Robust flight control systems are synthesized for the longitudinal motion of a hypersonic aircraft. Aircraft motion is modeled by nonlinear longitudinal dynamic equations containing 28 uncertain parameters. Each controller is designed using a genetic algorithm to search a design coefficient space; Monte Carlo evaluation at each search point estimates stability and performance robustness. Robustness of a compensator is indicated by the probability that stability and performance of the closed-loop system will fall within allowable bounds, given likely parameter variations. A stochastic cost function containing engineering design criteria (in this case, a stability metric plus 38 step-response metrics) is minimized, producing feasible control system coefficient sets for specified control system structures. This approach trades the likelihood of satisfying design goals against each other, and it identifies the plant parameter uncertainties that are most likely to compromise robustness goals. The approach makes efficient use of computational tools and broadly accepted engineering knowledge to produce practical control system designs.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Aerospace Engineering
- Space and Planetary Science
- Electrical and Electronic Engineering
- Applied Mathematics