Pub Date : 2008-09-30DOI: 10.1109/ISIC.2008.4635962
Yijing Wang, Zhenxian Yao, Z. Zuo, Huimin Zhao
The delay-dependent H∞ control for switched systems with time-delay is discussed in this paper. Based on linear matrix inequalities (LMI), a new delay-dependent condition is then derived by employing Lyapunov-Razumikhin functional method, which can ensure that the switched system is asymptotically stable with a prescribed Hinfin performance. Moreover, a switching state feedback strategy is proposed to solve the H∞ control problem for the linear switched systems. By state feedback, we mean that the switchings among subsystems are dependent on system states. Finally, a simulation example is given to illustrate the validity of the result.
{"title":"Delay-dependent Robust H∞ Control for a Class of Switched Systems with Time Delay","authors":"Yijing Wang, Zhenxian Yao, Z. Zuo, Huimin Zhao","doi":"10.1109/ISIC.2008.4635962","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635962","url":null,"abstract":"The delay-dependent H∞ control for switched systems with time-delay is discussed in this paper. Based on linear matrix inequalities (LMI), a new delay-dependent condition is then derived by employing Lyapunov-Razumikhin functional method, which can ensure that the switched system is asymptotically stable with a prescribed Hinfin performance. Moreover, a switching state feedback strategy is proposed to solve the H∞ control problem for the linear switched systems. By state feedback, we mean that the switchings among subsystems are dependent on system states. Finally, a simulation example is given to illustrate the validity of the result.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134091162","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635952
Atalla F. Sayda, James H. Taylor
This three-part paper thoroughly addresses the design and development of multi-agent system for asset management for the petroleum industry, which is crucial for profitable oil and gas facilities operations and maintenance. A research project was initiated to study the feasibility of an intelligent asset management system. Having proposed a conceptual model, architecture, and implementation plan for such a system in previous work (J.H. Taylor and A.F. Sayda, 2005), (A.F. Sayda and J.H. Taylor, 2006), defined its autonomy, communications, and artificial intelligence (AI) requirements and initiated the preliminary design of a simple system prototype (J.H. Taylor and A.F. Sayda, 2008), we are extending the build of a system prototype and simulate it in real-time to validate its logical behavior in normal and abnormal process situations and analyze its performance. The third-part paper addresses the ICAM system prototype validation in terms of system performance analysis and system behavior during unexpected situations.
本文由三部分组成，详细介绍了石油行业资产管理多代理系统的设计和开发，这对于油气设施的运营和维护至关重要。启动了一个研究项目，研究智能资产管理系统的可行性。在之前的工作(J.H. Taylor and A.F. Sayda, 2005)和(A.F. Sayda and J.H. Taylor, 2006)中提出了这样一个系统的概念模型、架构和实施计划，定义了其自主性、通信和人工智能(AI)需求，并启动了一个简单系统原型的初步设计(J.H. Taylor and A.F. Sayda, 2008)。我们正在扩展系统原型的构建，并对其进行实时仿真，以验证其在正常和异常过程情况下的逻辑行为，并分析其性能。论文的第三部分从系统性能分析和系统在意外情况下的行为方面阐述了ICAM系统原型验证。
{"title":"A Multi-agent System for Integrated Control and Asset Management of Petroleum Production Facilities - Part 3: Performance Analysis and System Limitations","authors":"Atalla F. Sayda, James H. Taylor","doi":"10.1109/ISIC.2008.4635952","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635952","url":null,"abstract":"This three-part paper thoroughly addresses the design and development of multi-agent system for asset management for the petroleum industry, which is crucial for profitable oil and gas facilities operations and maintenance. A research project was initiated to study the feasibility of an intelligent asset management system. Having proposed a conceptual model, architecture, and implementation plan for such a system in previous work (J.H. Taylor and A.F. Sayda, 2005), (A.F. Sayda and J.H. Taylor, 2006), defined its autonomy, communications, and artificial intelligence (AI) requirements and initiated the preliminary design of a simple system prototype (J.H. Taylor and A.F. Sayda, 2008), we are extending the build of a system prototype and simulate it in real-time to validate its logical behavior in normal and abnormal process situations and analyze its performance. The third-part paper addresses the ICAM system prototype validation in terms of system performance analysis and system behavior during unexpected situations.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134181404","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635954
Ching-Ling Huang, R. Sengupta
This paper investigates the performance of model-based estimation over multi-access networks and emphasizes on the estimation MSE (mean squared error) while using different channel access schemes: probabilistic (random access), deterministic (round-robin scheduling), and combined (grouped channel access). We propose a mathematical framework for estimation over a simple multi-access MAC protocol, the slotted ALOHA network. Estimation MSE, its asymptotic behavior and stability condition are derived for different channel access methods. Our quantitative discussion can provide guidelines to design the communication logic for those control systems built on top of multi-access networks.
