Pub Date : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628273
R. S. Filho, E. Boeira, L. Campestrini, D. Eckhard
This paper presents a new direct data-driven control method for the load disturbance problem in a Model Reference Matching framework. It consists in embedding the controller’s design under a prediction error approach, where a flexible reference model is also identified in order to guarantee the causality and stability of the ideal controller. Due to the complexity of the proposed approach, a dedicated iterative optimization algorithm is developed to properly solve the problem. Finally, the statistical properties of the obtained estimates are explored through simulation examples, where the enhancement obtained through the proposed methodology is compared to least-squares and instrumental variable solutions.
{"title":"Data-driven control design for load disturbance rejection by prediction error identification","authors":"R. S. Filho, E. Boeira, L. Campestrini, D. Eckhard","doi":"10.1109/anzcc53563.2021.9628273","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628273","url":null,"abstract":"This paper presents a new direct data-driven control method for the load disturbance problem in a Model Reference Matching framework. It consists in embedding the controller’s design under a prediction error approach, where a flexible reference model is also identified in order to guarantee the causality and stability of the ideal controller. Due to the complexity of the proposed approach, a dedicated iterative optimization algorithm is developed to properly solve the problem. Finally, the statistical properties of the obtained estimates are explored through simulation examples, where the enhancement obtained through the proposed methodology is compared to least-squares and instrumental variable solutions.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129943744","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628283
Wanjie Zhu, Jinde Cao, Xinli Shi
In this paper, the controllability of finite-field network (FFN) with single input is investigated through an algebra-theoretic perspective. An algebraic criterion on the matrix pair for controllability is derived, distinguishing FFNs from the classic real/complex-valued networks, and involving the algebraic structure caused by the system matrix pair. Basing on this, we further study a minimal controllability problem, i.e., finding a minimum number of agents to be affected by input, to make the system controllable. For FFN with single input, we present that the minimum number desired depends on the number of elementary divisors of the system matrix, if the given base satisfies certain condition. Meanwhile, we provide the corresponding method of constructing an optimal solution to the minimal controllability problem. In the end, we show that the set of all controllable pairs is dense in some sense by figuring the probability of the occurrence of a controllable pair.
{"title":"A Controllability Problem of Finite-Field Networks*","authors":"Wanjie Zhu, Jinde Cao, Xinli Shi","doi":"10.1109/anzcc53563.2021.9628283","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628283","url":null,"abstract":"In this paper, the controllability of finite-field network (FFN) with single input is investigated through an algebra-theoretic perspective. An algebraic criterion on the matrix pair for controllability is derived, distinguishing FFNs from the classic real/complex-valued networks, and involving the algebraic structure caused by the system matrix pair. Basing on this, we further study a minimal controllability problem, i.e., finding a minimum number of agents to be affected by input, to make the system controllable. For FFN with single input, we present that the minimum number desired depends on the number of elementary divisors of the system matrix, if the given base satisfies certain condition. Meanwhile, we provide the corresponding method of constructing an optimal solution to the minimal controllability problem. In the end, we show that the set of all controllable pairs is dense in some sense by figuring the probability of the occurrence of a controllable pair.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116523415","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628383
Muhammad Mudassar, Umair Zulfiqar, V. Sreeram, Muwahida Liaquat, A. Jazlan
A damping controller is essential for the smooth operation of power systems. Different types of disturbances result in low-frequency oscillations, which propagate in all the interconnected machines. A safe operation of an interconnected power system requires sufficient damping of these oscillations. Otherwise, there are high chances of blackouts. As the order of the interconnected power system model increases, the analytical controller design procedures result in a high-order controller, which is impractical to implement. In this paper, we demonstrate that the frequency-weighted model order reduction can be used to effectively design a reduced-order loop shaping damping controller. To that end, we design an ${mathcal{H}_infty }$ damping controller for the interconnection of the New England test system (NETS) with the New York power system (NYPS) with an additional constraint of pole-placement. The time-domain simulations of disturbed system with and without controller are performed using MATLAB. Results show that the designed controller successfully removes the low frequency oscillations, maintains synchronism among generators, and guarantees the stability of the power system.
