Pub Date : 2013-08-26DOI: 10.1109/AUCC.2013.6697292
I. Petersen
This paper considers some formulations and possible approaches to the coherent LQG and H∞ quantum control problems. Some new results for these problems are presented in the case of annihilation operator only quantum systems showing that in this case, the optimal controllers are trivial controllers.
{"title":"Notes on Coherent feedback control for linear quantum systems","authors":"I. Petersen","doi":"10.1109/AUCC.2013.6697292","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697292","url":null,"abstract":"This paper considers some formulations and possible approaches to the coherent LQG and H∞ quantum control problems. Some new results for these problems are presented in the case of annihilation operator only quantum systems showing that in this case, the optimal controllers are trivial controllers.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126601260","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 : 2013-07-17DOI: 10.1109/AUCC.2013.6697312
Rahmat Heidari, M. Seron, J. Braslavsky
We consider eigenvalue-eigenvector assignment in order to minimise ultimate bounds on the states of a linear time-invariant (LTI) discrete-time system in the presence of non-vanishing bounded disturbances. As opposed to continuous-time systems, for which eigenstructure assignment with large magnitude stable eigenvalues can yield arbitrarily small ultimate bounds for “matched” perturbations, for discrete-time systems, ultimate bounds cannot be smaller than certain values depending on the disturbance bounds. Moreover, these smallest bounds are not achievable, in general, by assigning the closed-loop eigenvalues to zero (an intuitive conjecture that parallels the continuous-time case). The first contribution of the paper, for single-input systems, are conditions on the zeros of the transfer function between the control input and a state to minimise the ultimate bound corresponding to that state. These conditions generalise a result recently presented by the authors. The second, and main, contribution of the current paper is to characterise, for multiple-input systems, the eigenstructure of the closed-loop system so that some ultimate bounds are minimised to their minimum values. The number of ultimate bound components that can be minimised is constrained by the number of control inputs. For m-input system, the minimisation problem of m - 1 ultimate bound components can be solved without restrictions, while in order to minimise an additional bound, an additional restrictive condition should be satisfied.
{"title":"On eigenvalue-eigenvector assignment for componentwise ultimate bound minimisation in MIMO LTI discrete-time systems","authors":"Rahmat Heidari, M. Seron, J. Braslavsky","doi":"10.1109/AUCC.2013.6697312","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697312","url":null,"abstract":"We consider eigenvalue-eigenvector assignment in order to minimise ultimate bounds on the states of a linear time-invariant (LTI) discrete-time system in the presence of non-vanishing bounded disturbances. As opposed to continuous-time systems, for which eigenstructure assignment with large magnitude stable eigenvalues can yield arbitrarily small ultimate bounds for “matched” perturbations, for discrete-time systems, ultimate bounds cannot be smaller than certain values depending on the disturbance bounds. Moreover, these smallest bounds are not achievable, in general, by assigning the closed-loop eigenvalues to zero (an intuitive conjecture that parallels the continuous-time case). The first contribution of the paper, for single-input systems, are conditions on the zeros of the transfer function between the control input and a state to minimise the ultimate bound corresponding to that state. These conditions generalise a result recently presented by the authors. The second, and main, contribution of the current paper is to characterise, for multiple-input systems, the eigenstructure of the closed-loop system so that some ultimate bounds are minimised to their minimum values. The number of ultimate bound components that can be minimised is constrained by the number of control inputs. For m-input system, the minimisation problem of m - 1 ultimate bound components can be solved without restrictions, while in order to minimise an additional bound, an additional restrictive condition should be satisfied.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124557208","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 : 2013-07-17DOI: 10.1109/AUCC.2013.6697280
A. Nazin, B. Miller
In this article, we study the effectiveness of the Mirror Descent Randomized Control Algorithm recently developed to a class of homogeneous finite Markov chains governed by the stochastic multi-armed bandit with unknown mean losses. We prove the explicit, non-asymptotic both upper and lower bounds for the mean losses at a given (finite) time horizon. These bounds are very similar as functions of problem parameters and time horizon, but with different logarithmic term and absolute constant. Numerical example illustrates theoretical results.