{"title":"Analysis of Channel Access Schemes for Model-based Estimation over Multi-access Networks","authors":"Ching-Ling Huang, R. Sengupta","doi":"10.1109/ISIC.2008.4635954","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635954","url":null,"abstract":"This paper investigates the performance of model-based estimation over multi-access networks and emphasizes on the estimation MSE (mean squared error) while using different channel access schemes: probabilistic (random access), deterministic (round-robin scheduling), and combined (grouped channel access). We propose a mathematical framework for estimation over a simple multi-access MAC protocol, the slotted ALOHA network. Estimation MSE, its asymptotic behavior and stability condition are derived for different channel access methods. Our quantitative discussion can provide guidelines to design the communication logic for those control systems built on top of multi-access networks.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"206 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121084475","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635968
N. Sharma, C. Gregory, Marcus Johnson, W. Dixon
Closed-loop control of skeletal muscle is complicated by the nonlinear muscle force to length relationship and the inherent unstructured and time-varying uncertainties in available models. Some pure feedback methods have been developed with some success, but the most promising and popular control methods for neuromuscular electrical stimulation (NMES) are neural network-based methods. Neural networks provide a function approximation of the muscle model, however a function reconstruction error limits the steady-state response of typical controllers (i.e., previous controllers are only uniformly ultimately bounded). Motivated by the desire to obtain improved steady-state performance, efforts in this paper focus on the use of a neural network feedforward controller that is augmented with a continuous robust feedback term to yield an asymptotic result. Specifically, a Lyapunov-based controller and stability analysis are provided to demonstrate semi-global asymptotic tracking (i.e., non-isometric contractions) of a desired time-varying trajectory. Experimental results are provided to demonstrate the performance of the developed controller where NMES is applied through external electrodes attached to the distal-medial and proximal-lateral portion of human quadriceps femoris muscle group.
{"title":"Modified Neural Network-based Electrical Stimulation for Human Limb Tracking","authors":"N. Sharma, C. Gregory, Marcus Johnson, W. Dixon","doi":"10.1109/ISIC.2008.4635968","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635968","url":null,"abstract":"Closed-loop control of skeletal muscle is complicated by the nonlinear muscle force to length relationship and the inherent unstructured and time-varying uncertainties in available models. Some pure feedback methods have been developed with some success, but the most promising and popular control methods for neuromuscular electrical stimulation (NMES) are neural network-based methods. Neural networks provide a function approximation of the muscle model, however a function reconstruction error limits the steady-state response of typical controllers (i.e., previous controllers are only uniformly ultimately bounded). Motivated by the desire to obtain improved steady-state performance, efforts in this paper focus on the use of a neural network feedforward controller that is augmented with a continuous robust feedback term to yield an asymptotic result. Specifically, a Lyapunov-based controller and stability analysis are provided to demonstrate semi-global asymptotic tracking (i.e., non-isometric contractions) of a desired time-varying trajectory. Experimental results are provided to demonstrate the performance of the developed controller where NMES is applied through external electrodes attached to the distal-medial and proximal-lateral portion of human quadriceps femoris muscle group.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129745058","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635946
Diana A. Urrego-Patarroyo, E. Sánchez, S. Carlos-Hernandez, J. Béteau
In this paper, a recurrent neural networks observer for anaerobic processes is proposed; the main objective is to estimate biomass, in a completely stirred tank reactor. The neural network is trained with an extended Kalman filter algorithm. The applicability of the proposed observer is verified via simulations.