{"title":"Reduced-order Damping Controller Design for Power Systems via Frequency-weighted Model Reduction","authors":"Muhammad Mudassar, Umair Zulfiqar, V. Sreeram, Muwahida Liaquat, A. Jazlan","doi":"10.1109/anzcc53563.2021.9628383","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628383","url":null,"abstract":"A damping controller is essential for the smooth operation of power systems. Different types of disturbances result in low-frequency oscillations, which propagate in all the interconnected machines. A safe operation of an interconnected power system requires sufficient damping of these oscillations. Otherwise, there are high chances of blackouts. As the order of the interconnected power system model increases, the analytical controller design procedures result in a high-order controller, which is impractical to implement. In this paper, we demonstrate that the frequency-weighted model order reduction can be used to effectively design a reduced-order loop shaping damping controller. To that end, we design an ${mathcal{H}_infty }$ damping controller for the interconnection of the New England test system (NETS) with the New York power system (NYPS) with an additional constraint of pole-placement. The time-domain simulations of disturbed system with and without controller are performed using MATLAB. Results show that the designed controller successfully removes the low frequency oscillations, maintains synchronism among generators, and guarantees the stability of the power system.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"13 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116812475","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628253
Zhengkun Shang, Yuqing Qin, Yudong Wang, Fei Li, H. Shen, Jing Wang
Performance indicators are suitable for the environmental selection in evolutionary multi-objective evolutionary algorithms (EAs). Balancing convergence and diversity is very important for performance indicators based evolutionary algorithms. Recently, the modified inverted generational distance, named IGD+ indicator, is popular to solve optimization problems with two or three objectives due to its better characteristics that the indicator can obtain the weak Pareto dominance solutions. However, only adopting the selection mechanism based on the IGD+ indicator in high dimensional objective space, is no longer enough to guarantee the candidate solutions a good diversity. In order to address this issue, we employ the reference vector to assist the IGD+ indicator for solving many-objective EAs. It is the first time to combine the IGD+ indicator and the selection based on the objective space partition. Experimental results have been conducted on the DTLZ test instances which show that our algorithm has achieved a competitive performance for multi-objective and many-objective optimization.
{"title":"The IGD+ Indicator and Reference Vector Guided Evolutionary Algorithm for Many-objective Optimization Problems","authors":"Zhengkun Shang, Yuqing Qin, Yudong Wang, Fei Li, H. Shen, Jing Wang","doi":"10.1109/anzcc53563.2021.9628253","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628253","url":null,"abstract":"Performance indicators are suitable for the environmental selection in evolutionary multi-objective evolutionary algorithms (EAs). Balancing convergence and diversity is very important for performance indicators based evolutionary algorithms. Recently, the modified inverted generational distance, named IGD+ indicator, is popular to solve optimization problems with two or three objectives due to its better characteristics that the indicator can obtain the weak Pareto dominance solutions. However, only adopting the selection mechanism based on the IGD+ indicator in high dimensional objective space, is no longer enough to guarantee the candidate solutions a good diversity. In order to address this issue, we employ the reference vector to assist the IGD+ indicator for solving many-objective EAs. It is the first time to combine the IGD+ indicator and the selection based on the objective space partition. Experimental results have been conducted on the DTLZ test instances which show that our algorithm has achieved a competitive performance for multi-objective and many-objective optimization.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126655838","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628238
V. L. B. Tuan, A. Hajjaji, O. Pagès
This paper addresses the regional stability and performance of anti-windup compensators for linear control systems in the presence of external disturbances. Based on the dynamic controller and compensator structure analysis for the saturated system, the non-convex stabilization design problems are converted to LMIs conditions by congruence transformation. Then, the stability condition is reinforced by using a new approach two-step stabilizing via algebraic constraints involved in the unbiased erroneous inverse compensation. The dynamic output controller and anti-windup gains achieve at the desired level of ℒ2-norm performance by set feasible solutions. A numerical example demonstrates the effectiveness of the proposed methodology.
