Pub Date : 2013-11-01DOI: 10.1109/AUCC.2013.6697286
T. Bruggemann, J. Ford
Aerial inspection of pipelines, powerlines, and other large linear infrastructure networks has emerged in a number of civilian remote sensing applications. Challenges relate to automating inspection flight for under-actuated aircraft with LiDAR/camera sensor constraints whilst subjected to wind disturbances. This paper presents new improved turn planning strategies with guidance suitable for automation of linear infrastructure inspection able to reduce inspection flight distance by including wind information. Simulation and experimental flight tests confirmed the flight distance saving, and the proposed guidance strategies exhibited good tracking performance in a range of wind conditions.
{"title":"Automated aerial inspection guidance with improved turn planning","authors":"T. Bruggemann, J. Ford","doi":"10.1109/AUCC.2013.6697286","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697286","url":null,"abstract":"Aerial inspection of pipelines, powerlines, and other large linear infrastructure networks has emerged in a number of civilian remote sensing applications. Challenges relate to automating inspection flight for under-actuated aircraft with LiDAR/camera sensor constraints whilst subjected to wind disturbances. This paper presents new improved turn planning strategies with guidance suitable for automation of linear infrastructure inspection able to reduce inspection flight distance by including wind information. Simulation and experimental flight tests confirmed the flight distance saving, and the proposed guidance strategies exhibited good tracking performance in a range of wind conditions.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127708672","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697291
Z. Miao, L. A. D. Espinosa, I. Petersen, V. Ugrinovskii, M. James
The purpose of this paper is to find coherent quantum observers for open n-level quantum systems. Recently, a class of linear coherent observers has been developed for quantum harmonic oscillators. However, open n-level quantum systems, which are characterized by bilinear quantum stochastic differential equations, escape the realm of the known theory. Therefore, in this paper we show how a coherent quantum observer is designed to track the corresponding n-level quantum plant asymptotically in the sense of mean values. We also discuss suboptimal quantum observers in the sense of least mean squares estimation.
{"title":"Coherent quantum observers for n-level quantum systems","authors":"Z. Miao, L. A. D. Espinosa, I. Petersen, V. Ugrinovskii, M. James","doi":"10.1109/AUCC.2013.6697291","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697291","url":null,"abstract":"The purpose of this paper is to find coherent quantum observers for open n-level quantum systems. Recently, a class of linear coherent observers has been developed for quantum harmonic oscillators. However, open n-level quantum systems, which are characterized by bilinear quantum stochastic differential equations, escape the realm of the known theory. Therefore, in this paper we show how a coherent quantum observer is designed to track the corresponding n-level quantum plant asymptotically in the sense of mean values. We also discuss suboptimal quantum observers in the sense of least mean squares estimation.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132729539","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697256
M. Fadil, I. Darus
This paper presents the development of self tuning Active Vibration Control (AVC) strategy for flexible beam structure. An experimental procedure was conducted on a flexible beam structure with clamped-free boundary condition. The beam was forced to vibrate using an external force and a set of input-output vibration data was acquired. Using the input-output data, the flexible beam model was developed using Least Squares (LS) algorithm that incorporated the Auto Regressive (ARX) model structure. The AVC controllers developed are proportional-derivative (PD) and proportionalintegral-derivative (PID). The parameters of PD and PID controllers were tuned using iterative learning algorithm (ILA) and evolutionary Particle Swarm Optimization (PSO) techniques. Mean squared errors (MSE) were used to compare PSO tuned PD (PD-PSO), PSO tuned PID (PID-PSO) and PID with ILA (PID-ILA) controllers. It was found that the PID-ILA controller tuned using ILA had performed better than PID-PSO but PD-PSO is the best among the three controllers.
