Pub Date : 2015-03-31DOI: 10.14257/IJCA.2015.8.3.27
C. Mei, Wentao Huang, Kaiting Yin, Guohai Liu
A novel control strategy based on Hammerstein model and neural network for the speedregulating system of the induction motor and inverter is proposed in this paper. First, Hammerstein model was used to model the speed-regulation system of the induction motor and inverter. Auto-regressive and moving average (ARMA) model was used to identify the dynamic linear module of Hammerstein model of the speed-regulating system. Second, the ARMA model was used as a reference model for identification of the inverse model of static nonlinear neural network (NN) module of Hammerstein model in the framework of the model reference adaptive control method. For the load disturbance issue, two control strategies, online learning neural network direct inverse control and the traditional PI close-loop control strategy were studied. Simulations show that the inverse control based on Hammerstein model and NN is effective and the online learning neural network direct inverse control strategy for the speed-regulating system with load disturbance has higher performance.
{"title":"Speed-regulating system for induction motor and inverter based on Hammerstein model and neural network control","authors":"C. Mei, Wentao Huang, Kaiting Yin, Guohai Liu","doi":"10.14257/IJCA.2015.8.3.27","DOIUrl":"https://doi.org/10.14257/IJCA.2015.8.3.27","url":null,"abstract":"A novel control strategy based on Hammerstein model and neural network for the speedregulating system of the induction motor and inverter is proposed in this paper. First, Hammerstein model was used to model the speed-regulation system of the induction motor and inverter. Auto-regressive and moving average (ARMA) model was used to identify the dynamic linear module of Hammerstein model of the speed-regulating system. Second, the ARMA model was used as a reference model for identification of the inverse model of static nonlinear neural network (NN) module of Hammerstein model in the framework of the model reference adaptive control method. For the load disturbance issue, two control strategies, online learning neural network direct inverse control and the traditional PI close-loop control strategy were studied. Simulations show that the inverse control based on Hammerstein model and NN is effective and the online learning neural network direct inverse control strategy for the speed-regulating system with load disturbance has higher performance.","PeriodicalId":34957,"journal":{"name":"控制与决策","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73018424","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 : 2014-02-01DOI: 10.13195/J.KZYJC.2012.1343
Y. Pang, Wei-Liang Li, H. Xia
This paper investigates the linear hybrid automata(LHA) model. Under some certain conditions, linear hybrid automata(LHA) can be converted into their equivalent state-dependent space models, where equivalence means that the two systems generate the same trajectory. The controller of state-dependent space model can be designed by using a nonlinear generalized minimum variance(NGMV) algorithm. NGMV controller is designed for a very general nonlinear model, which can include a set of delay terms and external disturbances. The controller is easy to be computed and implemented. Simulation results show that the NGMV algorithm can control linear hyprid automata effectively, and satisfying effect is obtained under the condition of time delay, disturbance and noise exsiting in the system.
{"title":"Nonlinear generalized minimum variance control of linear hybrid automata","authors":"Y. Pang, Wei-Liang Li, H. Xia","doi":"10.13195/J.KZYJC.2012.1343","DOIUrl":"https://doi.org/10.13195/J.KZYJC.2012.1343","url":null,"abstract":"This paper investigates the linear hybrid automata(LHA) model. Under some certain conditions, linear hybrid automata(LHA) can be converted into their equivalent state-dependent space models, where equivalence means that the two systems generate the same trajectory. The controller of state-dependent space model can be designed by using a nonlinear generalized minimum variance(NGMV) algorithm. NGMV controller is designed for a very general nonlinear model, which can include a set of delay terms and external disturbances. The controller is easy to be computed and implemented. Simulation results show that the NGMV algorithm can control linear hyprid automata effectively, and satisfying effect is obtained under the condition of time delay, disturbance and noise exsiting in the system.","PeriodicalId":34957,"journal":{"name":"控制与决策","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74443323","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 : 2014-01-01DOI: 10.13195/J.KZYJC.2013.0083
B. Feng, Bo Dai
With the rapid development of the world wide web, the network monitoring systems need to be built within the network, but due to huge cost, when the network monitoring system is designed, all of the edges can not be monitored at one time. Instead only a limited number of network nodes can be chosen to monitor a small part of the edge, and later the deployment of a new network monitoring node is increased. Based on the online theory, the online vertex covering problem is studied. A competitive algorithm is presented with a constant competitive ratio. The performance of the competitive ratio is better than the existed result.
