检索结果-内蒙古大学图书馆

Soft-minimum and soft-maximum barrier functions for safety with

AUTOMATICA 2025年 171卷

作者： Rabiee, Pedram Hoagg, Jesse B. Univ Kentucky Dept Mech & Aerosp Engn Lexington KY 40506 USA

This paper presents two new control approaches for guaranteed safety (remaining in a safe set) subject to actuator constraints (the control is in a convex polytope). The control signals are computed using real-time optimization, including linear and quadratic programs subject to affine constraints, which are shown to be feasible. The first control method relies on a soft-minimum barrier function that is constructed using a finite-time-horizon prediction of the system trajectories under a known backup control. The main result shows that the control is continuous and satisfies the actuator constraints, and a subset of the safe set is forward invariant under the control. Next, we extend this method to allow from multiple backup controls. This second approach relies on a combined soft-maximum/softminimum barrier function, and it has properties similar to the first. We demonstrate these controls on numerical simulations of an inverted pendulum and a nonholonomic ground robot. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Control of constrained systems optimization-based controller synthesis Nonlinear predictive control Safety

来源：评论

学校读者我要写书评

暂无评论

Trajectory tracking: A novel TMPC strategy for dynamic target management

引用

AUTOMATICA 2025年 177卷

作者： Adelirad, Masoud Afzalian, Ali A. Shahid Beheshti Univ Abbaspour Sch Eng Dept Elect Engn Tehran Iran

This paper presents a novel Tracking Model Predictive Control (TMPC) strategy, specifically designed for managing systems that track targets with unpredictable (priori unknown) trajectories. Traditional Model Predictive Control (MPC) is adept at set point tracking;however, it struggles with maintaining recursive feasibility when faced with variable references. Our TMPC approach addresses this by introducing a relaxation mechanism to the tracking problem's convergence conditions, which ensures the tracking error reduction within a predefined period of p sample times. To facilitate this, TMPC employs a tracking hyperplane as a constraint over the system's initial p-step trajectory, guaranteeing the convergence of the tracking error. We also introduce the concepts of the minimal p-step reachable set for the system and the maximal p-step reachable set for the target. These sets are pivotal in determining whether the system can feasibly track the target. Our approach assures recursive feasibility and the convergence of the tracking error within each p-sample time period. The efficacy of the TMPC strategy is demonstrated through simulation results and further substantiated by experimental validation on a laboratory-scale quadruple tank system. The outcomes confirm that TMPC is a robust solution for tracking control challenges in systems with dynamic targets. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： optimization-based controller synthesis Tracking Control of constrained systems Tracking hyperplane Reachable set Tracking tube

来源：评论

学校读者我要写书评

暂无评论

Anytime solvers for variational inequalities: The (recursive) safe monotone flows

引用

AUTOMATICA 2025年 177卷

作者： Allibhoy, Ahmed Cortes, Jorge UC Riverside Dept Mech Engn Riverside CA 92521 USA Univ Calif San Diego Dept Mech & Aerosp Engn La Jolla CA USA

This paper synthesizes anytime algorithms, in the form of continuous-time dynamical systems, to solve monotone variational inequalities. We introduce three algorithms that solve this problem: the projected monotone flow, the safe monotone flow, and the recursive safe monotone flow. The first two systems admit dual interpretations: either as projected dynamical systems or as dynamical systems controlled with a feedback controller specified by a quadratic program derived using techniques from safety-critical control. The third flow bypasses the need to solve quadratic programs along the trajectories by incorporating a dynamics whose equilibria precisely correspond to such solutions, and interconnecting the dynamical systems on different time scales. We perform a thorough analysis of the dynamical properties of all three systems. For the safe monotone flow, we show that equilibria correspond exactly with critical points of the original problem, and the constraint set is forward invariant and asymptotically stable. The additional assumption of convexity and monotonicity allows us to derive global stability guarantees, as well as establish the system is contracting when the constraint set is polyhedral. For the recursive safe monotone flow, we use tools from singular perturbation theory for contracting systems to show KKT points are locally exponentially stable and globally attracting, and obtain practical safety guarantees. We illustrate the performance of the flows on a two-player game example and also demonstrate the versatility for interconnection and regulation of dynamical processes of the safe monotone flow in an example of a receding horizon linear quadratic dynamic game. (c) 2025 Published by Elsevier Ltd.

