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最新文章

• Distributed Model Predictive Control via Separable Optimization in Multiagent Networks AI翻译
  作者：Shorinwa, Ola; Schwager, Mac
  作者单位：Stanford University; Stanford University
  摘要：We present a distributed model predictive control method, which enables a group of agents to compute their control inputs locally while communicating with their neighbors over a communication network. While many distributed model predictive control methods require a central station for some coordination or computation of the optimization variables, our method does not require a central station, making our approach applicable to a variety of communication network topologies. With our method, ea...
• Robust Optimal Control of Biobjective Linear-Quadratic System With Noisy Observation AI翻译
  作者：Wang, Guangchen; Xing, Zhuangzhuang
  作者单位：Shandong University
  摘要：note is dedicated to a kind of partially observable linear-quadratic control problem with model uncertainty, where the coefficients of cost functional are uncertain representing different market conditions. By virtue of backward separation technique, stochastic maximum principle, as well as filtering method, a feedback form of candidate optimal control is designed. Moreover, through some delicate analysis, the existence of maximal reference probability lambda (& lowast;) is certified. A consid...
• Robust State-Estimator-Based Control of Uncertain Semi-Markovian Jump Systems Subject to Actuator Failures and Time-Varying Delay AI翻译
  作者：Yu, Jinpeng; Liu, Zhen; Shi, Peng
  作者单位：Qingdao University; Qingdao University; University of Adelaide
  摘要：This note presents a reformed state-estimator-based adaptive control strategy for uncertain delayed semi-Markovian jump systems (DSMJS) via sliding-mode technique. In comparison to most literature results requiring exact prior knowledge of system time delay, a linear state estimator not linking any control inputs is developed to cope with the case with unknown state delays. By virtue of the acquired state estimation, the establishment of both a new switching surface of linear-type (SSL) and th...
• Risk-Averse Decision Making Under Uncertainty AI翻译
  作者：Ahmadi, Mohamadreza; Rosolia, Ugo; Ingham, Michel D.; Murray, Richard M.; Ames, Aaron D.
  作者单位：California Institute of Technology; National Aeronautics & Space Administration (NASA); NASA Jet Propulsion Laboratory (JPL)
  摘要：A large class of decision making under uncertainty problems can be described via Markov decision processes (MDPs) or partially observable MDPs (POMDPs), with application to artificial intelligence and operations research, among others. In this article, we consider the problem of designing policies for MDPs and POMDPs with objectives and constraints in terms of dynamic coherent risk measures rather than the traditional total expectation, which we refer to as the constrained risk-averse problem....
• Adaptive Regulation With Global KL Guarantees AI翻译
  作者：Karafyllis, Iasson; Aslanidis, Alexandros; Krstic, Miroslav
  作者单位：National Technical University of Athens; University of California System; University of California San Diego
  摘要：In the absence of persistency of excitation (PE), referring to adaptive control systems as uniformly asymptotically stable typically indicates insufficient understanding of stability concepts. While the state is indeed regulated to zero and the parameter estimate has some limit, namely, the overall state converges to some equilibrium, the equilibrium reached is not unique (and not even necessarily stable) but is dependent on the initial condition. The equilibrium set in the absence of PE is no...
• On the Structure of Feedback Potential Difference Games AI翻译
  作者：Prasad, Aathira; Mohapatra, Partha Sarathi; Reddy, Puduru Viswanadha
  作者单位：Indian Institute of Technology System (IIT System); Indian Institute of Technology (IIT) - Madras
  摘要：A static potential game is a noncooperative game for which there exists a fictitious function, also referred to as a potential function, whose optimizers provide a Nash equilibrium of the associated noncooperative game. In this article, we study nonzero-sum finite-horizon difference games with feedback information structure, which admit a potential game structure. We provide conditions for the existence of an optimal control problem such that the optimal solution of this problem provides a fee...
• On the Role of Convexity/Concavity in Vector Fields, Flows, and Stability/Stabilizability AI翻译
  作者：Sassano, M.; Astolfi, A.
  作者单位：University of Rome Tor Vergata; Imperial College London
  摘要：It is shown that strong convexity/concavity of a component of the vector field, as a function of the state variables, induces the same property on the corresponding component of the flow, as a function of the initial condition. Such an inherited property is then instrumental, for instance, for establishing several instability theorems, the proofs of which rely precisely on consequences of convexity/concavity of the flow with respect to the initial condition. Furthermore, the property of convex...
• Quantized Primal-Dual Algorithms for Network Optimization With Linear Convergence AI翻译
  作者：Chen, Ziqin; Liang, Shu; Li, Li; Cheng, Shuming
  作者单位：Tongji University
  摘要：This note investigates a network optimization problem in which a group of agents cooperate to minimize a global function under the practical constraint of finite-bandwidth communication. We propose an adaptive encoding-decoding scheme to handle the quantization communication between agents. Based on this scheme, we develop a continuous-time quantized distributed primal-dual algorithm for the network optimization problem. Our algorithm achieves linear convergence to an exact optimal solution. F...
• Inverse Optimal Safety Filters AI翻译
  作者：Krstic, Miroslav
  作者单位：University of California System; University of California San Diego
  摘要：Control barrier function quadratic programs (QP) safety filters are pointwise minimizers of the control effort at a given state, i.e., myopically optimal at each time. But are they optimal over the entire infinite time horizon? What does it mean for a controlled system to be optimally safe as opposed to, conventionally optimally stable? When disturbances, deterministic and stochastic, have unknown upper bounds, how should safety be defined to allow a graceful degradation under disturbances? Ca...
• Distributed Control for Uncertain Multiagent Systems With the Powers of Positive-Odd Numbers: A Low-Complexity Design Approach AI翻译
  作者：Lv, Maolong; Wang, Ning
  作者单位：Air Force Engineering University
  摘要：This work shows that low-complexity prescribed performance control (PPC) can be used to realize leader-following consensus for uncertain second-order multiagent systems (MASs) with the powers of positive odd numbers, i.e., agents whose dynamics are a chain of integrators with positive odd powers. Low-complexity PPC is a control methodology whose strongest feature is its adaptation-free structural simplicity: uncertainty can be handled without estimation of unknown parameters nor approximation ...