{"title":"An online competitive algorithm for network monitor nodes sequence deployment problem","authors":"B. Feng, Bo Dai","doi":"10.13195/J.KZYJC.2013.0083","DOIUrl":"https://doi.org/10.13195/J.KZYJC.2013.0083","url":null,"abstract":"With the rapid development of the world wide web, the network monitoring systems need to be built within the network, but due to huge cost, when the network monitoring system is designed, all of the edges can not be monitored at one time. Instead only a limited number of network nodes can be chosen to monitor a small part of the edge, and later the deployment of a new network monitoring node is increased. Based on the online theory, the online vertex covering problem is studied. A competitive algorithm is presented with a constant competitive ratio. The performance of the competitive ratio is better than the existed result.","PeriodicalId":34957,"journal":{"name":"控制与决策","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85730217","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}
The determination of the optimal control strategy is one of the key factors for the success of supply chain management.Therefore,the control strategy of serial supply chain is studied.First,the optimal model of the serial supply chain inventory control is proposed based on the nonlinear integer programming model combined with the general push/pull control model.Then,the optimal control strategy is obtained by integrating the genetic algorithm and simulation.Case study shows the effectiveness of the method.
{"title":"Optimal Control Strategy for Serial Supply Chain","authors":"Min Huang, Xingwei Wang, Jianqin Ding","doi":"10.5772/6650","DOIUrl":"https://doi.org/10.5772/6650","url":null,"abstract":"The determination of the optimal control strategy is one of the key factors for the success of supply chain management.Therefore,the control strategy of serial supply chain is studied.First,the optimal model of the serial supply chain inventory control is proposed based on the nonlinear integer programming model combined with the general push/pull control model.Then,the optimal control strategy is obtained by integrating the genetic algorithm and simulation.Case study shows the effectiveness of the method.","PeriodicalId":34957,"journal":{"name":"控制与决策","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85076723","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 : 2004-01-01DOI: 10.1109/icca.2003.1229132
Pan Hong-hua
An algorithm of predictive functional control based on grey system model is proposed. The problem of how to set up grey system model and how to calculate the output of predictive model and the equation of control law is addressed. The simulation results show that the algorithm of predictive functional control has better robustness, quick tracking and high control precision.
{"title":"Study of predictive functional control algorithm based on grey system model","authors":"Pan Hong-hua","doi":"10.1109/icca.2003.1229132","DOIUrl":"https://doi.org/10.1109/icca.2003.1229132","url":null,"abstract":"An algorithm of predictive functional control based on grey system model is proposed. The problem of how to set up grey system model and how to calculate the output of predictive model and the equation of control law is addressed. The simulation results show that the algorithm of predictive functional control has better robustness, quick tracking and high control precision.","PeriodicalId":34957,"journal":{"name":"控制与决策","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85196751","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 : 2003-01-01DOI: 10.1109/icit.2016.7474885
Zheng Da-zhong
Simulation optimization with strong engineering background studies the optimization problem of simulation-based objectives, which is often of some hardness, such as stochastic nature, time- consuming and NP-hardness. Currently, simulation optimization has been a hot and new topic in the fields of system simulation, operational research and so on, especially in the field of discrete event dynamical systems. By analyzing the features of simulation optimization, a survey on the algorithms, improvements, applications and software of simulation optimization is provided and some further research contents and directions are presented.
{"title":"Advances in simulation optimization","authors":"Zheng Da-zhong","doi":"10.1109/icit.2016.7474885","DOIUrl":"https://doi.org/10.1109/icit.2016.7474885","url":null,"abstract":"Simulation optimization with strong engineering background studies the optimization problem of simulation-based objectives, which is often of some hardness, such as stochastic nature, time- consuming and NP-hardness. Currently, simulation optimization has been a hot and new topic in the fields of system simulation, operational research and so on, especially in the field of discrete event dynamical systems. By analyzing the features of simulation optimization, a survey on the algorithms, improvements, applications and software of simulation optimization is provided and some further research contents and directions are presented.","PeriodicalId":34957,"journal":{"name":"控制与决策","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2003-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79068010","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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