This paper reports on a receding horizon filtering for mobile robot systems with cross-correlated sensor noises and uncertainties. Also, the effect of uncertain parameters in the state of the tracking error model performance is considered. A distributed fusion receding horizon filter is proposed. The distributed fusion filtering algorithm represents the optimal linear combination of the local f...

In some situations, when an external disturbance occurs, humans can rock stably backward and forward by lifting the toe or the heel to keep the upright balance without stepping. Many control schemes have been proposed for standing balance control under external disturbances without stepping. But, in most of them researchers have only considered a flat foot phase. In this paper a framework is pr...

A receding horizon filtering problem for nonlinear continuous-time stochastic systems is considered. The paper presents the optimal receding horizon filtering equations. Derivation of the equations is based on the Kushner-Stratonovich and Fokker-Planck-Kolmogorov equations for conditional and unconditional density functions. This result could be a theoretical basis for the optimal control in no...

Control Lyapunov functions (CLF’s) are used in conjunction with receding horizon control (RHC) to develop a new class of receding horizon control schemes. In the process, strong connections between the seemingly disparate approaches are revealed, leading to a unified picture that ties together the notions of pointwise min-norm, receding horizon, and optimal control. This framework is used to de...

A framework for robustness analysis of input constrained nite receding horizon control is presented. Under the assumption of quadratic upper bounds on the nite horizon costs, we derive suucient conditions for robust stability of the standard discrete-time linear-quadratic receding horizon control formulation. This is achieved by recasting conditions for nominal and robust stability as an implic...

This paper deals with unconstrained receding horizon control of nonlinear systems with a general, nonnegative terminal cost. Earlier results have indicated that when the terminal cost is a suitable local control Lyapunov function, the receding horizon scheme is stabilizing for any horizon length. In a recent paper, the authors show that there always exist a uniform horizon length which guarante...

Model-error control synthesis is a nonlinear robust control approach that uses an optimal solution to cancel the effects of modelling errors and external disturbances on a system. In this paper the optimal solution for a modified approximate receding-horizon problem is used to determine the model error in an aeroelastic system, which has several uncertain parameters, including a nonlinear sprin...

This paper presents a vision-based receding horizon control algorithm for enabling a micro air vehicle to fly autonomously through an unknown urban environment. A vision-based geometry estimation algorithm is used to generate a map of the environment and provide obstacle avoidance constraints on permissible MAV trajectories. The geometry estimation process is comprised of three components: a fe...

Receding horizon control is based on iteratively solving an open-loop nite horizon optimization problem. Despite its success in a variety of industrial applications, theoretical issues such as stability were not completely addressed until recently. It was shown in 5] that by utilizing a suitable Control Lyapunov Function (CLF) as terminal cost, the stability of the receding horizon scheme can b...