MBPC is a feedback-control methodology suitable to enforce efficiently hard constraints on the variables of the controlled system. It is shown that the method hinges upon a constrained open-loop optimal control problem along with the adoption of the so-called receding-horizon control strategy. In the important case of time-invariant linear saturated ANCBI systems, MBPC algorithms can be devised...

C. R. Fuerte-Esquivel Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Mexico Abstract A general approach to real-time transient stability control is described, yielding various complementary techniques: pure preventive, open-loop emergency, and closed-loop emergency controls. Recent progress in terms of a global transient stability-constrained optimal power flow is presented, yieldin...

We present an open loop control design allowing to steer a wheeled mobile robot along a prespecified smooth geometric path, minimizing a given cost index and satisfying a set of dynamical constraints. Using the concept of “differential flatness,” the problem is equivalent to the selection of the optimal time parametrization of the geometric path. This parametrization is characterized by a diffe...

We consider the stochastic optimal control problem of McKean-Vlasov stochastic differential equation where the coefficients may depend upon the joint law of the state and control. By using feedback controls, we reformulate the problem into a deterministic control problem with only the marginal distribution of the process as controlled state variable, and prove that dynamic programming principle...

We study a Hamilton± Jacobi partial di€ erential equation, arising in an optimal control problem for an a ne non-linear singularly perturbed system. This equation is solvable i€ there exists a special invariant manifold of the corresponding Hamiltonian system. We obtain exact slow± fast decomposition of the Hamiltonian system and of the special invariant manifold into slow and fast components....

In this paper the problem of stabilizing linear discrete-time systems under state and control linear constraints is studied. Based on the concept of positive invariance, existence conditions of linear state feedback control laws respecting both the constraints are established. These conditions are then translated into an algorithm of linear programming. 1. Introduction Most industrial systems m...

We introduce a new heuristic algorithm for the problem of finding minimum size loop cutsets in multiply connected belief networks. We compare this algorithm to that proposed in [Suermondt and Cooper, 1988]. We provide lower bounds on the performance of these algorithms with respect to one another and with respect to optimal. We demonstrate that no heuristic algorithm for this problem can be gua...