In this thesis we study receding horizon control strategies for stochastic discrete-time linear systems with additive noise. This study is divided into two parts: First, we compare the performance of different receding horizon control techniques under constrained and unconstrained control input settings for some representative systems. It appears from our simulations that while in an unconstrai...

This paper deals with the application of receding horizon methods to hover and forward flight models of an experimental tethered flying wing developed at Caltech. The dynamics of the system are representative of a vertical landing and take off aircraft, such as a Harrier around hover, or a thrust-vectored aircraft such as F18-HARV or X-31 in forward flight. The adopted control methodology is a ...

The art of multi-objective design is to extract the best compromise among conflicting requirements. The analytical multi-objective parameter synthesis adopts closed-form specifications that make the multi-objective design in linear systems computationally efficient. In this paper, the analytical multi-objective parameter synthesis method is extended to nonlinear systems via the state-dependent ...

Model Receding Horizon LTL Planner

We propose a receding horizon control strategy that readily handles systems that exhibit interval-wise total energy constraints on the input control sequence. The approach is based on a variable optimization horizon length and contractive final state constraint sets. The optimization horizon, which recedes by N steps every N steps, is the key to accommodate the interval-wise total energy constr...

A stochastic receding-horizon control approach for constrained Linear Parameter Varying discrete-time systems is proposed in this paper. It is assumed that the time-varying parameters have stochastic nature and that the system’s matrices are bounded but otherwise arbitrary nonlinear functions of these parameters. No specific assumption on the statistics of the parameters is required. By using a...