{"title":"Evolutionary algorithms for self-tuning Active Vibration Control of flexible beam","authors":"M. Fadil, I. Darus","doi":"10.1109/AUCC.2013.6697256","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697256","url":null,"abstract":"This paper presents the development of self tuning Active Vibration Control (AVC) strategy for flexible beam structure. An experimental procedure was conducted on a flexible beam structure with clamped-free boundary condition. The beam was forced to vibrate using an external force and a set of input-output vibration data was acquired. Using the input-output data, the flexible beam model was developed using Least Squares (LS) algorithm that incorporated the Auto Regressive (ARX) model structure. The AVC controllers developed are proportional-derivative (PD) and proportionalintegral-derivative (PID). The parameters of PD and PID controllers were tuned using iterative learning algorithm (ILA) and evolutionary Particle Swarm Optimization (PSO) techniques. Mean squared errors (MSE) were used to compare PSO tuned PD (PD-PSO), PSO tuned PID (PID-PSO) and PID with ILA (PID-ILA) controllers. It was found that the PID-ILA controller tuned using ILA had performed better than PID-PSO but PD-PSO is the best among the three controllers.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128384860","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697271
Shuma Nagaya, T. Morikawa, I. Takami, Gan Chen
In this study, we consider a controller of the parallel wheeled inverted pendulum named Beauto Balancer Duo. The mathematical model of the inverted pendulum is derived by using the Euler Lagrange formula. Kinetic coefficients of the motor are derived from a specification sheet. The inverted pendulum has an uncertain viscous friction coefficient around the wheel, that causes perturbation of the dynamics. Therefore, an upper bound and a lower bound of the viscous friction coefficient are estimated by several experiments. Two controllers are synthesized in order to compare by simulations and experiments. One controller provides optimal performance only for a nominal model, and other controller has a robustness for the range of the viscous friction coefficient. From comparing two controllers, an accuracy of the derived mathematical model and an accuracy of the estimated viscous friction coefficient are verified.
{"title":"Robust LQ control for parallel wheeled inverted pendulum","authors":"Shuma Nagaya, T. Morikawa, I. Takami, Gan Chen","doi":"10.1109/AUCC.2013.6697271","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697271","url":null,"abstract":"In this study, we consider a controller of the parallel wheeled inverted pendulum named Beauto Balancer Duo. The mathematical model of the inverted pendulum is derived by using the Euler Lagrange formula. Kinetic coefficients of the motor are derived from a specification sheet. The inverted pendulum has an uncertain viscous friction coefficient around the wheel, that causes perturbation of the dynamics. Therefore, an upper bound and a lower bound of the viscous friction coefficient are estimated by several experiments. Two controllers are synthesized in order to compare by simulations and experiments. One controller provides optimal performance only for a nominal model, and other controller has a robustness for the range of the viscous friction coefficient. From comparing two controllers, an accuracy of the derived mathematical model and an accuracy of the estimated viscous friction coefficient are verified.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133701931","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697283
A. Farhadi, P. Dower, M. Cantoni
This paper compares the computation time of two algorithms for solving a structured constrained linear optimal control problem with finite horizon quadratic cost within the context of automated irrigation networks. The first is a standard centralized algorithm based on the active set method that does not exploit problem structure. The second is distributed and is based on a consensus algorithm, not specifically tailored to account for system structure. It is shown that there is a significant advantage in terms of computation overhead (the time spent computing the optimal solution) in using the second algorithm in large-scale networks. Specifically, for a fixed horizon length the computation overhead of the centralized algorithm grows as O(n5) with the number n of sub-systems. By contrast, it is observed via a combination of analysis and experiment that given n times resources for computation the computation overhead of the distributed algorithm grows as O(n) with the number n of sub-systems.