{"title":"ℒ2-Stabilization of anti-windup compensators subject to actuator saturation and disturbances","authors":"V. L. B. Tuan, A. Hajjaji, O. Pagès","doi":"10.1109/anzcc53563.2021.9628238","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628238","url":null,"abstract":"This paper addresses the regional stability and performance of anti-windup compensators for linear control systems in the presence of external disturbances. Based on the dynamic controller and compensator structure analysis for the saturated system, the non-convex stabilization design problems are converted to LMIs conditions by congruence transformation. Then, the stability condition is reinforced by using a new approach two-step stabilizing via algebraic constraints involved in the unbiased erroneous inverse compensation. The dynamic output controller and anti-windup gains achieve at the desired level of ℒ2-norm performance by set feasible solutions. A numerical example demonstrates the effectiveness of the proposed methodology.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131543971","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628339
P. Pham, Gyoung-Hahn Kim, Q. Nguyen, K. Hong
This paper investigates the vibration control of a Cartesian robot consisting of a trolley and a flexible robotic arm, wherein the robotic arm is treated as an axially moving Timoshenko beam with time-varying length. A mathematical model describing the dynamics of the trolley and the beam is established based on the extended Hamilton principle. According to this dynamic model, a boundary control law is proposed to suppress the undesired transverse vibration of the beam. The stability of the closed-loop system is verified by using the Lyapunov method. Through simulation, the system’s performance under the proposed control law is demonstrated, and the impressive efficiency of the control law is also shown.
{"title":"Control of an Axially Moving Timoshenko Beam Attached to a Moving Base","authors":"P. Pham, Gyoung-Hahn Kim, Q. Nguyen, K. Hong","doi":"10.1109/anzcc53563.2021.9628339","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628339","url":null,"abstract":"This paper investigates the vibration control of a Cartesian robot consisting of a trolley and a flexible robotic arm, wherein the robotic arm is treated as an axially moving Timoshenko beam with time-varying length. A mathematical model describing the dynamics of the trolley and the beam is established based on the extended Hamilton principle. According to this dynamic model, a boundary control law is proposed to suppress the undesired transverse vibration of the beam. The stability of the closed-loop system is verified by using the Lyapunov method. Through simulation, the system’s performance under the proposed control law is demonstrated, and the impressive efficiency of the control law is also shown.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130444664","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628225
Kishore Bingi, P. Devan, F. Hussin
In this paper, a forecasting model using recur-rent neural networks (RNN) for reconstructing the chaotic fractional-order Tamaševičius system states has been developed. The attractiveness of the proposed model is in the developed relationships between inputs, which are state variables, and outputs, which are the change in state variables for accurate prediction. The results from the proposed model show the best prediction ability for all three output variables with the highest R2 and the least mean square errors. The proposed forecasting model also performs best in reconstructing all three system states with minimal mean square errors.
{"title":"Reconstruction of Chaotic Attractor for Fractional-order Tamaševičius System Using Recurrent Neural Networks","authors":"Kishore Bingi, P. Devan, F. Hussin","doi":"10.1109/anzcc53563.2021.9628225","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628225","url":null,"abstract":"In this paper, a forecasting model using recur-rent neural networks (RNN) for reconstructing the chaotic fractional-order Tamaševičius system states has been developed. The attractiveness of the proposed model is in the developed relationships between inputs, which are state variables, and outputs, which are the change in state variables for accurate prediction. The results from the proposed model show the best prediction ability for all three output variables with the highest R2 and the least mean square errors. The proposed forecasting model also performs best in reconstructing all three system states with minimal mean square errors.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120913421","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628194
N. Snehal, W. Pooja, K. Sonam, S. Wagh, N. Singh
Reinforcement learning with probabilistic policy search method is used in this paper for controlling an Acrobot system. Reinforcement learning with probabilistic policy search is a technique that is data-efficient and based on a model. Model bias is one of the main reasons for not using methods which are based on the model to learn from scratch. The model bias is not a severe problem in reinforcement learning with probabilistic policy search as it uses the Gaussian process which considers model uncertainty. Reinforcement learning with probabilistic policy search has the ability to give the best results even when very less data is available. The state of the art approximate inference is used for policy evaluation and for policy improvement. Policy gradients are calculated analytically.
