This paper examines the problem of estimating the parameters describing system models of quite general nonlinear and multi-variable form. The approach is a computational one in which quantities that are intractable to...
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Robust optimal experiment design for dynamic system identification is cast as a minmax optimization problem, which is infinite-dimensional. If the input spectrum is discretized (either by considering a Riemmann approx...
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We propose a distributed learning algorithm for fair scheduling in common-pool games. Common-pool games are strategic-form games where multiple agents compete over utilizing a limited common resource. A characteristic...
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In this contribution we present a method to estimate structured high order ARX models. By this we mean that the estimated model, despite its high order is close to a low order model. This is achieved by adding two ter...
In this contribution we present a method to estimate structured high order ARX models. By this we mean that the estimated model, despite its high order is close to a low order model. This is achieved by adding two terms to the least-squares cost function. These two terms correspond to nuclear norms of two Hankel matrices. These Hankel matrices are constructed from the impulse response coefficients of the inverse noise model, and the numerator polynomial of the model dynamics, respectively. In a simulation study the method is shown to be competitive as compared to the prediction error method. In particular, in the study the performance degrades more gracefully than for the Prediction Error Method when the signal to noise ratio decreases.
This paper proposes an event-based scheme to control a networked control system and to manage the radio-modes of its smart sensor node. The smart node is battery driven and is in charge of sensing the system and compu...
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A Norm-Optimal Iterative Learning control (NOILC) solution is developed for the problem when tracking is only required at a subset of isolated time points along the trial duration. Well-defined convergence properties ...
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ISBN:
(纸本)9781467320658
A Norm-Optimal Iterative Learning control (NOILC) solution is developed for the problem when tracking is only required at a subset of isolated time points along the trial duration. Well-defined convergence properties are presented, along with design guidelines and supporting experimental results using an electromechanical test facility.
In this paper we propose a decentralized nonlinear controller that has the ability to enhance the transient stability and achieve voltage regulation simultaneously for multimachine power systems. This paper extends th...
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This paper presents a distributed event-based control approach to cope with communication delays and packet losses affecting a networked dynamical system consisting of N linear time-invariant coupled systems. Two comm...
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This paper presents a distributed event-based control approach to cope with communication delays and packet losses affecting a networked dynamical system consisting of N linear time-invariant coupled systems. Two communication protocols are proposed to deal with these communication effects. It is shown that both protocols preserve the system stability in the sense that the state of every subsystem converges to a small region around the origin if the delay and the number of packet losses are bounded. Analytical expressions for the delay bound and the maximum number of consecutive packet losses are derived. Simulations illustrate the results.
Mutation analysis is widely employed to evaluate the effectiveness of various software testing techniques. In most situations, mutation operators are uniformly applied to the original programs, while the faults tend t...
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In this work, we present two unconstrained MPC schemes using additional weighting terms which allow to obtain improved stability conditions. First, we consider unconstrained MPC with general terminal cost functions. I...
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ISBN:
(纸本)9781467320658
In this work, we present two unconstrained MPC schemes using additional weighting terms which allow to obtain improved stability conditions. First, we consider unconstrained MPC with general terminal cost functions. If the terminal cost is not a control Lyapunov function, but satisfies a relaxed condition, then our results yield improved estimates for a stabilizing prediction horizon. Furthermore, our analysis also allows to recover two well-known results as special cases: if the terminal cost function is chosen as zero, we recover previous conditions on the length of the prediction horizon such that stability is guaranteed; and if the terminal cost is a control Lyapunov function conform to the stage cost, stability follows independently of the length of the prediction horizon. Second, we propose to use an exponential weighting on the stage cost in order to improve the stability properties of the closed-loop. This also allows to consider local controllability assumptions in combination with a suitable terminal constraints and thereby gives a connection to the classical MPC approaches using terminal constraints.
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