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2023 American Control Conference (ACC)最新文献

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Attacker-Resilient Adaptive Path Following of a Quadrotor with Dynamic Path-Dependent Constraints 具有动态路径依赖约束的四旋翼飞行器攻击者弹性自适应路径跟踪
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156266
Xu Jin, Zhongjun Hu
{"title":"Attacker-Resilient Adaptive Path Following of a Quadrotor with Dynamic Path-Dependent Constraints","authors":"Xu Jin, Zhongjun Hu","doi":"10.23919/ACC55779.2023.10156266","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156266","url":null,"abstract":"For most works on constrained motion control in the literature, only constant or time-varying constraints are discussed, which are often conservative and cannot adapt to the dynamically changing operation environment. In this work, in the context of quadrotor operations, we propose a new adaptive path following architecture with dynamic path-dependent constraints, in which the desired path coordinate, desired path speed, and constraint requirements not only depend on a path parameter associated with the desired path, but also can adapt to the presence of an \"attacker\" nearby. A new concept of \"composite barrier function\" has been proposed to address both safety and performance constraints in a unified structure. Adaptive laws are introduced to estimate the upper bounds of system uncertainties and unknown \"attacker\" velocity. Exponential convergence into a small neighborhood around the equilibrium for position tracking error can be guaranteed. In the end, a simulation example further demonstrates the effectiveness of the proposed architecture.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130619127","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}
引用次数: 0
Transfer Learning-Based Modeling and Predictive Control of Nonlinear Processes 基于迁移学习的非线性过程建模与预测控制
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156613
Ming Xiao, Cheng Hu, Zhe Wu
{"title":"Transfer Learning-Based Modeling and Predictive Control of Nonlinear Processes","authors":"Ming Xiao, Cheng Hu, Zhe Wu","doi":"10.23919/ACC55779.2023.10156613","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156613","url":null,"abstract":"This work develops a transfer learning (TL) framework for modeling nonlinear dynamic systems using recurrent neural networks (RNNs). The TL-based RNN models are then incorporated into the design of model predictive control (MPC) systems. Specifically, transfer learning uses a pre-trained model developed based on a source domain as the starting point, and adapts the model to a target domain with similar data distribution. The generalization error for TLbased RNNs (TL-RNNs) that depends on model capacity and discrepancy between source and target domains is first derived to demonstrate the generalization capability on target process. Subsequently, the TL-RNN model is utilized as the prediction model in MPC for the target process. Finally, a chemical process example is used to demonstrate the benefits of transfer learning.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"284 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132160901","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}
引用次数: 0
Decentralized Multi-Agent Motion Planning in Dynamic Environments 动态环境下的分散多智能体运动规划
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156024
Josh Netter, K. Vamvoudakis
{"title":"Decentralized Multi-Agent Motion Planning in Dynamic Environments","authors":"Josh Netter, K. Vamvoudakis","doi":"10.23919/ACC55779.2023.10156024","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156024","url":null,"abstract":"In this paper we present a decentralized multi-agent motion planning algorithm for navigation in dynamic environments. Each agent constructs a graph of boundary value problems in the environment considering their own kinodynamic constraints using a learning-based motion planning framework. A game-theoretic approach is then used by each agent to select their individual path through the environment while considering the planned motion of other agents. This path is updated online to ensure collisions are avoided, and to provide a method of counteracting the freezing robot problem. The effectiveness of the algorithm is illustrated in simulations.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131300314","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}
引用次数: 0
Multiscale modeling, experimental validation, and optimal operation for a batch pulp digester with a novel solvent 多尺度建模，实验验证，并与一种新型溶剂间歇式纸浆消化池的优化操作
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10155797
Silabrata Pahari, Juhyeon Kim, Mairui Zhang, Anqi Ji, Changjin Yoo, J. Kwon