{"title":"Computation time analysis of centralized and distributed optimization algorithms applied to automated irrigation networks","authors":"A. Farhadi, P. Dower, M. Cantoni","doi":"10.1109/AUCC.2013.6697283","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697283","url":null,"abstract":"This paper compares the computation time of two algorithms for solving a structured constrained linear optimal control problem with finite horizon quadratic cost within the context of automated irrigation networks. The first is a standard centralized algorithm based on the active set method that does not exploit problem structure. The second is distributed and is based on a consensus algorithm, not specifically tailored to account for system structure. It is shown that there is a significant advantage in terms of computation overhead (the time spent computing the optimal solution) in using the second algorithm in large-scale networks. Specifically, for a fixed horizon length the computation overhead of the centralized algorithm grows as O(n5) with the number n of sub-systems. By contrast, it is observed via a combination of analysis and experiment that given n times resources for computation the computation overhead of the distributed algorithm grows as O(n) with the number n of sub-systems.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"689 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122703794","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697244
O. Techakesari, T. Bruggemann, J. Ford
The low-altitude aircraft inspection of powerlines, or other linear infrastructure networks, is emerging as an important application requiring specialised control technologies. Despite some recent advances in automated control related to this application, control of the underactuated aircraft vertical dynamics has not been completely achieved, especially in the presence of thermal disturbances. Rejection of thermal disturbances represents a key challenge to the control of inspection aircraft due to the underactuated nature of the dynamics and specified speed, altitude, and pitch constraints. This paper proposes a new vertical controller consisting of a backstepping elevator controller with feedforward-feedback throttle controller. The performance of our proposed approach is evaluated against two existing candidate controllers.
{"title":"Control of infrastructure inspection aircraft vertical dynamics in the presence of thermal disturbances","authors":"O. Techakesari, T. Bruggemann, J. Ford","doi":"10.1109/AUCC.2013.6697244","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697244","url":null,"abstract":"The low-altitude aircraft inspection of powerlines, or other linear infrastructure networks, is emerging as an important application requiring specialised control technologies. Despite some recent advances in automated control related to this application, control of the underactuated aircraft vertical dynamics has not been completely achieved, especially in the presence of thermal disturbances. Rejection of thermal disturbances represents a key challenge to the control of inspection aircraft due to the underactuated nature of the dynamics and specified speed, altitude, and pitch constraints. This paper proposes a new vertical controller consisting of a backstepping elevator controller with feedforward-feedback throttle controller. The performance of our proposed approach is evaluated against two existing candidate controllers.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128637736","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697259
Chunlin Chen, Ruixing Long, B. Qi, D. Dong
Robust control design is a central problem for quantum systems in practical implementation and applications. In this paper, we formulate the control problem of a quantum system with bounded uncertainties as the problem of steering this system to a target state with bounded controls via an optimized evolution path to achieve a satisfactory level of fidelity. To find the optimized path (controls), we present a combined design method of sampling-based learning control and path planning. The numerical results on an example of a four-level quantum system show the effectiveness of the proposed learning control design method.
{"title":"Sampling-based learning control of quantum systems with bounded inputs and uncertainties via path planning","authors":"Chunlin Chen, Ruixing Long, B. Qi, D. Dong","doi":"10.1109/AUCC.2013.6697259","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697259","url":null,"abstract":"Robust control design is a central problem for quantum systems in practical implementation and applications. In this paper, we formulate the control problem of a quantum system with bounded uncertainties as the problem of steering this system to a target state with bounded controls via an optimized evolution path to achieve a satisfactory level of fidelity. To find the optimized path (controls), we present a combined design method of sampling-based learning control and path planning. The numerical results on an example of a four-level quantum system show the effectiveness of the proposed learning control design method.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"62 2-3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126966537","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697315
C. Hartung, G. Reissig, F. Svaricek
A linear time-invariant system of the form ẋ(t) = Ax(t) + Bu{t), or x(t + 1) = Ax(t) + Bu(t) is sign controllable if all linear time-invariant systems whose matrices A and B have the same sign pattern as A and B are controllable. This work characterizes the sign controllability for systems, whose sign pattern of A allows only real eigenvalues. Moreover, we present a combinatorial condition which is necessary for sign controllability and we show that if this condition is satisfied, then in all linear time-invariant systems with that sign pattern, all real eigenvalues of A are controllable. In addition, it is proven that the decision whether a linear time-invariant systems is not sign controllable is NP-complete. We want to emphasize, that our results cover the single and the multi-input case.
