H? filtering of networked systems with time-varying sampling rates

In this paper, the problem of robust filter design for networked systems with time-varying sampling rate is investigated. The design conditions are obtained by using the Lyapunov theory and the Finsler\u27s Lemma. A robust filter, that minimizes an upper bound to the Hinfin performance of the estimation error, is obtained as the solution of an optimization problem. A path-dependent Lyapunov function is used in order to obtain less conservative design conditions. Robust filters based on affine parameter-dependent Lyapunov functions can be obtained as a particular case of the proposed method. Numerical examples illustrate the results

Robust H2 static output feedback to control an autmomotive throttle valve

The paper presents a control strategy for an automotive electronic throttle body, a device largely used into vehicles to increase the efficiency of the combustion engines. The synthesis of the proposed controller is based on a linear matrix inequality (LMI) formulation, which allows us to deal with uncertainties on the measurements of the position of the throttle valve. The LMI approach generates a suboptimal solution for the robust H-2 static output feedback control problem, and the corresponding suboptimal control gain was evaluated in practice to control the valve position of the throttle. The usefulness of the approach has been verified not only by numerical simulations but also by real experiments taken in a laboratory prototype.Postprint (published version

H_∞ Static Output-Feedback Gain-Scheduled Control for Discrete LPV Time-Delay Systems^⁎

This paper proposes new synthesis conditions to design H∞ static output-feedback controllers for discrete-time linear systems affected by time-varying parameters and time-varying delays. The design conditions are provided in terms of sufficient parameter-dependent linear matrix inequalities with a scalar parameter, being capable of synthesizing either robust or gain-scheduled controllers. The main motivations to deal with such problem are that many real-world plants can be modeled in terms of discrete-time linear parameter-varying (LPV) time-delay models and the lack of methods to deal with such systems considering an output-feedback based approach. The technique presented in this paper is quite generalist, allowing an arbitrary structure for the measured output matrix. Numerical examples are provided to illustrate the effectiveness of the synthesis conditions, tractable in terms of LMI relaxations, for robust or gain-scheduled H∞ output-feedback for LPV time-delayed systems

A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network

Output feedback control of discrete-time Lur'e systems through FIR Zames-Falb multipliers

International audienceThis paper is concerned with output feedback control of discrete-time Lur'e systems with slope bounded nonlinearities that can be non-odd. Using FIR (Finite Impulse Response) Zames-Falb multipliers of any given order, stability conditions based on positive realness are proposed in terms of linear matrix inequalities and linear constraints that assure the ℓ 1 norm bound for the multiplier. Importantly, the proposed approach does not require line searches. Applying a relaxation on the stability and exploiting the fact that the matrices of the system appear affinely in the conditions, an iterative method is constructed to search for the FIR Zames-Falb multiplier certifying stability. An extension to cope with the design of a control law is also presented, dealing with state or output feedback gains that may include a term proportional to the output of the nonlinear block. Numerical examples illustrate the advantages of the proposed approach, that can be numerically more efficient than other techniques from the literature