2026

最新文章

• A Linear Parameter-Varying Approach to Data Predictive Control AI翻译
  作者：Verhoek, Chris; Berberich, Julian; Haesaert, Sofie; Toth, Roland; Abbas, Hossam S.
  作者单位：Eindhoven University of Technology; University of Stuttgart; University of Lubeck; HUN-REN; HUN-REN Institute for Computer Science & Control
  摘要：By means of the linear parameter-varying (LPV) Fundamental Lemma, we derive novel data-driven predictive control (DPC) methods for LPV systems. In particular, we present output-feedback and state-feedback-based LPV-DPC methods with terminal ingredients, which guarantee exponential stability and recursive feasibility. We provide methods for the data-based computation of these terminal ingredients. Furthermore, an in-depth analysis of the application and implementation aspects of the LPV-DPC sch...
• FlipDyn With Control: Resource Takeover Games With Dynamics AI翻译
  作者：Banik, Sandeep; Bopardikar, Shaunak D.
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; Michigan State University
  摘要：We introduce FlipDyn with control, a finite-horizon zero-sum resource takeover game, where a defender and an adversary decide when to takeover and how to control a common resource. At each discrete-time step, the players can take over or retain control, incurring state and control-dependent costs. The system is modeled as a hybrid dynamical system, with a discrete FlipDyn state determining control authority. Our contributions are: first, for arbitrary nonnegative costs, we derive the saddle-po...
• Distributed Optimal Output Consensus Control of Heterogeneous Multiagent Systems With Safety Constraints AI翻译
  作者：Ma, Ji; Liang, Shu; Hong, Yiguang
  作者单位：Xiamen University; Tongji University
  摘要：This article investigates the distributed optimal output consensus control for heterogeneous multiagent systems under the constraint that agents' outputs must remain within a prescribed safe set. A distributed two-layer optimal safe consensus protocol is proposed using the extended projection method, which simultaneously ensures safety requirements and optimal output consensus. Specifically, we construct a distributed projection optimization algorithm with an expanding constraint set in the de...
• A Robust Consensus plus Innovations-Based Distributed Parameter Estimator AI翻译
  作者：Lorenz-Meyer, Nicolai; Rueda-Escobedo, Juan G.; Moreno, Jaime A.; Schiffer, Johannes
  作者单位：Brandenburg University of Technology Cottbus; Universidad Nacional Autonoma de Mexico; Universidad Nacional Autonoma de Mexico
  摘要：While distributed parameter estimation has been extensively studied in the literature, little has been achieved in terms of robust analysis and tuning methods in the presence of disturbances. However, disturbances, such as measurement noise and model mismatches occur in any real-world setting. Therefore, providing tuning methods with specific robustness guarantees would greatly benefit the practical application. To address these issues, we recast the error dynamics of a continuous-time version...
• Distributed Continuous-Discrete State Observer With Discrete Output Measurements and Communication AI翻译
  作者：Cheng, Yi; Zhang, Baoyong; Xu, Shengyuan
  作者单位：Nanjing University of Science & Technology
  摘要：This article addresses a distributed state estimation problem for a continuous-time linear time-invariant system over the sensor and communication networks utilizing the discrete local output measurements and the intermittent communication. A distributed continuous-discrete state observer is developed to continuously generate the estimates. At each sampling moment, the estimate is updated based on the state update rule by using the periodic samples of the local output measurement and the neigh...
• Finite Time Convergence Analysis of Policy Gradient Learning in Stochastic Stackelberg Games AI翻译
  作者：Das, Pranoy; Zaman, Muhammad Aneeq uz; Gupta, Vijay
  作者单位：Purdue University System; Purdue University; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：Designing and analyzing learning algorithms for general sum stochastic Stackelberg games remain challenging. We propose an inner-outer loop policy gradient-based learning algorithm for this problem and analyze its finite time convergence. Our analysis does not assume a time scale separation between the leader and the follower or a special structure of the game, such as being Markov potential or zero-sum.
• High-Perception-Area Collaborative Exploration of Double-Integrator Robots in Parabolic-Type Diffusion Fields With Partially Unknown Information AI翻译
  作者：Li, Rui-Guo; Wang, Liang; Wu, Huai-Ning
  作者单位：Tiangong University; Shenzhen University; Beihang University
  摘要：This article solves a high-perception-area collaborative exploration issue for double-integrator robots in 2-dimensional parabolic-type diffusion scalar fields with partially unknown information. In the absence of surrounding field density information for robots, a distributed field density observer with adaptive update laws and event-triggering mechanisms is built to approximate necessary field density information. Taking into account of the scenario that robot's actual velocity is unmeasurab...
• Online Learning and Control Synthesis for Reachable Paths of Unknown Nonlinear Systems AI翻译
  作者：Meng, Yiming; Shafa, Taha; Wei, Jesse; Ornik, Melkior
  作者单位：University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign; University of Illinois System; University of Illinois Urbana-Champaign
  摘要：In this article, we present a novel method to drive a nonlinear system to a desired state, with limited a priori knowledge of its dynamic model: local dynamics at a single point and the bounds on the rate of change of these dynamics. This method synthesizes control actions by utilizing locally learned dynamics along a trajectory, based on data available up to that moment, and known proxy dynamics, which can generate an underapproximation of the unknown system's true reachable set. An important...
• Minimax Linear Regulator Problems for Positive Systems AI翻译
  作者：Gurpegui, Alba; Jeeninga, Mark; Tegling, Emma; Rantzer, Anders
  作者单位：Lund University
  摘要：Explicit solutions to optimal control problems are rarely obtainable. Of particular interest are the explicit solutions derived for minimax problems, providing a framework to address adversarial conditions and uncertainty. This work considers a multidisturbance minimax linear regulator (LR) framework for positive linear time-invariant systems in continuous time, which, analogous to the linear-quadratic regulator problem, can be utilized for the stabilization of positive systems. The problem is...
• Differentially Private Consensus of Multiagent Systems Under Binary-Valued Communications AI翻译
  作者：Lu, Xiaodong; Zhao, Yanlong; Zhang, Ji-Feng
  作者单位：University of Science & Technology Beijing; Chinese Academy of Sciences; Nanjing Institute of Geology & Paleontology, CAS; Academy of Mathematics & System Sciences, CAS; Chinese Academy of Sciences; University of Chinese Academy of Sciences, CAS; Zhongyuan University of Technology
  摘要：This article investigates the differentially private output consensus problem of continuous-time heterogeneous multiagent systems. An algorithm blending estimation, control and privacy is proposed. To prevent privacy leakage, each agent constructs an auxiliary variable regarding to its own initial output, and then adds a nondecaying noise to this variable. To incorporate the network bandwidth limitation, each agent quantifies the noisy auxiliary variable to 1-bit binary-valued data, and transm...