境，特别是冬季，大大增加了污染程度。二氧化硫和臭氧浓度符合中央污染控制委员会（CPCB）的准则；尽管如此，冬季的几个月总体污染物水平显著上升。PM2.5和PM10与NO2 （r = 0.54, r = 0.51）、CO （r = 0.51, r = 0.45）、SO2 （r = 0.18, r = 0.34）呈显著正相关，与臭氧（r = - 0.02, r = - 0.18）、风速（r = - 0.17, r = - 0.20）、相对湿度（r = - 0.08, r = - 0.37）呈显著负相关。太阳辐射也呈负相关（r = - 0.32, r = - 0.13）。该研究优化了利用历史数据预测空气质量的预测模型。XGBoost模型在预测PM2.5和PM10浓度方面优于其他模型，平均绝对误差（MAE）最低，R2最高（PM2.5: MAE 13.24μg/m3, R2 0.8960, PM10: MAE 27.46μg/m3, R2 0.8397）。灵敏度分析发现，PM10浓度对PM2.5水平的影响最大，对模型预测能力的贡献率约为63.56%，其次是太阳辐射（9.74%）和相对湿度（8.30%）。该模型准确预测了2023年的空气质量，具有较高的可靠性（2023年PM2.5: MAE 14.64μg/m3, R2 0.8850, PM10: MAE 27.66μg/m3, R2 0.8234）。这些可靠的短期预报对公共卫生规划和环境管理至关重要，有助于采取主动措施减轻污染水平，保障公众健康。可靠的预测有助于采取有针对性的行动，支持减少空气污染及其对人口的不利影响的政策决定。
{"title":"Air quality analysis and modelling of particulate matter (PM2.5 and PM10) of Ghaziabad city in India using Artificial Intelligence techniques","authors":"Patil Aashish Suhas, Aneesh Mathew, Chinthu Naresh","doi":"10.1016/j.ifacsc.2025.100315","DOIUrl":"10.1016/j.ifacsc.2025.100315","url":null,"abstract":"<div><div>Air pollution affects 91% of the global population, causing approximately 4.2 million deaths annually, according to the World Health Organization. This study presents a comprehensive analysis of spatiotemporal air quality patterns in Ghaziabad, focusing on seasonal variations, aerosol characteristics, correlation analysis, machine learning-based modelling, sensitivity analysis, and short-term prediction of PM<span><math><msub><mrow></mrow><mrow><mi>2.5</mi></mrow></msub></math></span> and PM<sub>10</sub> concentrations using data from four monitoring stations (MS1, MS2, MS3, MS4). Alarming levels of PM<sub>10</sub> and PM<span><math><msub><mrow></mrow><mrow><mi>2.5</mi></mrow></msub></math></span>, frequently exceeding permissible standards, were observed, particularly at MS2, where industrial activities led to an 81.29% exceedance rate for PM<sub>10</sub> with a maximum concentration increase of 447.23%. PM<span><math><msub><mrow></mrow><mrow><mi>2.5</mi></mrow></msub></math></span> concentrations at MS2 reached <span><math><mrow><mn>360</mn><mo>.</mo><mn>93</mn><mspace></mspace><mi>μ</mi><mi>g</mi></mrow></math></span>/m<sup>3</sup>, representing a 501.55% increase. Meteorological circumstances, particularly during winter, significantly increased pollution levels. SO<sub>2</sub> and ozone concentrations adhered to CPCB (Central Pollution Control Board) guidelines; nonetheless, winter months experienced a significant increase in overall pollutant levels. Positive correlations were identified between PM<span><math><msub><mrow></mrow><mrow><mi>2.5</mi></mrow></msub></math></span> and PM<sub>10</sub> with NO<sub>2</sub> (r <span><math><mo>=</mo></math></span> 0.54, r <span><math><mo>=</mo></math></span> 0.51), CO (r <span><math><mo>=</mo></math></span> 0.51, r <span><math><mo>=</mo></math></span> 0.45), and SO<sub>2</sub> (r <span><math><mo>=</mo></math></span> 0.18, r <span><math><mo>=</mo></math></span> 0.34), while negative correlations were noted with ozone (r <span><math><mo>=</mo></math></span> −0.02, r <span><math><mo>=</mo></math></span> −0.18), wind speed (r <span><math><mo>=</mo></math></span> −0.17, r <span><math><mo>=</mo></math></span> −0.20), and relative humidity (r <span><math><mo>=</mo></math></span> −0.08, r <span><math><mo>=</mo></math></span> −0.37). Solar radiation also showed a negative correlation (r <span><math><mo>=</mo></math></span> −0.32, r <span><math><mo>=</mo></math></span> −0.13). The study optimized predictive models for air quality forecasting using historical data. The XGBoost model outperformed others in predicting PM<span><math><msub><mrow></mrow><mrow><mi>2.5</mi></mrow></msub></math></span> and PM<sub>10</sub> concentrations, achieving the lowest Mean Absolute Error (MAE) and highest R<sup>2</sup> values (PM<span><math><msub><mrow></mrow><mrow><mi>2.5</mi></mrow></msub></math></span>: MAE <span><math><mrow><mn>13</mn><mo>.</mo><mn>24</mn><mspace></mspace><mi>μ</mi><mi>g</mi></mrow></math></span>/m<su","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100315"},"PeriodicalIF":1.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144204247","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}
