Distributed moving horizon estimation for nonlinear constrained systems

Distributed moving horizon estimation for nonlinear constrained systems

Constrained state estimation for nonlinear discrete-time systems: stability and moving horizon approximations

State estimator design for a nonlinear discrete-time system is a challenging problem, further complicated when additional physical insight is available in the form of inequality constraints on the state variables and disturbances. One strategy for constrained state estimation is to employ online optimization using a moving horizon approximation. In this article we propose a general theory for c...

Computationally Efficient, Approximate Moving Horizon State Estimation for Nonlinear Systems

Moving horizon estimation for discrete-time nonlinear systems is addressed by using fast optimization algorithms for which stability results under general conditions are ensured. The solution of the on-line moving horizon estimation problem is obtained by using the sampling time to solve a reference problem with model-predicted measurements while waiting for the next measurement. In order to co...

Constrained Split Rate Estimation by Moving Horizon

The paper presents a method for the constrained Moving Horizon Estimation of origin-destination (OD) matrices for traffic networks. In traffic systems split ratios are important parameters for OD estimation and for control problems as well. The paper treats the general constrained Moving Horizon Estimation problem for traffic systems modelled in terms of linear time varying system and solves th...

Moving horizon estimation for hybrid systems

We propose a state smoothing algorithm for hybrid systems based on Moving Horizon Estimation (MHE) by exploiting the equivalence between hybrid systems modeled in the Mixed Logic Dynamical form and piecewise affine systems. We provide sufficient conditions on the time horizon and the penalties on the state at the beginning of the estimation horizon to guarantee asymptotic convergence of the MHE...