关键词： Variational inequalities Safety-critical control Projected dynamical systems Parametric optimization optimization-based controller synthesis

来源：评论

学校读者我要写书评

暂无评论

A polynomial eigenvalue test for checking DLMI constraints

引用

AUTOMATICA 2023年 148卷

作者： Omar Baldissera, Joao Victor Harrop Galvao, Roberto Kawakami Gabriel, Gabriela Werner Inst Tecnol Aeronaut Elect Engn Div BR-12228900 Sao Jose Dos Campos SP Brazil

In order to obtain an optimization problem with a finite number of variables and constraints, Differential Linear Matrix Inequalities (DLMIs) are usually recast into the form of a system of LMIs. To this end, a typical approach consists in parameterizing the solution as a linear combination of known functions, with weights to be optimized. The constraints are then imposed on a finite set of discrete time points. This technical communique is concerned with the problem of checking whether a matrix polynomial solution obtained in this manner satisfies the original DLMI constraints. To this end, a novel test based on the concept of polynomial eigenvalues is presented. The proposed test is illustrated through a numerical example based on the H-infinity synthesis of a sampled-data controller. (c) 2022 Elsevier Ltd. All rights reserved.

关键词： Differential Linear Matrix Inequalities Polynomial eigenvalues Sampled-data control optimization-based controller synthesis

来源：评论

学校读者我要写书评

暂无评论

Data-driven control via Petersen's lemma

引用

AUTOMATICA 2022年 145卷

作者： Bisoffi, Andrea De Persis, Claudio Tesi, Pietro Univ Groningen ENTEG NL-9747 AG Groningen Netherlands Univ Florence DINFO I-50139 Florence Italy

We address the problem of designing a stabilizing closed-loop control law directly from input and state measurements collected in an experiment. In the presence of a process disturbance in data, we have that a set of dynamics could have generated the collected data and we need the designed controller to stabilize such set of data-consistent dynamics robustly. For this problem of data-driven control with noisy data, we advocate the use of a popular tool from robust control, Petersen's lemma. In the cases of data generated by linear and polynomial systems, we conveniently express the uncertainty captured in the set of data-consistent dynamics through a matrix ellipsoid, and we show that a specific form of this matrix ellipsoid makes it possible to apply Petersen's lemma to all of the mentioned cases. In this way, we obtain necessary and sufficient conditions for data-driven stabilization of linear systems through a linear matrix inequality. The matrix ellipsoid representation enables insights and interpretations of the designed control laws. In the same way, we also obtain sufficient conditions for data-driven stabilization of polynomial systems through alternate (convex) sum-of-squares programs. The findings are illustrated numerically.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Data-based control optimization-based controller synthesis Analysis of systems with uncertainty Robust control of nonlinear systems Linear matrix inequalities Sum-of-squares

来源：评论

学校读者我要写书评

暂无评论

When control and state variations increase uncertainty: Modeling and stochastic control in discrete time

引用

AUTOMATICA 2021年 123卷 109341-109341页

作者： Pedrosa, Filipe C. Nereu, Joao C. do Val, Joao B. R. UNICAMP Univ Campinas Sch Elect & Comp Engn BR-13083852 Campinas Brazil

This paper deals with the paradigm of controlling uncertain stochastic systems for which control and state variations increase uncertainty (CSVIU). The discrete time CSVIU model is particularly useful when an accurate dynamic model is unattainable, and only a rough model is available. Interesting features arise from the optimal control solution for the model. In particular, the optimal control action is to remain idle within a certain region of the state space - the inaction region. This feature, peculiar to the CSVIU approach, has ties to cautionary control policies found in economics. The convexity of the cost function holds for the discounted control problem with quadratic costs when the noise is Gaussian, and the control policy admits a solution in closed form in some regions of the state space. A linearly perturbed Lyapunov equation inside the inaction region, and a rational Riccati equation, asymptotically in far-off regions, characterize the control. We show the stochastic stability of solutions and provide numerical experiments that underline CSVIU model control's interesting peculiarities. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Stochastic control Stochastic modeling optimization-based controller synthesis Uncertain dynamic systems optimization under uncertainties Non-smooth and discontinuous problems

来源：评论

学校读者我要写书评

暂无评论

Optimal control of port-Hamiltonian systems: A continuous-time learning approach

引用

AUTOMATICA 2021年 130卷 109725-109725页

作者： Koelsch, Lukas Soneira, Pol Jane Strehle, Felix Hohmann, Soeren Karlsruhe Inst Technol KIT Inst Control Syst Kaiserstr 12 D-76131 Karlsruhe Germany