In this paper, we propose a bottom-up approach for designing sparse static output-feedback controllers for large-scale systems. Starting from an existing sparse controller, we iteratively add feedback channels using a gradient-based predictor, optimizing the closed-loop norm within a predefined budget constraint. The proposed method significantly reduces the computational burden compared to traditional top-down approaches, which rely on pruning centralized controllers. We prove the convergence of our method and demonstrate its scalability through benchmarks, achieving comparable or better performance with significantly less computation time. This approach paves the way for efficient and scalable control design in distributed systems.
{"title":"A bottom-up approach for searching for sparse controllers with a budget","authors":"Vasanth Reddy , Suat Gumussoy , Almuatazbellah Boker , Hoda Eldardiry","doi":"10.1016/j.ifacsc.2025.100308","DOIUrl":"10.1016/j.ifacsc.2025.100308","url":null,"abstract":"<div><div>In this paper, we propose a bottom-up approach for designing sparse static output-feedback controllers for large-scale systems. Starting from an existing sparse controller, we iteratively add feedback channels using a gradient-based predictor, optimizing the closed-loop <span><math><mrow><msub><mrow><mi>H</mi></mrow><mrow><mn>2</mn></mrow></msub><mo>−</mo></mrow></math></span>norm within a predefined budget constraint. The proposed method significantly reduces the computational burden compared to traditional top-down approaches, which rely on pruning centralized controllers. We prove the convergence of our method and demonstrate its scalability through benchmarks, achieving comparable or better performance with significantly less computation time. This approach paves the way for efficient and scalable control design in distributed systems.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100308"},"PeriodicalIF":1.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144189379","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}
Pub Date : 2025-06-01DOI: 10.1016/j.ifacsc.2025.100317
Eugenia Villa , Oriana Guagliardi , Valentina Breschi , Mara Tanelli
The urgency of implementing effective policies to foster the energy transition and mitigate the devastating effects of climate change is undeniable. Nonetheless, the success of these policies is also closely intertwined with the necessity of preserving a delicate social balance when allocating resources toward a widespread transition. In response to this issue, we propose to adopt the recently proposed Fair-MPC scheme to introduce a control-oriented framework to aid policymakers in designing sustainability policies that are both effective and fair and evaluating existing policies by looking at these two key facets of sustainable technology diffusion. The modular design of our tool enables the assessment of fairness objectives integrated within the policy design strategy, striking a balance between impartial equality and inclusive equity with the imperative of cost minimization and effective diffusion of the transition process. Meanwhile, the flexibility of the framework makes it applicable to various scenarios, potentially representing a key tool in supporting all sectors involved in the energy transition. In this work, we prove its usability through its data-driven application in the context of the green mobility transition. Our analyses reveal that pursuing fairness objectives leads to a decrease (even if minor) in diffusion performance, underscoring the delicate balance between these frequently conflicting goals and highlighting the necessity of having quantitative tools to navigate the complexities characterizing social contexts.
