Pub Date : 2001-09-05DOI: 10.1109/ISIC.2001.971519
Torbjörn Liljenvall, Martin Fabian
In this paper we propose a generic system architecture for development, control and scheduling of flexible production systems. As typical applications we have mainly considered control systems for machining cells, and batch applications in processing industry. The architecture is based on an object-oriented model of a production system, together with distributed product specifications and automatic synthesis of control laws to integrate product specification and production planning with the control system.
{"title":"Implementation of control and scheduling for production systems","authors":"Torbjörn Liljenvall, Martin Fabian","doi":"10.1109/ISIC.2001.971519","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971519","url":null,"abstract":"In this paper we propose a generic system architecture for development, control and scheduling of flexible production systems. As typical applications we have mainly considered control systems for machining cells, and batch applications in processing industry. The architecture is based on an object-oriented model of a production system, together with distributed product specifications and automatic synthesis of control laws to integrate product specification and production planning with the control system.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126941025","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971513
M. Yeddes, J. Mullins
This paper show how one can transform a synchronous system into a globally asynchronous locally synchronous systems in which each site behaves synchronously while the exchange between sites are asynchronous. This is a case of synchronous distributed systems called quasi-synchronous systems. We investigate a hybrid system and show that the continuous control has no problem when the distribution is different from the discrete sequential one. We propose a method allowing the validation of the distributed system through the validation of the centralized one.
{"title":"Quasi-synchronous approach for distributed control in synchronous systems","authors":"M. Yeddes, J. Mullins","doi":"10.1109/ISIC.2001.971513","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971513","url":null,"abstract":"This paper show how one can transform a synchronous system into a globally asynchronous locally synchronous systems in which each site behaves synchronously while the exchange between sites are asynchronous. This is a case of synchronous distributed systems called quasi-synchronous systems. We investigate a hybrid system and show that the continuous control has no problem when the distribution is different from the discrete sequential one. We propose a method allowing the validation of the distributed system through the validation of the centralized one.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"355 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115932746","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971500
Goran Frehse, O. Stursberg, S. Engell, Ralf Huuck, Ben Lukoschus
While formal verification has been successfully used to analyze several academic examples of controlled hybrid systems, the application to real-world processing systems is largely restricted by the complexity of modeling and computation. This paper aims at improving the applicability by using decomposition and deduction techniques: A given system is first decomposed into a set of physical and/or functional units and modeled by communicating timed automata or linear hybrid automata. The so-called assumption/commitment method allows one to formulate requirements for the desired behavior of single modules or groups of modules. Model-checking is an appropriate technique to analyze whether the requirements (e.g. the exclusion of critical states) are fulfilled. By combining the analysis results obtained for single modules, properties of composed modules can be deduced. As illustrated for a laboratory plant, properties of the complete system for which direct model-checking is prohibitively expensive can be inferred by the iterative application of analysis and deduction.
{"title":"Verification of hybrid controlled processing systems based on decomposition and deduction","authors":"Goran Frehse, O. Stursberg, S. Engell, Ralf Huuck, Ben Lukoschus","doi":"10.1109/ISIC.2001.971500","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971500","url":null,"abstract":"While formal verification has been successfully used to analyze several academic examples of controlled hybrid systems, the application to real-world processing systems is largely restricted by the complexity of modeling and computation. This paper aims at improving the applicability by using decomposition and deduction techniques: A given system is first decomposed into a set of physical and/or functional units and modeled by communicating timed automata or linear hybrid automata. The so-called assumption/commitment method allows one to formulate requirements for the desired behavior of single modules or groups of modules. Model-checking is an appropriate technique to analyze whether the requirements (e.g. the exclusion of critical states) are fulfilled. By combining the analysis results obtained for single modules, properties of composed modules can be deduced. As illustrated for a laboratory plant, properties of the complete system for which direct model-checking is prohibitively expensive can be inferred by the iterative application of analysis and deduction.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116138659","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971477
T. Samad, D. Gorinevsky, F. Stoffelen
We describe an approach for dynamic route optimization for autonomous high-performance aircraft. A multiresolution representation scheme is presented that uses B-spline basis functions of different support and at different locations along the trajectory, parametrized by a dimensionless parameter. A multirate receding horizon problem is formulated as an example of online multiresolution optimization under feedback. The underlying optimization problem is solved with an anytime evolutionary computing algorithm. By selecting particular basis function coefficients as the optimization variables, computing resources can flexibly be devoted to those regions of the trajectory requiring most attention. A simulation scenario is presented.