In this paper, we propose a continuous-time adaptive feedback controller for the optimal control of input-state-output port-Hamiltonian systems with respect to general Lagrangian performance indices. The proposed control law implements an online learning procedure which uses the Hamiltonian of the system as an initial value function candidate. The continuous-time learning of the value function is achieved by means of a certain Lagrange multiplier that allows to evaluate the optimality of the current solution. In particular, constructive conditions for stabilizing initial value function candidates are stated and asymptotic stability of the closed-loop equilibrium is proven. Simulations of an exemplary nonlinear optimal control problem demonstrate the performance of the controller resulting from the proposed online learning procedure. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Port-Hamiltonian systems optimization-based controller synthesis Adaptive control Dynamic optimization problem

来源：评论

学校读者我要写书评

暂无评论

Homothetic tube-based robust offset-free economic Model Predictive Control

引用

AUTOMATICA 2020年 119卷 109105-109105页

作者： Dong, Zihang Angeli, David Imperial Coll London Dept Elect & Elect Engn London England Univ Firenze Dipartimento Ingn Informaz Florence Italy

This paper proposes a novel economic Model Predictive Control algorithm aiming at achieving optimal steady-state performance despite the presence of plant-model mismatch or unmeasured nonzero mean disturbances. According to the offset-free formulation, the system's state is augmented with disturbances and transformed into a new coordinate framework. based on the new variables, the proposed controller integrates a moving horizon estimator to determine a solution of the nominal system surrounded by a set of potential states compatible with past input and output measurements. The worst cost within a single homothetic tube around the nominal solution is chosen as the economic objective function which is minimized to provide a tightened upper bound for the accumulated real cost within the prediction horizon window. Thanks to the combined use of the nominal system and homothetic tube, the designed optimization problem is recursively feasible and less conservative economic performance bounds are achieved. The proposed controller is demonstrated on a two-tanks system. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Robust economic model predictive control Output feedback and observers Optimal controller synthesis for systems with uncertainties optimization-based controller synthesis Robust estimation

来源：评论

学校读者我要写书评

暂无评论

Selective modal control for vibration reduction in flexible structures

引用

AUTOMATICA 2017年 75卷 282-287页

作者： Canciello, Giacomo Cavallo, Alberto Seconda Univ Napoli Dipartimento Ingn Ind & Informaz I-81031 Aversa CE Italy

The design of a controller for selective reduction of vibrations in flexible low-damped structures is presented. The objective of the active feedback control law is to increase damping of selected modes only, in frequency regions where a disturbance is likely to produce largest effect. Moreover, the stabilizing controller is required to be band-pass, in order to filter out high-frequency sensor noise and low-frequency accelerometer drift, and stable to increase robustness to uncertain parameters. The control design is based on the Inverse Optimal Design approach, through the solution of a matrix Stein equation, resulting in the solution of an optimal H-infinity control problem. A grey-box identification approach of the authors is employed for obtaining the model from experimental data or from detailed Finite Element Model (FEM) simulators. The problem of optimal actuator/sensor location is also addressed. Detailed simulation results are provided to show the effectiveness of the strategy. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Large scale optimization problems and methods Vibration control for flexible structures optimization-based controller synthesis Infinite-dimensional systems Identification methods

来源：评论

学校读者我要写书评

暂无评论

Distributed predictive control with minimization of mutual disturbances

引用

AUTOMATICA 2017年 77卷 31-43页

作者： Trodden, Paul A. Maestre, J. M. Univ Sheffield Dept Automat Control & Syst Engn Mappin St Sheffield S1 3JD S Yorkshire England Univ Seville Dept Syst Seville Spain Univ Seville Dept Automat Engn Seville Spain

In this paper, a distributed model predictive control scheme is proposed for linear, time-invariant dynamically coupled systems. Uniquely, controllers optimize state and input constraint sets, and exchange information about these - rather than planned state and control trajectories - in order to coordinate actions and reduce the effects of the mutual disturbances induced via dynamic coupling. Mutual disturbance rejection is by means of the tube-based model predictive control approach, with tubes optimized and terminal sets reconfigured on-line in response to the changing disturbance sets. Feasibility and exponential stability are guaranteed under provided sufficient conditions on non-increase of the constraint set parameters. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Decentralization Time-invariant Control of constrained systems optimization-based controller synthesis Parametric optimization

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：