{"title":"Recurrent Neural Networks Biomass Observer for Anaerobic Processes","authors":"Diana A. Urrego-Patarroyo, E. Sánchez, S. Carlos-Hernandez, J. Béteau","doi":"10.1109/ISIC.2008.4635946","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635946","url":null,"abstract":"In this paper, a recurrent neural networks observer for anaerobic processes is proposed; the main objective is to estimate biomass, in a completely stirred tank reactor. The neural network is trained with an extended Kalman filter algorithm. The applicability of the proposed observer is verified via simulations.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124764563","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635951
Atalla F. Sayda, James H. Taylor
This three-part paper thoroughly addresses the design and development of multi-agent system for asset management for the petroleum industry, which is crucial for profitable oil and gas facilities operations and maintenance. A research project was initiated to study the feasibility of an intelligent asset management system. Having proposed a conceptual model, architecture, and implementation plan for such a system defined its autonomy, communications, and artificial intelligence (AI) requirements, and initiated the preliminary design of a simple system prototype, we are extending the build of a system prototype and simulate it in real-time to validate its logical behavior in normal and abnormal process situations and analyze its performance. The second-part paper addresses the ICAM system prototype design verification and its logical behavior during sensor faults in the plant.
{"title":"A Multi-agent System for Integrated Control and Asset Management of Petroleum Production Facilities - Part 2: Prototype Design Verification","authors":"Atalla F. Sayda, James H. Taylor","doi":"10.1109/ISIC.2008.4635951","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635951","url":null,"abstract":"This three-part paper thoroughly addresses the design and development of multi-agent system for asset management for the petroleum industry, which is crucial for profitable oil and gas facilities operations and maintenance. A research project was initiated to study the feasibility of an intelligent asset management system. Having proposed a conceptual model, architecture, and implementation plan for such a system defined its autonomy, communications, and artificial intelligence (AI) requirements, and initiated the preliminary design of a simple system prototype, we are extending the build of a system prototype and simulate it in real-time to validate its logical behavior in normal and abnormal process situations and analyze its performance. The second-part paper addresses the ICAM system prototype design verification and its logical behavior during sensor faults in the plant.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114649093","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635931
R. Decarlo, S. Pekarek, M. Žefran
This workshop will present recently developed results on the solution of the hybrid/switched optimal control problem using the embedding method developed by Bengea and DeCarlo (Automatica, January 2005). Using a variation of the collocation method, a numerical solution of the problem via sequential quadratic programming is outlined. Using these tools and a model predictive control approach, application of the techniques to the switching control of a boost converter using a sliding mode observer is then presented followed by the model predictive control of mobile robots and groups of autonomous aerial vehicles (AUVs). Finally, a solution to the power management problem in a hybrid electric vehicle is presented with simulation studies for a variety of driving profiles including the new EPA driving profile. The examples will not only describe appropriate models, MPC control methodologies, and simulation studies, but also highlight the broader appeal of these newly developed techniques for modeling, analysis, and design of hybrid/switched systems. SCHEDULE: SEPTEMBER 2, 2008
{"title":"Optimal Control of Switching/Hybrid Systems with Applications to Hybrid Electric Vehicles, Dc-Dc Converters, and Autonomous Mobile Robots","authors":"R. Decarlo, S. Pekarek, M. Žefran","doi":"10.1109/ISIC.2008.4635931","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635931","url":null,"abstract":"This workshop will present recently developed results on the solution of the hybrid/switched optimal control problem using the embedding method developed by Bengea and DeCarlo (Automatica, January 2005). Using a variation of the collocation method, a numerical solution of the problem via sequential quadratic programming is outlined. Using these tools and a model predictive control approach, application of the techniques to the switching control of a boost converter using a sliding mode observer is then presented followed by the model predictive control of mobile robots and groups of autonomous aerial vehicles (AUVs). Finally, a solution to the power management problem in a hybrid electric vehicle is presented with simulation studies for a variety of driving profiles including the new EPA driving profile. The examples will not only describe appropriate models, MPC control methodologies, and simulation studies, but also highlight the broader appeal of these newly developed techniques for modeling, analysis, and design of hybrid/switched systems. SCHEDULE: SEPTEMBER 2, 2008","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122630170","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635945
M. Hernández-González, E. Sánchez, A. Loukianov
This paper presents a discrete-time control for a linear induction motor (LIM). First, an identifier is proposed with a nonlinear block controllable form (NBC) structure. This identifier is based on a discrete-time high order neural network trained on-line with an extended Kalman filter (EKF)-based algorithm. Then, a sliding mode control is used to achieve the purpose of tracking velocity and magnitude flux. The neural control performance is illustrated via simulations.
