European Journal of Control最新文献

A comparative study of sensitivity computations in ESDIRK-based optimal control problems 基于 ESDIRK 的最优控制问题中灵敏度计算的比较研究

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101064

Anders Hilmar Damm Christensen, John Bagterp Jørgensen

{"title":"A comparative study of sensitivity computations in ESDIRK-based optimal control problems","authors":"Anders Hilmar Damm Christensen, John Bagterp Jørgensen","doi":"10.1016/j.ejcon.2024.101064","DOIUrl":"10.1016/j.ejcon.2024.101064","url":null,"abstract":"<div><div>This paper compares the impact of iterated and direct approaches to sensitivity computation in fixed step-size explicit singly diagonally implicit Runge–Kutta (ESDIRK) methods when applied to optimal control problems (OCPs). We strictly use the principle of internal numerical differentiation (IND) for the iterated approach, i.e., reusing iteration matrix factorizations, the number of Newton-type iterations, and Newton iterates, to compute the sensitivities. The direct method computes the sensitivities without using the Newton schemes. We compare the impact of these sensitivity computations in OCPs for the quadruple tank system (QTS). We discretize the OCPs using multiple shooting and solve these with a sequential quadratic programming (SQP) solver. We benchmark the iterated and direct approaches against a base case. This base case applies the ESDIRK methods with exact Newton schemes and a direct approach for sensitivity computations. In these OCPs, we vary the number of integration steps between control intervals and evaluate the performance based on the number of SQP and QPs iterations, KKT violations, function evaluations, Jacobian updates, and iteration matrix factorizations. We also provide examples using the continuous-stirred tank reactor (CSTR), and the IPOPT algorithm instead of the SQP. For OCPs solved using SQP, the QTS results show the direct method converges only once, while the iterated approach and base case converges in all situations. Similar results are seen with the CSTR. Using IPOPT, both the iterated approach and base case converge in all cases. In contrast, the direct method only converges in all cases regarding the CSTR.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101064"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Nonlinear model predictive control based on K-step control invariant sets 基于 K 步控制不变集的非线性模型预测控制

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101040

Zhixin Zhao, Antoine Girard, Sorin Olaru

{"title":"Nonlinear model predictive control based on K-step control invariant sets","authors":"Zhixin Zhao, Antoine Girard, Sorin Olaru","doi":"10.1016/j.ejcon.2024.101040","DOIUrl":"10.1016/j.ejcon.2024.101040","url":null,"abstract":"<div><div><span><span>One of the fundamental issues in Nonlinear Model Predictive Control (NMPC) is to be able to guarantee the recursive feasibility of the underlying receding horizon optimization. In other terms, the primary condition for a safe NMPC design is to ensure that the closed-loop solution remains indefinitely within the feasible set of the optimization problem. This issue can be addressed by introducing a terminal constraint described in terms of a control invariant set. However, the control invariant sets of </span>nonlinear systems are often impractical to use or even to construct due to their complexity. The </span><span><math><mi>K</mi></math></span>-step control invariant sets are representing generalizations of the classical one-step control invariant sets and prove to retain the useful properties for MPC design, but often with simpler representations, and thus greater applicability. In this paper, a novel NMPC scheme based on <span><math><mi>K</mi></math></span>-step control invariant sets is proposed. We employ symbolic control techniques to compute a <span><math><mi>K</mi></math></span>-step control invariant set and build the NMPC framework by integrating this set as a terminal constraint, thereby ensuring recursive feasibility.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101040"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141407713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoherence time control by interconnection for finite-level quantum memory systems 通过互联控制有限级量子存储器系统的退相干时间

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101054

Igor G. Vladimirov, Ian R. Petersen

{"title":"Decoherence time control by interconnection for finite-level quantum memory systems","authors":"Igor G. Vladimirov, Ian R. Petersen","doi":"10.1016/j.ejcon.2024.101054","DOIUrl":"10.1016/j.ejcon.2024.101054","url":null,"abstract":"<div><div>This paper is concerned with open quantum systems whose dynamic variables have an algebraic structure, similar to that of the Pauli matrices for finite-level systems. The Hamiltonian and the operators of coupling of the system to the external bosonic fields depend linearly on the system variables. The fields are represented by quantum Wiener processes which drive the system dynamics according to a quasilinear Hudson–Parthasarathy quantum stochastic differential equation whose drift vector and dispersion matrix are affine and linear functions of the system variables. This setting includes the zero-Hamiltonian isolated system dynamics as a particular case, where the system variables are constant in time, which makes them potentially applicable as a quantum memory. In a more realistic case of nonvanishing system-field coupling, we define a memory decoherence time when a mean-square deviation of the system variables from their initial values becomes relatively significant as specified by a weighting matrix and a fidelity parameter. We consider the decoherence time maximization over the energy parameters of the system and obtain a condition under which the zero Hamiltonian provides a suboptimal solution. This optimization problem is also discussed for a direct energy coupling interconnection of such systems.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101054"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Observer design for visual-inertial estimation of pose, linear velocity and gravity direction in planar environments 平面环境中姿态、线速度和重力方向视觉惯性估算的观测器设计