{"title":"Fair closed-loop policies for fostering the energy transition: A control-oriented approach","authors":"Eugenia Villa , Oriana Guagliardi , Valentina Breschi , Mara Tanelli","doi":"10.1016/j.ifacsc.2025.100317","DOIUrl":"10.1016/j.ifacsc.2025.100317","url":null,"abstract":"<div><div>The urgency of implementing effective policies to foster the energy transition and mitigate the devastating effects of climate change is undeniable. Nonetheless, the success of these policies is also closely intertwined with the necessity of preserving a delicate social balance when allocating resources toward a widespread transition. In response to this issue, we propose to adopt the recently proposed Fair-MPC scheme to introduce a control-oriented framework to aid policymakers in designing sustainability policies that are both effective and fair and evaluating existing policies by looking at these two key facets of sustainable technology diffusion. The modular design of our tool enables the assessment of fairness objectives integrated within the policy design strategy, striking a balance between impartial <em>equality</em> and inclusive <em>equity</em> with the imperative of cost minimization and effective diffusion of the transition process. Meanwhile, the flexibility of the framework makes it applicable to various scenarios, potentially representing a key tool in supporting all sectors involved in the energy transition. In this work, we prove its usability through its data-driven application in the context of the green mobility transition. Our analyses reveal that pursuing fairness objectives leads to a decrease (even if minor) in diffusion performance, underscoring the delicate balance between these frequently conflicting goals and highlighting the necessity of having quantitative tools to navigate the complexities characterizing social contexts.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100317"},"PeriodicalIF":1.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230521","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}
Pub Date : 2025-06-01DOI: 10.1016/j.ifacsc.2025.100316
Yoshihiro Iwanaga , Yasutaka Fujimoto
Motion planning for wheeled systems is crucial for enabling efficient automation in applications such as automobiles, wheeled construction machinery, and forklifts. In particular, when operating in cluttered environments, there has been growing interest in methods that utilize sampling-based techniques for coarse path planning, followed by subsequent optimization. However, many such frameworks still violate several constraints under certain conditions or produce low-quality trajectories from the perspective of the total duration or other criteria. Thus, in this study, we propose a novel trajectory-planning algorithm that ensures that the produced trajectories satisfy all constraints, including the vehicle-kinematic and collision avoidance. The proposed algorithm is structured hierarchically: first, it employs the Hybrid A* algorithm to plan a coarse path, and this is subsequently optimized within an optimal control framework. A key aspect of this approach is the use of barrier function-based optimization to ensure constraint satisfaction. To utilize the barrier function, a feasible initial trajectory is essential. To generate a strictly feasible initial trajectory that adheres to the Hybrid A* path, we introduce a new discrete-time model for the general bicycle model. This model aligns with the analytical solutions of continuous-time differential equations when the steering angle is constant and maintains high accuracy even with varying steering angles. We evaluate the effectiveness of our method through a comparison with existing methods, finding that our approach successfully generates trajectories that satisfy all constraints in scenarios where others fail. Additionally, our method achieves a significantly lower jerk cost or reduced total duration compared to existing methods.
{"title":"Minimum-time-trajectory planning in cluttered environment via highly accurate discrete-time modeling for wheeled mobile systems","authors":"Yoshihiro Iwanaga , Yasutaka Fujimoto","doi":"10.1016/j.ifacsc.2025.100316","DOIUrl":"10.1016/j.ifacsc.2025.100316","url":null,"abstract":"<div><div>Motion planning for wheeled systems is crucial for enabling efficient automation in applications such as automobiles, wheeled construction machinery, and forklifts. In particular, when operating in cluttered environments, there has been growing interest in methods that utilize sampling-based techniques for coarse path planning, followed by subsequent optimization. However, many such frameworks still violate several constraints under certain conditions or produce low-quality trajectories from the perspective of the total duration or other criteria. Thus, in this study, we propose a novel trajectory-planning algorithm that ensures that the produced trajectories satisfy all constraints, including the vehicle-kinematic and collision avoidance. The proposed algorithm is structured hierarchically: first, it employs the Hybrid A* algorithm to plan a coarse path, and this is subsequently optimized within an optimal control framework. A key aspect of this approach is the use of barrier function-based optimization to ensure constraint satisfaction. To utilize the barrier function, a feasible initial trajectory is essential. To generate a strictly feasible initial trajectory that adheres to the Hybrid A* path, we introduce a new discrete-time model for the general bicycle model. This model aligns with the analytical solutions of continuous-time differential equations when the steering angle is constant and maintains high accuracy even with varying steering angles. We evaluate the effectiveness of our method through a comparison with existing methods, finding that our approach successfully generates trajectories that satisfy all constraints in scenarios where others fail. Additionally, our method achieves a significantly lower jerk cost or reduced total duration compared to existing methods.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100316"},"PeriodicalIF":1.8,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144255277","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}
Pub Date : 2025-06-01DOI: 10.1016/j.ifacsc.2025.100314
Áron Fehér, Lőrinc Márton
The problem of state and disturbance estimation based on a limited number of measurements is addressed for processes that can be modeled by Fisher–Kolmogorov-type Partial Differential Equations (PDEs). The Petrov–Galerkin approximation is employed to derive an Ordinary Differential Equation (ODE) model suitable for observer design. A nonlinear state observer is introduced to estimate the state (solution) of the Fisher–Kolmogorov PDE based on this model. The observer can efficiently reconstruct spatially distributed biological, chemical, or ecological invasion-like processes by applying only a limited number of measurements. Using Lyapunov techniques, it is demonstrated that the proposed observer ensures the convergence of the estimated state to the true state, although the system’s nonlinearity does not satisfy globally the Lipschitz condition. In cases where the system’s dynamics are influenced by an unknown disturbance source, a spatial disturbance localization method is introduced, leveraging the same model. Furthermore, a technique for estimating the magnitude of the unknown disturbance is presented using disturbance observer methods. Simulation results are provided to demonstrate the efficacy of the proposed state and source estimation methods.
