Combination Of Model Predictive Control Research Articles

Model Predictive Lateral Pulse Jet Control of an Atmospheric Rocket

Uncontrolled direct fire atmospheric rockets exhibit high impact point dispersion, even at relatively short range, and, as such, have been employed as area weapons on the battlefield. To reduce the dispersion of a direct fire rocket, the use of a small number of short-duration lateral pulses acting as a control mechanism is investigated. A unique control law is reported that combines model predictive control and linear projectile theory for lateral pulse jet control of an atmospheric rocket. The impact point in the target plane is directly controlled. Through simulation, this model predictive flight control law is shown to efficiently reduce direct fire rocket dispersion. A parametric trade study on an example rocket configuration is reported that details the effect of the number and amplitude of individual pulse jets, as well as the effect of the flight control system computation cycle time.

Output-feedback predictive control of constrained linear systems via set-membership state estimation

This paper combines model predictive control (MPC) and set-membership (SM) state estimation techniques for controlling systems subject to hard input and state constraints. Linear systems with unknown but bounded disturbances and partial state information are considered. The adopted approach guarantees that the constraints are satisfied for all the states which are compatible with the available information and for all the disturbances within given bounds. Properties of the proposed MPC-SM algorithm and simulation studies are reported.

Optimizing the consolidation of titanium matrix composites

The high temperature consolidation of fiber reinforced metal matrix composite preforms seeks to eliminate matrix porosity (i.e. to increase the relative density) while simultaneously minimizing fiber microbending/fracture and the growth of reaction products at the fiber-matrix interface. By combining model predictive control concepts with previously developed time dependent consolidation models [18], a method is presented for the design of near optimal process schedules that evolve performance defining microstructural parameters (relative density, fiber fracture density and fiber-matrix reaction thickness) to prechosen microstructural goal states that result in composites of acceptable mechanical performance. The method is illustrated by exploring the design of process schedules for two titanium matrix composites with very different creep properties. Feasible process schedules resulting in acceptable composite mechanical performance are identified for a Ti 6Al 4V/SCS-6 system. However, the method reveals the absence of such schedules for the more creep resistant Ti 24Al 11Nb/SCS-6 intermetallic matrix composite. The optimization methodology is then used to explore modifications to the process environment, the composites component material properties (e.g. fiber strength or diffusion inhibiting coating), and the preforms initial microstructure that together enable the successful consolidation of the intermetallic matrix composite system.