{"title":"Dynamic multiresolution route optimization for autonomous aircraft","authors":"T. Samad, D. Gorinevsky, F. Stoffelen","doi":"10.1109/ISIC.2001.971477","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971477","url":null,"abstract":"We describe an approach for dynamic route optimization for autonomous high-performance aircraft. A multiresolution representation scheme is presented that uses B-spline basis functions of different support and at different locations along the trajectory, parametrized by a dimensionless parameter. A multirate receding horizon problem is formulated as an example of online multiresolution optimization under feedback. The underlying optimization problem is solved with an anytime evolutionary computing algorithm. By selecting particular basis function coefficients as the optimization variables, computing resources can flexibly be devoted to those regions of the trajectory requiring most attention. A simulation scenario is presented.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128463334","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971481
Derong Liu, T. Chang, Yi Zhang
We develop in the present paper a constructive learning algorithm for feedforward neural networks. We employ an incremental training procedure where training patterns are learned one by one. Our algorithm starts with a single training pattern and a single hidden layer neuron. During the course of neural network training, when the algorithm gets stuck in a local minimum, we will attempt to escape from the local minimum by using the weight scaling technique. It is only after several consecutive failed attempts in escaping from a local minimum, we will allow the network to grow by adding a hidden layer neuron. At this stage, we employ an optimization procedure based on quadratic/linear programming to select initial weights for the newly added neuron. Our optimization procedure tends to make the network reach the error tolerance with no or little training after adding a hidden layer neuron Our simulation results indicate that the present constructive algorithm can obtain neural networks very close to minimal structures and that convergence (to a solution) in neural network training can be guaranteed. We tested our algorithm extensively using the parity problem.
{"title":"A new learning algorithm for feedforward neural networks","authors":"Derong Liu, T. Chang, Yi Zhang","doi":"10.1109/ISIC.2001.971481","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971481","url":null,"abstract":"We develop in the present paper a constructive learning algorithm for feedforward neural networks. We employ an incremental training procedure where training patterns are learned one by one. Our algorithm starts with a single training pattern and a single hidden layer neuron. During the course of neural network training, when the algorithm gets stuck in a local minimum, we will attempt to escape from the local minimum by using the weight scaling technique. It is only after several consecutive failed attempts in escaping from a local minimum, we will allow the network to grow by adding a hidden layer neuron. At this stage, we employ an optimization procedure based on quadratic/linear programming to select initial weights for the newly added neuron. Our optimization procedure tends to make the network reach the error tolerance with no or little training after adding a hidden layer neuron Our simulation results indicate that the present constructive algorithm can obtain neural networks very close to minimal structures and that convergence (to a solution) in neural network training can be guaranteed. We tested our algorithm extensively using the parity problem.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128239305","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971491
S. S. Ge, G.Y. Li, T.H. Lee
In this paper, the adaptive control problem is studied for a class of discrete-time unknown nonlinear systems with general relative degree in the presence of bounded disturbances. To derive the feedback control, a causal state-space model of the plant is obtained. By using an NN observer to estimate the unavailable but predictable states of the system, a Lyapunov-based adaptive state feedback NN controller is proposed. The state feedback control avoids the possible singularity problem in adaptive nonlinear control. The closed-loop system is proven to be semi-globally uniformly ultimately bounded (SGUUB). An arbitrarily small tracking error can be achieved if the size of neural networks is chosen large enough, and the control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.
{"title":"Adaptive control for a class of nonlinear discrete-time systems using neural networks","authors":"S. S. Ge, G.Y. Li, T.H. Lee","doi":"10.1109/ISIC.2001.971491","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971491","url":null,"abstract":"In this paper, the adaptive control problem is studied for a class of discrete-time unknown nonlinear systems with general relative degree in the presence of bounded disturbances. To derive the feedback control, a causal state-space model of the plant is obtained. By using an NN observer to estimate the unavailable but predictable states of the system, a Lyapunov-based adaptive state feedback NN controller is proposed. The state feedback control avoids the possible singularity problem in adaptive nonlinear control. The closed-loop system is proven to be semi-globally uniformly ultimately bounded (SGUUB). An arbitrarily small tracking error can be achieved if the size of neural networks is chosen large enough, and the control performance of the closed-loop system is guaranteed by suitably choosing the design parameters.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124172911","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971517
A. Vahidi, Martin Fabian, B. Lennartson
This paper presents a generic model for the resource allocation problem common in flexible manufacturing systems. The resource allocation model is used for computing the supremal controllable and nonblocking supervisor of the system. A real world example of such system is given, and it is explained why the exhaustive search method for supervisor generation fails on large system due to the state explosion problem. To solve this a special data structure adapted from the symbolic model checking area called binary decision diagram is utilized.
