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This paper presents a new approach to congestion management at traffic-light intersections. The approach is based on controlling the relative lengths of red/green cycles in order to have the congestion level track a given reference. It uses an integral control with adaptive gains, designed to provide fast tracking and wide stability margins. The gains are inverse-proportional to the derivative of the plant-function with respect to the control parameter, and are computed by infinitesimal perturbation analysis. Convergence of this technique is shown to be robust with respect to modeling uncertainties, computing errors, and other random effects. The framework is presented in the setting of stochastic hybrid systems, and applied to a particular traffic-light model. This is but an initial study and hence the latter model is simple, but it captures some of the salient features of traffic-light processes. The paper concludes with comments on possible extensions of the proposed approach to traffic-light grids with realistic flow models.
We present a flow-control technique in traffic-light intersections, aiming at regulating queue lengths to given reference setpoints. The technique is based on multivariable integrators with adaptive gains, computed at each control cycle by assessing
This paper presents a performance-regulation method for a class of stochastic timed event-driven systems aimed at output tracking of a given reference setpoint. The systems are either Discrete Event Dynamic Systems (DEDS) such as queueing networks or
This paper studies stochastic boundedness of trajectories of a nonvanishing stochastically perturbed stable LTI system. First, two definitions on stochastic boundedness of stochastic processes are presented, then the boundedness is analyzed via Lyapu
We study predictive control in a setting where the dynamics are time-varying and linear, and the costs are time-varying and well-conditioned. At each time step, the controller receives the exact predictions of costs, dynamics, and disturbances for th
As most natural resources, fisheries are affected by random disturbances. The evolution of such resources may be modelled by a succession of deterministic process and random perturbations on biomass and/or growth rate at random times. We analyze the