{"title":"Control of an Acrobot system using reinforcement learning with probabilistic policy search","authors":"N. Snehal, W. Pooja, K. Sonam, S. Wagh, N. Singh","doi":"10.1109/anzcc53563.2021.9628194","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628194","url":null,"abstract":"Reinforcement learning with probabilistic policy search method is used in this paper for controlling an Acrobot system. Reinforcement learning with probabilistic policy search is a technique that is data-efficient and based on a model. Model bias is one of the main reasons for not using methods which are based on the model to learn from scratch. The model bias is not a severe problem in reinforcement learning with probabilistic policy search as it uses the Gaussian process which considers model uncertainty. Reinforcement learning with probabilistic policy search has the ability to give the best results even when very less data is available. The state of the art approximate inference is used for policy evaluation and for policy improvement. Policy gradients are calculated analytically.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130214150","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628201
Kazuhiko Takahashi, Sora Shibata, M. Hashimoto
This study investigates the learning capability of a quaternion recurrent neural network that is trained based on a backpropagation through time algorithm extended to quaternion numbers. Computational experiments to identify nonlinear systems, e.g. a three–dimensional chaotic system and discrete–time plant, were performed, and the simulation results confirmed the feasibility of using the quaternion recurrent neural network for a control system application.
{"title":"Remarks on System Identification Using a Quaternion Recurrent Neural Network Trained by Backpropagation through Time","authors":"Kazuhiko Takahashi, Sora Shibata, M. Hashimoto","doi":"10.1109/anzcc53563.2021.9628201","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628201","url":null,"abstract":"This study investigates the learning capability of a quaternion recurrent neural network that is trained based on a backpropagation through time algorithm extended to quaternion numbers. Computational experiments to identify nonlinear systems, e.g. a three–dimensional chaotic system and discrete–time plant, were performed, and the simulation results confirmed the feasibility of using the quaternion recurrent neural network for a control system application.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133682275","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 : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628289
Hao Zhang, Jesse Cranney, D. Gratadour, N. Doucet, F. Rigaut
Large optical telescopes depend on adaptive optics for the real-time compensation of turbulence-induced wavefront aberrations. The performance of laser guide star based Multi-Conjugate Adaptive Optics systems is degraded by tilt anisoplanatism. In this paper we propose and derive a method for mitigating this effect, achieved by merging the measurements of natural and laser guide stars together. This method performs a modal reconstruction of the field dependent Tip-Tilt aberration that is not sensed by the high order laser guide stars. The proposed method benefits from its (i) reduced computational load, (ii) compatibility with predictive control schemes, and (iii) improved uniformity of image quality over the whole science field of view. End-to-end numerical simulations are used to demonstrate the performance of the slope merging method in modern Adaptive Optics systems.
{"title":"Mitigating Tilt Anisoplanatism with the Slope Merging Method for Multi-Conjugate Adaptive Optics Systems","authors":"Hao Zhang, Jesse Cranney, D. Gratadour, N. Doucet, F. Rigaut","doi":"10.1109/anzcc53563.2021.9628289","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628289","url":null,"abstract":"Large optical telescopes depend on adaptive optics for the real-time compensation of turbulence-induced wavefront aberrations. The performance of laser guide star based Multi-Conjugate Adaptive Optics systems is degraded by tilt anisoplanatism. In this paper we propose and derive a method for mitigating this effect, achieved by merging the measurements of natural and laser guide stars together. This method performs a modal reconstruction of the field dependent Tip-Tilt aberration that is not sensed by the high order laser guide stars. The proposed method benefits from its (i) reduced computational load, (ii) compatibility with predictive control schemes, and (iii) improved uniformity of image quality over the whole science field of view. End-to-end numerical simulations are used to demonstrate the performance of the slope merging method in modern Adaptive Optics systems.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"190 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114746863","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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