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Pub Date : 2025-05-10DOI: 10.1016/j.ifacsc.2025.100313
Vijay Kumar Singh, Jagannathan Sarangapani
Achieving consensus within a user-defined time frame for uncertain nonlinear systems is both crucial and challenging. To tackle this issue, we propose an adaptive consensus protocol that utilizes a radial basis function neural network to handle unknown nonlinearities and actuator faults. Unlike traditional finite-time or fixed-time consensus methods, our approach employs continuous, time-varying feedback to guarantee convergence within the desired time. The proposed strategy ensures that all closed-loop signals of the system remain bounded, achieving consensus within the prescribed time. The effectiveness of the proposed control strategy is demonstrated through a simulation example of phase synchronization in a power system.
{"title":"Prescribed-time fault-tolerant consensus for uncertain nonlinear multi-agent systems","authors":"Vijay Kumar Singh, Jagannathan Sarangapani","doi":"10.1016/j.ifacsc.2025.100313","DOIUrl":"10.1016/j.ifacsc.2025.100313","url":null,"abstract":"<div><div>Achieving consensus within a user-defined time frame for uncertain nonlinear systems is both crucial and challenging. To tackle this issue, we propose an adaptive consensus protocol that utilizes a radial basis function neural network to handle unknown nonlinearities and actuator faults. Unlike traditional finite-time or fixed-time consensus methods, our approach employs continuous, time-varying feedback to guarantee convergence within the desired time. The proposed strategy ensures that all closed-loop signals of the system remain bounded, achieving consensus within the prescribed time. The effectiveness of the proposed control strategy is demonstrated through a simulation example of phase synchronization in a power system.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100313"},"PeriodicalIF":1.8,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143943562","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}
In this paper, we introduce a new concept termed global temporal observability for continuous and discrete linear dynamic systems and explore its connection with the classical notion of observability. It is shown that, as a concept, global temporal observability is a generalization of the classical observability. However, as a feature of a dynamic system, global temporal observability is embedded into classical observability. The necessary condition for global temporal observability is presented. Four linear systems were considered to test the proposed concept. Since observability is a binary test, our results matched the results of classical observability analysis when appropriate basis functions are utilized. The advantages and disadvantages of the proposed concept are discussed. The main advantage of global temporal observability is that it restores the state function for the entire time duration in a single step that requires matrix inversion. It is shown that global temporal observability connects state reconstruction, differential equations, and observability concepts.
{"title":"Global temporal observability of linear dynamic systems","authors":"Altay Zhakatayev , Yuriy Rogovchenko , Matthias Pätzold","doi":"10.1016/j.ifacsc.2025.100312","DOIUrl":"10.1016/j.ifacsc.2025.100312","url":null,"abstract":"<div><div>In this paper, we introduce a new concept termed global temporal observability for continuous and discrete linear dynamic systems and explore its connection with the classical notion of observability. It is shown that, as a concept, global temporal observability is a generalization of the classical observability. However, as a feature of a dynamic system, global temporal observability is embedded into classical observability. The necessary condition for global temporal observability is presented. Four linear systems were considered to test the proposed concept. Since observability is a binary test, our results matched the results of classical observability analysis when appropriate basis functions are utilized. The advantages and disadvantages of the proposed concept are discussed. The main advantage of global temporal observability is that it restores the state function for the entire time duration in a single step that requires matrix inversion. It is shown that global temporal observability connects state reconstruction, differential equations, and observability concepts.</div></div>","PeriodicalId":29926,"journal":{"name":"IFAC Journal of Systems and Control","volume":"32 ","pages":"Article 100312"},"PeriodicalIF":1.8,"publicationDate":"2025-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143928557","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}
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