{"title":"Generic resource booking models in flexible cells","authors":"A. Vahidi, Martin Fabian, B. Lennartson","doi":"10.1109/ISIC.2001.971517","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971517","url":null,"abstract":"This paper presents a generic model for the resource allocation problem common in flexible manufacturing systems. The resource allocation model is used for computing the supremal controllable and nonblocking supervisor of the system. A real world example of such system is given, and it is explained why the exhaustive search method for supervisor generation fails on large system due to the state explosion problem. To solve this a special data structure adapted from the symbolic model checking area called binary decision diagram is utilized.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133799641","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971488
G. Vachtsevanos, Peng Wang, J. Echauz
This paper introduces a new model-free diagnostic methodology to detect and identify machine failures and product defects. The basic module of the methodology is a novel multidimensional wavelet neural network construct used as the failure mode classifier. Validated sensor data are preprocessed and a vector of appropriate features is extracted. The feature vector becomes the input to the wavelet neural network which is trained off-line to map features to failure causes. An example is employed to illustrate the robustness and effectiveness of the proposed scheme.
{"title":"A wavelet neural network framework for diagnostics of complex engineered systems","authors":"G. Vachtsevanos, Peng Wang, J. Echauz","doi":"10.1109/ISIC.2001.971488","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971488","url":null,"abstract":"This paper introduces a new model-free diagnostic methodology to detect and identify machine failures and product defects. The basic module of the methodology is a novel multidimensional wavelet neural network construct used as the failure mode classifier. Validated sensor data are preprocessed and a vector of appropriate features is extracted. The feature vector becomes the input to the wavelet neural network which is trained off-line to map features to failure causes. An example is employed to illustrate the robustness and effectiveness of the proposed scheme.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129268281","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971489
S. Ploix, C. Follot
This paper focuses on diagnostic reasoning for uncertain dynamical systems. It proposes a diagnostic reasoning that distinguishes normal from abnormal behavior and that takes into account the new results in set-membership diagnostic approaches. Considering these results, which are dedicated to uncertain systems, enlightens the diagnostic reasoning with new aspects. To validate the theoretical aspects, the paper ends by the presentation of an application of diagnostic reasoning and set-membership coherency tests on a laboratory plant: a water tanks system.
{"title":"Fault diagnosis reasoning for set-membership approaches and application","authors":"S. Ploix, C. Follot","doi":"10.1109/ISIC.2001.971489","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971489","url":null,"abstract":"This paper focuses on diagnostic reasoning for uncertain dynamical systems. It proposes a diagnostic reasoning that distinguishes normal from abnormal behavior and that takes into account the new results in set-membership diagnostic approaches. Considering these results, which are dedicated to uncertain systems, enlightens the diagnostic reasoning with new aspects. To validate the theoretical aspects, the paper ends by the presentation of an application of diagnostic reasoning and set-membership coherency tests on a laboratory plant: a water tanks system.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114138448","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 : 2001-09-05DOI: 10.1109/ISIC.2001.971534
B. Kadmiry, D. Driankov
The paper presents the design of a horizontal velocity controller for the unmanned helicopter APID MK-III developed by Scandicraft AB in Sweden. The controller is able of regulating high horizontal velocities via stabilization of the attitude angles within much larger ranges than currently available. We use a novel approach to the design consisting of two steps: 1) a Mamdani-type of a fuzzy rules are used to compute for each desired horizontal velocity the corresponding desired values for the attitude angles and the main rotor collective pitch; and 2) using a nonlinear model of the altitude and attitude dynamics, a Takagi-Sugeno controller is used to regulate the attitude angles so that the helicopter achieves its desired horizontal velocities at a desired altitude. According to our knowledge this is the first time when a combination of linguistic and model-based fuzzy control is used for the control of a complicated plant such as an autonomous helicopter. The performance of the combined linguistic/model-based controllers is evaluated in simulation and shows that the proposed design method achieves its intended purpose.
{"title":"Autonomous helicopter control using linguistic and model-based fuzzy control","authors":"B. Kadmiry, D. Driankov","doi":"10.1109/ISIC.2001.971534","DOIUrl":"https://doi.org/10.1109/ISIC.2001.971534","url":null,"abstract":"The paper presents the design of a horizontal velocity controller for the unmanned helicopter APID MK-III developed by Scandicraft AB in Sweden. The controller is able of regulating high horizontal velocities via stabilization of the attitude angles within much larger ranges than currently available. We use a novel approach to the design consisting of two steps: 1) a Mamdani-type of a fuzzy rules are used to compute for each desired horizontal velocity the corresponding desired values for the attitude angles and the main rotor collective pitch; and 2) using a nonlinear model of the altitude and attitude dynamics, a Takagi-Sugeno controller is used to regulate the attitude angles so that the helicopter achieves its desired horizontal velocities at a desired altitude. According to our knowledge this is the first time when a combination of linguistic and model-based fuzzy control is used for the control of a complicated plant such as an autonomous helicopter. The performance of the combined linguistic/model-based controllers is evaluated in simulation and shows that the proposed design method achieves its intended purpose.","PeriodicalId":367430,"journal":{"name":"Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132371408","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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