IEEE Transactions on Automatic Control

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• Memory Augmented Neural Network Adaptive Controllers: Performance and Stability AI翻译
  作者：Muthirayan, Deepan; Khargonekar, Pramod P.
  作者单位：University of California System; University of California Irvine
  摘要：In this article, we propose a novel control architecture, inspired from neuroscience, for adaptive control of continuous-time systems. The proposed architecture, in the setting of standard neural network (NN)-based adaptive control, augments an external working memory to the NN. The controller, through a write operation, writes the hidden layer feature vector of the NN to the external working memory and can also update this information with the observed error in the output. Through a read oper...
• Incentive Mechanism Design for Unicast Service Provisioning With Network Aggregative Game AI翻译
  作者：Eslami, Ehsan; Kebriaei, Hamed; Atrianfar, Hajar; Farhadi, Farzaneh
  作者单位：University of Tehran; University of Tehran; Institute for Research in Fundamental Sciences IPM; Amirkabir University of Technology; Imperial College London
  摘要：We investigate the problem of distributed resource allocation in unicast communication networks with strategic/selfish users. First, through mechanism design, the centralized problem is converted to a decentralized problem that induces a network aggregative game among users. At every Nash equilibrium, this mechanism strongly implements the solution of the resource allocation problem, and it is budget balance as well. Then, we establish a relationship between Nash equilibria of the induced game...
• Personalized Incentives as Feedback Design in Generalized Nash Equilibrium Problems AI翻译
  作者：Fabiani, Filippo; Simonetto, Andrea; Goulart, Paul J.
  作者单位：IMT School for Advanced Studies Lucca; Institut Polytechnique de Paris; ENSTA Paris; University of Oxford
  摘要：We investigate both stationary and time-varying, nonmonotone-generalized Nash equilibrium problems that exhibit symmetric interactions among the agents, which are known to be potential. As may happen in practical cases, however, we envision a scenario in which the formal expression of the underlying potential function is not available, and we design a semidecentralized Nash-equilibrium-seeking algorithm. In the proposed two-layer scheme, a coordinator iteratively integrates possibly noisy and ...
• Event-Triggered Tracking Control for a Class of Nonlinear Systems: A Dynamic Gain Approach AI翻译
  作者：Li, Hanfeng; Zhang, Xianfu; Xie, Lihua; Liu, Shuai; Liu, Qingrong
  作者单位：Shandong University; Nanyang Technological University; Shandong University of Finance & Economics
  摘要：This note presents a dynamic gain approach to the event-triggered tracking control for a class of strict-feedback nonlinear systems. A novel shifting function is designed to make the initial tracking error arbitrarily bounded, which significantly relaxes the requirement on the initial tracking error. To achieve the objective that the tracking error does not exceed the constraint after the prespecified finite time, a barrier Lyapunov function and a new reduced-order observer are constructed by ...
• Pisot-Number-Based Discrete-Time Controllers With Integer State Matrices to Ensure Monotonic Closed-Loop Step Responses AI翻译
  作者：Tavazoei, Mohammad Saleh
  作者单位：Sharif University of Technology
  摘要：Motivated by the applicability of homomorphically encrypted discrete-time controllers possessing integer state matrices to work in an infinite time horizon, this article deals with the design of such controllers to guarantee that the step response of the control system is monotonic. On the basis of locating the poles of designed controllers at positive Pisot numbers and some of their algebraic conjugates and benefiting from the idea of using nonminimal state-space models, an analytical approac...
• Distributed Exponential State Estimation for Discrete-Time Linear Systems Over Jointly Connected Switching Networks AI翻译
  作者：Liu, Tao; Huang, Jie
  作者单位：Chinese University of Hong Kong; CUHK Shenzhen Research Institute; Chinese University of Hong Kong; Southern University of Science & Technology
  摘要：The existing results on the distributed state estimation problem for discrete-time linear systems were obtained over connected static networks, or every-time connected switching networks by a two-time-scale design. This article further studies the same problem over jointly connected switching networks that can be disconnected at every time instant by a single-time-scale distributed design. Since the existing distributed designs critically rely on the connectedness assumption on the networks an...
• A Simple and Fast Coordinate-Descent Augmented-Lagrangian Solver for Model Predictive Control AI翻译
  作者：Wu, Liang; Bemporad, Alberto
  作者单位：IMT School for Advanced Studies Lucca
  摘要：This article proposes a novel coordinate-descent augmented-Lagrangian (CDAL) solver for linear, possibly parameter-varying, model predictive control (MPC) problems. At each iteration, an augmented Lagrangian (AL) subproblem is solved by coordinate descent (CD), exploiting the structure of the MPC problem. The CDAL solver enjoys three main properties: 1) it is construction-free, in that it avoids explicitly constructing the quadratic programming problem associated with MPC; 2) is matrix-free, a...
• From Data to Reduced-Order Models via Generalized Balanced Truncation AI翻译
  作者：Burohman, Azka Muji; Besselink, Bart; Scherpen, Jacquelien M. A.; Camlibel, M. Kanat
  作者单位：University of Groningen; University of Groningen; University of Groningen
  摘要：This article proposes a data-driven model reduction approach on the basis of noisy data with a known noise model. Firstl, the concept of data reduction is introduced. In particular, we show that the set of reduced-order models obtained by applying a Petrov-Galerkin projection to all systems explaining the data characterized in a large-dimensional quadratic matrix inequality (QMI) can again be characterized in a lower-dimensional QMI. Next, we develop a data-driven generalized balanced truncati...
• Fourier-Hermite Dynamic Programming for Optimal Control AI翻译
  作者：Hassan, Syeda Sakira; Sarkka, Simo
  作者单位：Aalto University
  摘要：In this article, we propose a novel computational method for solving nonlinear optimal control problems. The method is based on the use of Fourier-Hermite series for approximating the action-value function arising in dynamic programming instead of the conventional Taylor-series expansion used in differential dynamic programming. The coefficients of the Fourier-Hermite series can be numerically computed by using sigma-point methods, which leads to a novel class of sigma-point-based dynamic prog...
• Risk-Aware Maximum Hands-Off Control Using Worst-Case Conditional Value-at-Risk AI翻译
  作者：Kishida, Masako; Nagahara, Masaaki
  作者单位：Research Organization of Information & Systems (ROIS); National Institute of Informatics (NII) - Japan; University of Kitakyushu
  摘要：With the view of risks, this article deals with the problems of maximum hands-off control that aims at minimizing the length of nonzero control input. More specifically, we consider stochastic systems and seek sparse control inputs that bring the system state to a ball centered at the origin, such that the expected value of the states that are further than a given threshold from the origin is small, thus minimizing the risk that the system state is outside of the ball. To deal with this proble...