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101067

Tarek Bouazza , Tarek Hamel , Claude Samson

引用次数: 0

Optimal control of linear cost networks 线性成本网络的优化控制

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101068

David Ohlin, Emma Tegling, Anders Rantzer

引用次数: 0

Constructive synchronous observer design for inertial navigation with delayed GNSS measurements 利用延迟全球导航卫星系统测量进行惯性导航的建设性同步观测器设计

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101047

Pieter van Goor, Punjaya Wickramasinghe, Matthew Hampsey, Robert Mahony

引用次数: 0

Reinforcement learning based MPC with neural dynamical models 基于神经动力学模型的强化学习 MPC

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101048

Saket Adhau , Sébastien Gros , Sigurd Skogestad

引用次数: 0

Closed-loop identification of stabilized models using dual input–output parameterization 利用双输入输出参数化对稳定模型进行闭环识别

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101089

Ran Chen , Amber Srivastava , Mingzhou Yin , Roy S. Smith

{"title":"Closed-loop identification of stabilized models using dual input–output parameterization","authors":"Ran Chen , Amber Srivastava , Mingzhou Yin , Roy S. Smith","doi":"10.1016/j.ejcon.2024.101089","DOIUrl":"10.1016/j.ejcon.2024.101089","url":null,"abstract":"<div><div>This paper introduces a dual input–output parameterization (dual IOP) for the identification of linear time-invariant systems from closed-loop data. It draws inspiration from the recent input–output parameterization developed to synthesize a stabilizing controller. The controller is parameterized in terms of closed-loop transfer functions, from the external disturbances to the input and output of the system, constrained to lie in a given subspace. Analogously, the dual IOP method parameterizes the unknown plant with analogous closed-loop transfer functions, also referred to as dual parameters. In this case, these closed-loop transfer functions are constrained to lie in an affine subspace guaranteeing that the identified plant is <em>stabilized</em> by the known controller. Compared with existing closed-loop identification techniques guaranteeing closed-loop stability, such as the dual Youla parameterization, the dual IOP requires neither a doubly-coprime factorization of the controller nor a nominal plant that is stabilized by the controller. The dual IOP does not depend on the order and the state-space realization of the controller either, as in the dual system-level parameterization. Simulation shows that the dual IOP outperforms the existing benchmark methods.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101089"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Towards fully autonomous orbit management for low-earth orbit satellites based on neuro-evolutionary algorithms and deep reinforcement learning 基于神经进化算法和深度强化学习实现低地轨道卫星的完全自主轨道管理

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101052

Alexander Kyuroson, Avijit Banerjee, Nektarios Aristeidis Tafanidis, Sumeet Satpute, George Nikolakopoulos

{"title":"Towards fully autonomous orbit management for low-earth orbit satellites based on neuro-evolutionary algorithms and deep reinforcement learning","authors":"Alexander Kyuroson, Avijit Banerjee, Nektarios Aristeidis Tafanidis, Sumeet Satpute, George Nikolakopoulos","doi":"10.1016/j.ejcon.2024.101052","DOIUrl":"10.1016/j.ejcon.2024.101052","url":null,"abstract":"<div><div>The recent advances in space technology are focusing on fully autonomous, real-time, long-term orbit management and mission planning for large-scale satellite constellations in Low-Earth Orbit (LEO). Thus, a pioneering approach for autonomous orbital station-keeping has been introduced using a model-free Deep Policy Gradient-based Reinforcement Learning (DPGRL) strategy explicitly tailored for LEO. Addressing the critical need for more efficient and self-regulating orbit management in LEO satellite constellations, this work explores the potential synergy between Deep Reinforcement Learning (DRL) and Neuro-Evolution of Augmenting Topology (NEAT) to optimize station-keeping strategies with the primary goal to empower satellite to autonomously maintain their orbit in the presence of external perturbations within an allowable tolerance margin, thereby significantly reducing operational costs while maintaining precise and consistent station-keeping throughout their life cycle. The study specifically tailors DPGRL algorithms for LEO satellites, considering low-thrust constraints for maneuvers and integrating dense reward schemes and domain-based reward shaping techniques. By showcasing the adaptability and scalability of the combined NEAT and DRL framework in diverse operational scenarios, this approach holds immense promise for revolutionizing autonomous orbit management, paving the way for more efficient and adaptable satellite operations while incorporating the physical constraints of satellite, such as thruster limitations.</div></div>","PeriodicalId":50489,"journal":{"name":"European Journal of Control","volume":"80 ","pages":"Article 101052"},"PeriodicalIF":2.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141397533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Secure state estimation of networked switched systems under denial-of-service attacks 拒绝服务攻击下网络交换系统的安全状态估计

IF 2.5 3区计算机科学

European Journal of Control Pub Date : 2024-11-01 DOI: 10.1016/j.ejcon.2024.101037

Qingkai Meng , Andreas Kasis , Hao Yang , Marios M. Polycarpou

引用次数: 0