IF 4.8 2区计算机科学

Automatica Pub Date : 2025-07-03 DOI: 10.1016/j.automatica.2025.112460

Hanieh Tabatabaei , Alexander J. Gallo , Ahmad W. Al-Dabbagh

引用次数: 0

Continuous-time successive convexification for constrained trajectory optimization 约束轨迹优化的连续时间连续凸化

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-07-03 DOI: 10.1016/j.automatica.2025.112464

Purnanand Elango , Dayou Luo , Abhinav G. Kamath , Samet Uzun , Taewan Kim , Behçet Açıkmeşe

{"title":"Continuous-time successive convexification for constrained trajectory optimization","authors":"Purnanand Elango , Dayou Luo , Abhinav G. Kamath , Samet Uzun , Taewan Kim , Behçet Açıkmeşe","doi":"10.1016/j.automatica.2025.112464","DOIUrl":"10.1016/j.automatica.2025.112464","url":null,"abstract":"<div><div>We present continuous-time successive convexification (<span>ct- scvx</span> ), a real-time-capable solution method for constrained trajectory optimization, with continuous-time constraint satisfaction and guaranteed convergence. The proposed solution framework only relies on first-order information, and it combines several key methods to solve a large class of nonlinear optimal control problems: (i) exterior penalty-based reformulation of the path constraints; (ii) generalized time-dilation; (iii) multiple-shooting discretization; (iv) <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>-exact penalization of the nonconvex constraints; and (v) the prox-linear method, a sequential convex programming (SCP) algorithm for convex-composite minimization. The proposed reformulation of the path constraints enables continuous-time constraint satisfaction even on sparse temporal discretization grids and obviates the need for mesh-refinement heuristics. Through the prox-linear method, we guarantee that: (i) <span>ct-scvx</span> converges to stationary points of the penalized problem; (ii) the converged stationary points that are feasible for the discretized and control-parameterized optimal control problem are also Karush–Kuhn–Tucker (KKT) points. Furthermore, we specialize this property to global minimizers of convex optimal control problems and obtain stronger convergence results by exploiting convexity. In addition to theoretical analysis, we demonstrate the effectiveness and real-time performance of <span>ct-scvx</span> by means of numerical examples from real-world optimal control applications: dynamic obstacle avoidance, and 3-degree-of-freedom (3-DoF) and 6-DoF autonomous rocket landing.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"180 ","pages":"Article 112464"},"PeriodicalIF":4.8,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144548522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Lyapunov-based adaptive deep system identification for approximate dynamic programming 基于lyapunov的深度系统自适应近似动态规划辨识

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-07-03 DOI: 10.1016/j.automatica.2025.112462

Wanjiku A. Makumi , Omkar Sudhir Patil , Warren E. Dixon

引用次数: 0

Continuous safety-critical control of Euler–Lagrange systems subject to multiple obstacles and velocity constraints 多障碍物和速度约束下欧拉-拉格朗日系统的连续安全临界控制

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-07-02 DOI: 10.1016/j.automatica.2025.112404

Zhi Liu , Si Wu , Tengfei Liu , Zhong-Ping Jiang

{"title":"Continuous safety-critical control of Euler–Lagrange systems subject to multiple obstacles and velocity constraints","authors":"Zhi Liu , Si Wu , Tengfei Liu , Zhong-Ping Jiang","doi":"10.1016/j.automatica.2025.112404","DOIUrl":"10.1016/j.automatica.2025.112404","url":null,"abstract":"<div><div>This paper studies the safety-critical control problem for Euler–Lagrange (EL) systems subject to multiple ball obstacles and velocity constraints. A key strategy is to exploit the underlying cascade structure of EL systems to design a new safety-critical controller featuring an inner–outer-loop structure. In particular, the outer-loop control law is developed based on quadratic programming (QP) to avoid ball obstacles and generate velocity reference signals fulfilling the velocity limitation. Taking full advantage of the energy conservation property, a nonlinear velocity-tracking control law is designed to form the inner loop. One major difficulty is caused by the possible non-Lipschitz continuity of the standard QP algorithm when there are multiple constraints. To solve this problem, we propose a new feasible-set reshaping technique such that the refined QP algorithm with the reshaped feasible set admits a Lipschitz continuity property. Additionally, inspired by small-gain analysis, we construct a max-type Lyapunov-like function to integrate the safety constraints and the velocity-tracking error, and prove the achievement of the safety-critical control objective. The effectiveness of the proposed design is validated through numerical simulations and experiments on a 2-link planar manipulator.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"180 ","pages":"Article 112404"},"PeriodicalIF":4.8,"publicationDate":"2025-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

On reconstructing high derivatives of noisy time-series with confidence intervals 带置信区间的噪声时间序列高导数重构

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-06-30 DOI: 10.1016/j.automatica.2025.112469

Mazen Alamir

引用次数: 0

Computationally efficient system level tube-MPC for uncertain systems 不确定系统的高效计算系统级管- mpc

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-06-28 DOI: 10.1016/j.automatica.2025.112466