{"title":"Characterization of sign controllability for linear systems with real eigenvalues","authors":"C. Hartung, G. Reissig, F. Svaricek","doi":"10.1109/AUCC.2013.6697315","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697315","url":null,"abstract":"A linear time-invariant system of the form ẋ(t) = Ax(t) + Bu{t), or x(t + 1) = Ax(t) + Bu(t) is sign controllable if all linear time-invariant systems whose matrices A and B have the same sign pattern as A and B are controllable. This work characterizes the sign controllability for systems, whose sign pattern of A allows only real eigenvalues. Moreover, we present a combinatorial condition which is necessary for sign controllability and we show that if this condition is satisfied, then in all linear time-invariant systems with that sign pattern, all real eigenvalues of A are controllable. In addition, it is proven that the decision whether a linear time-invariant systems is not sign controllable is NP-complete. We want to emphasize, that our results cover the single and the multi-input case.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121886649","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697282
M. Fairbairn, Philipp Muller, S. Moheimani
The benefits of decreasing the quality (Q) factor of an Atomic Force Microscope (AFM) micro-cantilever, when operating in tapping mode, using passive piezoelectric shunt control have been previously demonstrated. A passive electrical impedance is placed in series with the cantilever oscillation voltage to control the Q factor of the cantilever. The amount of Q factor reduction obtainable using this method is limited due to the passive nature of the shunt impedance. This work demonstrates that further decreases in the cantilever Q factor may be obtained through the use of an active impedance. The active impedance is designed in such a way that the piezoelectric shunt controller emulates a PPF controller in a displacement feedback loop. The damping obtained with this controller is compared with the maximum damping obtainable with a passive impedance.
{"title":"Active piezoelectric shunt control of an Atomic Force Microscope micro-cantilever","authors":"M. Fairbairn, Philipp Muller, S. Moheimani","doi":"10.1109/AUCC.2013.6697282","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697282","url":null,"abstract":"The benefits of decreasing the quality (Q) factor of an Atomic Force Microscope (AFM) micro-cantilever, when operating in tapping mode, using passive piezoelectric shunt control have been previously demonstrated. A passive electrical impedance is placed in series with the cantilever oscillation voltage to control the Q factor of the cantilever. The amount of Q factor reduction obtainable using this method is limited due to the passive nature of the shunt impedance. This work demonstrates that further decreases in the cantilever Q factor may be obtained through the use of an active impedance. The active impedance is designed in such a way that the piezoelectric shunt controller emulates a PPF controller in a displacement feedback loop. The damping obtained with this controller is compared with the maximum damping obtainable with a passive impedance.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"2008 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113966653","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 : 2013-11-01DOI: 10.1109/AUCC.2013.6697258
T. Shiota, H. Ohmori
As one of the control schemes which overcome model uncertainty, there is a model reference adaptive control. In the conventional adaptive control method, the reference model is designed in advance. However, this reference model should also be essentially re-designed according to characteristic change of a controlled object. Therefore, in this paper, we propose an adaptive I-PD control scheme with variable reference model and show the validity by the numeric simulation.
{"title":"Design of adaptive I-PD control system with variable reference model","authors":"T. Shiota, H. Ohmori","doi":"10.1109/AUCC.2013.6697258","DOIUrl":"https://doi.org/10.1109/AUCC.2013.6697258","url":null,"abstract":"As one of the control schemes which overcome model uncertainty, there is a model reference adaptive control. In the conventional adaptive control method, the reference model is designed in advance. However, this reference model should also be essentially re-designed according to characteristic change of a controlled object. Therefore, in this paper, we propose an adaptive I-PD control scheme with variable reference model and show the validity by the numeric simulation.","PeriodicalId":177490,"journal":{"name":"2013 Australian Control Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114230730","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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