Title of thesis: A STUDY ON DISTRIBUTED RECEDING HORIZON CONTROL Wann-Jiun Ma, Master of Science, 2011 Thesis directed by: Professor Nuno Martins Department of Electrical and Computer Engineering We consider a distributed control problem comprising of multiple sub-systems with one-controller at each sub-system. We apply a recent result about suboptimal receding horizon control that analytically...

A receding horizon FIR filter is suggested for discrete time-varying systems, combining the Kalman filter with the receding horizon strategy. The suggested filter is shown to be an FIR structure that has many good inherent properties. The suggested filter is represented in an iterative form and also in a standard FIR form. The suggested filter turns out to be a remarkable deadbeat observer that...

We present a receding-horizon cooperative search algorithm that jointly optimizes routes and sensor orientations for a team of autonomous agents searching for a mobile target. By sampling the region of interest at locations with high target probability, we reduce the continuous search problem to an optimization on a finite graph. Paths are computed on this graph using a receding horizon approac...

Abstract Model-error control synthesis is a nonlinear robust control approach that mitigates the effects of modeling errors and disturbances on a system by providing corrections to the nominal control input directly. In this paper model-error control synthesis is applied to the spacecraft attitude control problem, where the model-error vector is computed using a receding-horizon approximation. ...

A receding horizon Kalman FIR filter is presented that combines the Kalman filter and the receding horizon strategy when the horizon initial state is assumed to be unknown. The suggested filter is an FIR filter form which has many good inherent properties. It can always be defined irrespective of singularity problems caused by unknown information about the horizon initial state. The suggested f...

We address stability of receding horizon control for stochastic linear systems with additive noise and bounded control authority. We construct tractable and recursively feasible receding horizon control policies that ensure a mean-square bounded system in closed-loop if the noise has bounded forthorder moment, the unexcited system is stabilizable, the system matrix A is Lyapunov stable, and the...

We present a receding horizon control algorithm for compensation of backlash at the input of a stable linear system under control rate constraints. The problem is first posed as a receding horizon optimal control problem by modelling backlash as a piecewise affine system with a state space partition consisting of three regions. This optimal control problem involves solving, at each step, 3 quad...

This technical report is an extended version of the paper ’A Receding Horizon Algorithm for Informative Path Planning with Temporal Logic Constraints’ accepted to the 2013 IEEE International Conference on Robotics and Automation (ICRA). This paper considers the problem of finding the most informative path for a sensing robot under temporal logic constraints, a richer set of constraints than hav...

A receding horizon Kalman finite-impulse response (FIR) filter is suggested for continuous-time systems, combining the Kalman filter with the receding horizon strategy. In the suggested filter, the horizon initial state is assumed to be unknown. It can always be obtained irrespective of unknown information on the horizon initial state. The filter may be the first stochastic FIR form for continu...