{"title":"On effectiveness of the Mirror Decent Algorithm for a stochastic multi-armed bandit governed by a stationary finite Markov chain","authors":"A. Nazin, B. Miller","doi":"10.1109/AUCC.2013.6697280","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697280","url":null,"abstract":"In this article, we study the effectiveness of the Mirror Descent Randomized Control Algorithm recently developed to a class of homogeneous finite Markov chains governed by the stochastic multi-armed bandit with unknown mean losses. We prove the explicit, non-asymptotic both upper and lower bounds for the mean losses at a given (finite) time horizon. These bounds are very similar as functions of problem parameters and time horizon, but with different logarithmic term and absolute constant. Numerical example illustrates theoretical results.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125682512","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 : 2013-05-14DOI: 10.1109/AUCC.2013.6697287
Esteban N. Osella, H. Haimovich, M. Seron
We present a new output feedback fault tolerant control strategy for continuous-time linear systems. The strategy combines a digital nominal controller under controller-driven (varying) sampling with virtual-actuator (VA)-based controller reconfiguration to compensate for actuator faults. In the proposed scheme, the controller controls both the plant and the sampling period, and a fault detection mechanism performs controller reconfiguration by engaging in the loop the VA adapted to the diagnosed fault. The VA also operates under controller-driven sampling. Two independent objectives are considered: (a) closed-loop stability with setpoint tracking and (b) controller reconfiguration under faults. Our main contribution is to extend an existing VA-based controller reconfiguration strategy to systems under controller-driven sampling in such a way that if objective (a) is possible under controller-driven sampling (without VA) and objective (b) is possible under uniform sampling (without controller-driven sampling), then closed-loop stability and setpoint tracking will be preserved under both healthy and faulty operation for all possible sampling rate evolutions.
{"title":"Fault-tolerant control under controller-driven sampling using a virtual actuator strategy","authors":"Esteban N. Osella, H. Haimovich, M. Seron","doi":"10.1109/AUCC.2013.6697287","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697287","url":null,"abstract":"We present a new output feedback fault tolerant control strategy for continuous-time linear systems. The strategy combines a digital nominal controller under controller-driven (varying) sampling with virtual-actuator (VA)-based controller reconfiguration to compensate for actuator faults. In the proposed scheme, the controller controls both the plant and the sampling period, and a fault detection mechanism performs controller reconfiguration by engaging in the loop the VA adapted to the diagnosed fault. The VA also operates under controller-driven sampling. Two independent objectives are considered: (a) closed-loop stability with setpoint tracking and (b) controller reconfiguration under faults. Our main contribution is to extend an existing VA-based controller reconfiguration strategy to systems under controller-driven sampling in such a way that if objective (a) is possible under controller-driven sampling (without VA) and objective (b) is possible under uniform sampling (without controller-driven sampling), then closed-loop stability and setpoint tracking will be preserved under both healthy and faulty operation for all possible sampling rate evolutions.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"361 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133904895","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 : 1900-01-01DOI: 10.1109/AUCC.2013.6697269
Rahul Sharma, R. Yan, M. Kearney
The large-scale use of wind power generation continues to be hindered due to its intermittency. Among the potential solutions to this problem, the adoption of battery-based storage systems is widely seen as inevitable. The aim of this paper is to develop a real-time model-based optimisation approach for the coordinated control of a wind turbine equipped with battery storage. First, the mathematical model of the wind turbine-battery system is systematically reduced using singular perturbation theory. Then, the obtained reduced-order model is utilised in the control system development. The control system is devised using a real-time implementable version of model predictive control whereby the nonlinear dynamics are linearised at each sampling instant to simultaneously overcome the computational issues due to nonlinear optimisation and performance degradation issues due to linearisation at only one operating point. The effectiveness of the proposed controller in reducing wind intermittency through the optimal management of the battery storage is demonstrated using simulation studies involving real wind-data from an Australian wind farm.
{"title":"Predictive control of wind turbines with storage","authors":"Rahul Sharma, R. Yan, M. Kearney","doi":"10.1109/AUCC.2013.6697269","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697269","url":null,"abstract":"The large-scale use of wind power generation continues to be hindered due to its intermittency. Among the potential solutions to this problem, the adoption of battery-based storage systems is widely seen as inevitable. The aim of this paper is to develop a real-time model-based optimisation approach for the coordinated control of a wind turbine equipped with battery storage. First, the mathematical model of the wind turbine-battery system is systematically reduced using singular perturbation theory. Then, the obtained reduced-order model is utilised in the control system development. The control system is devised using a real-time implementable version of model predictive control whereby the nonlinear dynamics are linearised at each sampling instant to simultaneously overcome the computational issues due to nonlinear optimisation and performance degradation issues due to linearisation at only one operating point. The effectiveness of the proposed controller in reducing wind intermittency through the optimal management of the battery storage is demonstrated using simulation studies involving real wind-data from an Australian wind farm.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130017059","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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