{"title":"Multiscale modeling, experimental validation, and optimal operation for a batch pulp digester with a novel solvent","authors":"Silabrata Pahari, Juhyeon Kim, Mairui Zhang, Anqi Ji, Changjin Yoo, J. Kwon","doi":"10.23919/ACC55779.2023.10155797","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10155797","url":null,"abstract":"The rising need for reducing the usage and wastage of paper has mandated the production of mechanically superior papers, and it is known that maintaining a high degree of polymerization (DP) for cellulose microfibers ensures the high tensile strength of the pulp. To mitigate the cellulose degradation and establish the optimum operating strategies of the pulping processes, it is necessary to understand the effect of the operation conditions on cellulose DP. In this sense, we proposed a novel multiscale model which can predict the mesoscopic properties (e.g., Kappa number, and fiber morphology) alongside the microscopic properties (e.g., cellulose DP). The model incorporates a multi-layered kinetic Monte Carlo (kMC) framework that allows us to capture the temporal evolution of Kappa number, fiber morphology, and cellulose DP in a computationally tractable fashion. Furthermore, the model predictions are validated with the experimental results, which are then used to find an optimal operation profile to achieve desired Kappa number and cellulose DP.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131651314","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}
引用次数: 0
Vessel Inspection In-the-wild: Practical Planning in Large-scale Industrial Environments 野外船舶检验:大规模工业环境下的实际规划
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10155874
Jakob Grimm Hansen, M. Heiss, Dengyun Li, Michał Kozłowski, E. Kayacan
{"title":"Vessel Inspection In-the-wild: Practical Planning in Large-scale Industrial Environments","authors":"Jakob Grimm Hansen, M. Heiss, Dengyun Li, Michał Kozłowski, E. Kayacan","doi":"10.23919/ACC55779.2023.10155874","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10155874","url":null,"abstract":"In this paper, a novel strategy for practical inspection planning in dry docks using unmanned aerial vehicles (UAVs) is presented. Planning is a fundamental prerequisite for accurate navigation and control of the UAV. The proposed method utilises the random sample consensus (RANSAC) algorithm to extract plane models from a voxel grid representation of the environment. For high-level planning, semantic knowledge of the environment is leveraged in a novel manner to exploit of structured obstacles, such as straight walls and orthogonal corners. In order to deal with lower-level navigation, the approach incorporates a simple graph-based local replanner to generate paths that avoid obstacles in the environment. The proposed method is compared with state-of-the-art graph-based planner in simulation and subsequently evaluated in a real environment. The paper maintains the use case of UAV vessel inspection and presents exhaustive simulation and field testing, which demonstrate the viability of the proposed approach in a fully working large-scale industrial environment.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129263543","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}
引用次数: 1
MPC with Integrated Evasive Maneuvers for Failure-safe Automated Driving 集成规避机动的MPC故障安全自动驾驶
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156177
Terrence Skibik, Abraham P. Vinod, A. Weiss, S. D. Cairano
{"title":"MPC with Integrated Evasive Maneuvers for Failure-safe Automated Driving","authors":"Terrence Skibik, Abraham P. Vinod, A. Weiss, S. D. Cairano","doi":"10.23919/ACC55779.2023.10156177","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156177","url":null,"abstract":"Automated vehicles may encounter non-nominal situations called failure scenarios, due for instance to errors in perception or environment prediction. In some failure scenarios, a risk area must suddenly be avoided, possibly at the price of no longer satisfying all the constraints enforced in nominal driving conditions. We propose a design for a failure-safe controller that operates the vehicle according to the specifications in nominal conditions, while ensuring that, should a known failure occur, an evasive maneuver can be performed that avoids the risk area and satisfies a possibly relaxed set of driving constraints. We design evasive maneuver controllers parametrized in their reference, and we leverage set based methods to determine the region where such controllers satisfy the constraints and avoid the risk area. Membership in such a region during nominal operation is achieved by imposing additional constraints on the controller for nominal driving. We demonstrate the approach in simulations in a few different scenarios.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123368011","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}
引用次数: 0
Plenary and Semi-Plenary Sessions 全体会议和半全体会议
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156471
{"title":"Plenary and Semi-Plenary Sessions","authors":"","doi":"10.23919/ACC55779.2023.10156471","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156471","url":null,"abstract":"","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126346665","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}
引用次数: 0
A Reduced Order Iterative Linear Quadratic Regulator (ILQR) Technique for the Optimal Control of Nonlinear Partial Differential Equations 非线性偏微分方程最优控制的降阶迭代线性二次调节器(ILQR)技术
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156062
Aayushman Sharma, S. Chakravorty
