Pub Date : 2021-11-25DOI: 10.1109/anzcc53563.2021.9628236
Yamin Yan, S. Stüdli, M. Seron, R. Middleton
Grounding of a node in a consensus network is a disruption by which the grounded node is no longer affected by other agents but it continues to influence the network, possibly in harmful ways. Indeed, grounding may cause consensus networks to have undesirable consensus performance or even unconsensusability. One possible countermeasure was recently proposed to recover from the effect of grounding by additionally grounding more nodes. In this paper, we further study the selection criteria for additional nodes to ground as a countermeasure in order to recover the consensus performance. Two effective and computationally efficient algorithms are proposed to assist in the selection of the additional nodes to ground.
{"title":"On Grounding Additional Nodes in a Grounded Consensus Network *","authors":"Yamin Yan, S. Stüdli, M. Seron, R. Middleton","doi":"10.1109/anzcc53563.2021.9628236","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628236","url":null,"abstract":"Grounding of a node in a consensus network is a disruption by which the grounded node is no longer affected by other agents but it continues to influence the network, possibly in harmful ways. Indeed, grounding may cause consensus networks to have undesirable consensus performance or even unconsensusability. One possible countermeasure was recently proposed to recover from the effect of grounding by additionally grounding more nodes. In this paper, we further study the selection criteria for additional nodes to ground as a countermeasure in order to recover the consensus performance. Two effective and computationally efficient algorithms are proposed to assist in the selection of the additional nodes to ground.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"20 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":"123416011","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 : 2021-08-29DOI: 10.1109/ANZCC53563.2021.9628258
Subhransu S. Bhattacharjee, I. Petersen
We introduce a novel adaptive damping technique for an inertial gradient system which finds application as a gradient descent algorithm for unconstrained optimisation. In an example using the non-convex Rosenbrock’s function, we show an improvement on existing momentum-based gradient optimisation methods. Also using Lyapunov stability analysis, we demonstrate the performance of the continuous-time version of the algorithm. Using numerical simulations, we consider the performance of its discrete-time counterpart obtained by using the symplectic Euler method of discretisation.
{"title":"A Closed Loop Gradient Descent Algorithm applied to Rosenbrock’s function","authors":"Subhransu S. Bhattacharjee, I. Petersen","doi":"10.1109/ANZCC53563.2021.9628258","DOIUrl":"https://doi.org/10.1109/ANZCC53563.2021.9628258","url":null,"abstract":"We introduce a novel adaptive damping technique for an inertial gradient system which finds application as a gradient descent algorithm for unconstrained optimisation. In an example using the non-convex Rosenbrock’s function, we show an improvement on existing momentum-based gradient optimisation methods. Also using Lyapunov stability analysis, we demonstrate the performance of the continuous-time version of the algorithm. Using numerical simulations, we consider the performance of its discrete-time counterpart obtained by using the symplectic Euler method of discretisation.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"117 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129136916","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 : 2021-01-31DOI: 10.1109/anzcc53563.2021.9628202
Xun Liu, H. Rastgoftar
This paper develops a conservation-based approach to model traffic dynamics and alleviate traffic congestion in a network of interconnected roads (NOIR). We generate a NOIR by using the Simulation of Urban Mobility (SUMO) software based on the real street map of Philadelphia Center City. The NOIR is then represented by a directed graph with nodes identifying distinct streets in the Center City area. By classifying the streets as inlets, outlets, and interior nodes, the model predictive control (MPC) method is applied to alleviate the network traffic congestion by optimizing the traffic inflow and outflow across the boundary of the NOIR with consideration of the inner traffic dynamics as a stochastic process. The proposed boundary control problem is defined as a quadratic programming problem with constraints imposing the feasibility of traffic coordination, and a cost function defined based on the traffic density across the NOIR.
{"title":"Conservation-Based Modeling and Boundary Control of Congestion with an Application to Traffic Management in Center City Philadelphia","authors":"Xun Liu, H. Rastgoftar","doi":"10.1109/anzcc53563.2021.9628202","DOIUrl":"https://doi.org/10.1109/anzcc53563.2021.9628202","url":null,"abstract":"This paper develops a conservation-based approach to model traffic dynamics and alleviate traffic congestion in a network of interconnected roads (NOIR). We generate a NOIR by using the Simulation of Urban Mobility (SUMO) software based on the real street map of Philadelphia Center City. The NOIR is then represented by a directed graph with nodes identifying distinct streets in the Center City area. By classifying the streets as inlets, outlets, and interior nodes, the model predictive control (MPC) method is applied to alleviate the network traffic congestion by optimizing the traffic inflow and outflow across the boundary of the NOIR with consideration of the inner traffic dynamics as a stochastic process. The proposed boundary control problem is defined as a quadratic programming problem with constraints imposing the feasibility of traffic coordination, and a cost function defined based on the traffic density across the NOIR.","PeriodicalId":246687,"journal":{"name":"2021 Australian & New Zealand Control Conference (ANZCC)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121347752","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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