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We present a study of the scaling properties of the interconnection of nagents (e.g. vehicles) through an r-lookahead network. These networks are considered as a possible implementation for vehicle platooning, although we do not make any assumptions on what the agents represent, and we assume them to be linear time invariant (LTI) discrete time systems, locally controlled by an LTI controller. In particular, we show that the r-lookahead topology gives rise to dynamics which can be studied from the roots of polynomials with transfer functions as their coefficients. Through numerical simulations, we study aspects relating the use of lookahead measurements and their effect on the value of a time headway constant needed for the scalability property known as string stability.

This paper proposes a complete robust control design procedure for combustion systems, present in a wide range of important applications. Using a non-linear model identified through optical instrumentation, it is proposed a linear model around an operating condition. To ensure robustness with respect to variations on the operation condition and to deal with external disturbances, a state-space linear representation is further developed, introducing uncertain parameters and exogenous inputs affecting the plant (as non-laminar air flow), giving rise to a poly topic uncertain linear system. Finally, it is proposed a reduced-order H∞output-feedback control law for the resulting uncertain system, capable to assure closed-loop robust stability and performance in the whole uncertain domain. A numerical experiment is presented to show the effectiveness of the designed reduced-order controller, that is robust against uncertainties and have a low cost of implementation.

In the present work, motivated by the recent inclusion of optical variables in combustion processes, we consider the control of a reduced Hammerstein plant model over an additive white noise (AWN) channel located at the feedback path. For comparison, assuming uncertainty in the knowledge of the static nonlinearity of the Hammerstein plant model, we first propose in a one degree-of-freedom (DOF) scheme, the design of a proportional controller for robust stability We then introduce a PI controller, in a 3 DOF scheme, to achieve not only robust stability, but also AWN channel Signal-to-Noise Ratio (SNR) minimization and setpoint first moment tracking.