{"title":"A Reduced Order Iterative Linear Quadratic Regulator (ILQR) Technique for the Optimal Control of Nonlinear Partial Differential Equations","authors":"Aayushman Sharma, S. Chakravorty","doi":"10.23919/ACC55779.2023.10156062","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156062","url":null,"abstract":"In this paper, we introduce a reduced order Iterative Linear Quadratic Regulator (RO-ILQR) approach for the optimal control of nonlinear Partial Differential Equations (PDE). The approach proposes a novel modification of the ILQR technique: it uses the Method of Snapshots to identify a reduced order Linear Time Varying (LTV) approximation of the nonlinear PDE dynamics around a current estimate of the optimal trajectory, utilizes the identified LTV model to solve a time varying reduced order LQR problem to obtain an improved estimate of the optimal trajectory along with a new reduced basis, and iterates till convergence. The proposed approach is tested on the viscous Burger’s equation and two phase field models for microstructure evolution in materials, and the results show that there is a significant reduction in the computational burden over the standard ILQR approach, without sacrificing performance.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126072341","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}
引用次数: 0
Radar Based Wake Control for Reducing the Levelized Cost of Energy in Offshore Wind Farms* 基于雷达的尾流控制降低海上风电场能源平准化成本*
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10155955
F. D'Amato, George I. Boutselis, P. Bonanni, W. Szczepanski, R. López-Negrete
{"title":"Radar Based Wake Control for Reducing the Levelized Cost of Energy in Offshore Wind Farms*","authors":"F. D'Amato, George I. Boutselis, P. Bonanni, W. Szczepanski, R. López-Negrete","doi":"10.23919/ACC55779.2023.10155955","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10155955","url":null,"abstract":"Wake controls in wind farms has evolved significantly in the last twenty years, motivated mainly by its potential to increase annual energy production (AEP) through reduction of wake losses. Engineering models that characterize the wakes in the farm have enhanced fidelity and computational efficiency. Computational environments have been developed to adjust turbine control settings based on these models to reduce the impact of wakes. Several experimental campaigns have been carried out to validate the computational predictions. Yet, experimental results have typically shown lower AEP gains than expected. The variability in wake characteristics and the inability to calculate them online are key factors limiting the practical value of existing wake control solutions.This work presents a wake control approach that proposes new sensors to measure the wakes online and uses accurate wake characteristics to enable further energy capture in off-shore wind farms. A network of low-cost radar sensors is specifically designed to detect wakes in wind farms. A model-based estimation approach is developed to reduce the online wake uncertainty. Then, a model-based optimization framework is used to calculate AEP gains achieved by steering wakes via yaw actuation. The feasibility of the proposed approach is assessed by quantifying the changes in the levelized cost of energy (LCOE) resulting from the additional AEP gains and the extra cost of the new sensors.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"20 11","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120917672","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}
引用次数: 0
Amplification of noisy gene expression by protein burden: An analytical approach 蛋白负荷扩增噪声基因表达:一种分析方法
2023 American Control Conference (ACC) Pub Date : 2023-05-31 DOI: 10.23919/ACC55779.2023.10156378
Iryna Zabaikina, Zhanhao Zhang, César Nieto, Pavol Bokes, Abhyudai Singh
{"title":"Amplification of noisy gene expression by protein burden: An analytical approach","authors":"Iryna Zabaikina, Zhanhao Zhang, César Nieto, Pavol Bokes, Abhyudai Singh","doi":"10.23919/ACC55779.2023.10156378","DOIUrl":"https://doi.org/10.23919/ACC55779.2023.10156378","url":null,"abstract":"The overexpression of many proteins can often have a detrimental impact on cellular growth. This expression-growth coupling leads to positive feedback - any increase of intracellular protein concentration reduces the growth rate of cell size expansion that in turn enhances the concentration via reduced dilution. We investigate how such feedback amplifies intrinsic stochasticity in gene expression to drive a skewed distribution of the protein concentration. Our research provides the analytical expression of the distribution after solving the associated Chapman-Kolmogorov equation. With these results, we quantify the enhancement of noise/skewness as a function of expression-growth coupling. This analysis has important implications for the expression of stress factors, where high levels provide protection from stress, but come at the cost of reduced cellular proliferation. Finally, we connect these analytical results to the case of an actively degraded gene product, where the degradation machinery is working close to saturation.","PeriodicalId":397401,"journal":{"name":"2023 American Control Conference (ACC)","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121800350","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}
引用次数: 0
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