Jerome Sieber, Alexandre Didier, Melanie N. Zeilinger

{"title":"Computationally efficient system level tube-MPC for uncertain systems","authors":"Jerome Sieber, Alexandre Didier, Melanie N. Zeilinger","doi":"10.1016/j.automatica.2025.112466","DOIUrl":"10.1016/j.automatica.2025.112466","url":null,"abstract":"<div><div>Tube-based model predictive control (MPC) is one of the principal robust control techniques for constrained linear systems affected by additive disturbances. While tube-based methods with online-computed tubes have been successfully applied to systems with additive disturbances, their application to systems affected by additional model uncertainties is challenging. This paper proposes a tube-based MPC method – named filter-based system level tube-MPC (SLTMPC) – which overapproximates both types of uncertainties with an online optimized disturbance set, while simultaneously computing the tube controller online. For the first time, we provide rigorous closed-loop guarantees for receding horizon control of such a MPC method. These guarantees are obtained by virtue of a new terminal controller design and an online optimized terminal set. To reduce the computational complexity of the proposed method, we additionally introduce an asynchronous computation scheme that separates the optimization of the tube controller and the nominal trajectory. Finally, we provide a comprehensive numerical evaluation of the proposed methods to demonstrate their effectiveness.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"180 ","pages":"Article 112466"},"PeriodicalIF":4.8,"publicationDate":"2025-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144502024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Comment on “Saturated adaptive pose tracking control of spacecraft on SE(3) under attitude constraints and obstacle-avoidance constraints” [Automatica 159 (2024) 111367] 评“姿态约束和避障约束下航天器SE(3)上的饱和自适应姿态跟踪控制”[Automatica 159 (2024) 111367]

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-06-28 DOI: 10.1016/j.automatica.2025.112468

Yuxin Su

引用次数: 0

Predefined-time reinforcement learning for optimal feedback control 用于最优反馈控制的预定义时间强化学习

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-06-27 DOI: 10.1016/j.automatica.2025.112421

Nick-Marios T. Kokolakis , Kyriakos G. Vamvoudakis , Wassim M. Haddad

{"title":"Predefined-time reinforcement learning for optimal feedback control","authors":"Nick-Marios T. Kokolakis , Kyriakos G. Vamvoudakis , Wassim M. Haddad","doi":"10.1016/j.automatica.2025.112421","DOIUrl":"10.1016/j.automatica.2025.112421","url":null,"abstract":"<div><div>In this paper, we develop an online predefined time-convergent reinforcement learning architecture to solve the optimal predefined-time stabilization problem. Specifically, we introduce the problem of optimal predefined-time stabilization to construct feedback controllers that guarantee closed-loop system predefined-time stability while optimizing a given performance measure. The predefined time stability of the closed-loop system is established via a Lyapunov function satisfying a differential inequality while simultaneously serving as a solution to the steady-state Hamilton–Jacobi–Bellman equation ensuring optimality. Given that the Hamilton–Jacobi–Bellman equation is generally difficult to solve, we develop a critic-only reinforcement learning-based algorithm to learn the solution to the steady-state Hamilton–Jacobi–Bellman equation in predefined time. In particular, a non-Lipschitz experience replay-based learning law utilizing recorded and current data is introduced for updating the critic weights to learn the value function. The non-Lipschitz property of the dynamics and letting the learning rate as a function of the predefined time gives rise to predefined-time convergence, while the experience replay-based approach eliminates the need to satisfy the persistence of excitation condition as long as the recorded data set is sufficiently rich. Finally, an illustrative numerical example is provided to demonstrate the efficacy of the proposed approach.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112421"},"PeriodicalIF":4.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

On kernel design for regularized Volterra series identification of Wiener–Hammerstein systems Wiener-Hammerstein系统正则化Volterra级数辨识的核设计

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-06-27 DOI: 10.1016/j.automatica.2025.112457

Yu Xu , Biqiang Mu , Tianshi Chen

{"title":"On kernel design for regularized Volterra series identification of Wiener–Hammerstein systems","authors":"Yu Xu , Biqiang Mu , Tianshi Chen","doi":"10.1016/j.automatica.2025.112457","DOIUrl":"10.1016/j.automatica.2025.112457","url":null,"abstract":"<div><div>There have been increasing interests in the Volterra series identification with the kernel-based regularization method. The major difficulties are on the kernel design and efficiency of the corresponding implementation. In this paper, we first assume that the underlying system to be identified is the Wiener–Hammerstein (WH) system with polynomial nonlinearity. We then show how to design kernels with nonzero off-diagonal blocks for Volterra maps by taking into account the prior knowledge of the linear blocks and the structure of WH systems. Moreover, exploring the structure of the designed kernels leads to the same computational complexity as the state-of-the-art result, i.e., <span><math><mrow><mi>O</mi><mrow><mo>(</mo><msup><mrow><mi>N</mi></mrow><mrow><mn>3</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span>, where <span><math><mi>N</mi></math></span> is the sample size, but with the significant difference that the proposed kernels are designed in a direct and flexible way. In addition, for a special case of the kernel and a class of widely used input signals, further exploring the separable structure of the output kernel matrix can lower the computational complexity from <span><math><mrow><mi>O</mi><mrow><mo>(</mo><msup><mrow><mi>N</mi></mrow><mrow><mn>3</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span> to <span><math><mrow><mi>O</mi><mrow><mo>(</mo><mi>N</mi><msup><mrow><mi>γ</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>)</mo></mrow></mrow></math></span>, where <span><math><mi>γ</mi></math></span> is the separability rank of the output kernel matrix and can be much smaller than <span><math><mi>N</mi></math></span>. We finally run Monte Carlo simulations to demonstrate the proposed kernels and the obtained theoretical results.</div></div>","PeriodicalId":55413,"journal":{"name":"Automatica","volume":"179 ","pages":"Article 112457"},"PeriodicalIF":4.8,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144491250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Finite-time regret minimization for linear quadratic adaptive controllers: An experiment design approach 线性二次型自适应控制器的有限时间后悔最小化：一种实验设计方法

IF 4.8 2区计算机科学

Automatica Pub Date : 2025-06-26 DOI: 10.1016/j.automatica.2025.112459

Kévin Colin , Håkan Hjalmarsson , Xavier Bombois

引用次数: 0

Automatica最新文献