{"title":"Discrete-time Neural Network Control for a Linear Induction Motor","authors":"M. Hernández-González, E. Sánchez, A. Loukianov","doi":"10.1109/ISIC.2008.4635945","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635945","url":null,"abstract":"This paper presents a discrete-time control for a linear induction motor (LIM). First, an identifier is proposed with a nonlinear block controllable form (NBC) structure. This identifier is based on a discrete-time high order neural network trained on-line with an extended Kalman filter (EKF)-based algorithm. Then, a sliding mode control is used to achieve the purpose of tracking velocity and magnitude flux. The neural control performance is illustrated via simulations.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114762713","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635937
Philipp Adelt, A. Schmidt, Natascha Esau, L. Kleinjohann, B. Kleinjohann, Mirko Rose
In mechatronic systems a lot of components above the controller level are needed for the development towards self-optimizing systems. Among them a hybrid planning architecture integrating discrete and continuous domains is of major importance to support the permanent determination of system objectives and their implementation during the course of action, which defines the principle of self-optimizing mechatronic systems. Such a novel hybrid planning architecture is outlined in this paper. In order to plan efficiently, environment models are needed for predicting future system behaviors. In this paper we propose a fuzzy logic based approach to environment modeling and apply it in a railway-bound domain within the context of an air gap adjustment system for a dual-fed linear motor powering a wheeled train.
{"title":"Approximation of Environment Models for an Air Gap Adjustment System in a Hybrid Planning Context","authors":"Philipp Adelt, A. Schmidt, Natascha Esau, L. Kleinjohann, B. Kleinjohann, Mirko Rose","doi":"10.1109/ISIC.2008.4635937","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635937","url":null,"abstract":"In mechatronic systems a lot of components above the controller level are needed for the development towards self-optimizing systems. Among them a hybrid planning architecture integrating discrete and continuous domains is of major importance to support the permanent determination of system objectives and their implementation during the course of action, which defines the principle of self-optimizing mechatronic systems. Such a novel hybrid planning architecture is outlined in this paper. In order to plan efficiently, environment models are needed for predicting future system behaviors. In this paper we propose a fuzzy logic based approach to environment modeling and apply it in a railway-bound domain within the context of an air gap adjustment system for a dual-fed linear motor powering a wheeled train.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133986688","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635950
Atalla F. Sayda, James H. Taylor
This three-part paper thoroughly addresses the design and development of multi-agent system for asset management for the petroleum industry, which is crucial for profitable oil and gas facilities operations and maintenance. A research project was initiated to study the feasibility of an intelligent asset management system. Having proposed a conceptual model, architecture, and implementation plan for such a system in previous work [1], [2], [3], defined its autonomy, communications, and artificial intelligence (AI) requirements [4], [5], and initiated the preliminary design of a simple system prototype [6], we are extending the build of a system prototype and simulate it in real-time to validate its logical behavior in normal and abnormal process situations and analyze its performance.
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