Comparison of intelligent, adaptive, and nonlinear flight control laws

Seven different nonlinear control laws for multiaxis control of a high-perf ormance aircraft are compared in simulation. The control law approaches are fuzzy logic control, backstepping adaptive control, neural network augment ed control, variable structure control, and indirect adaptive versions of m odel predictive control and dynamic inversion,In addition, a more conventio nal scheduled dynamic inversion control la,v is used as a baseline. In some of the cases, a stochastic genetic algorithm was used to optimize fixed pa rameters during design. The control laws are demonstrated on a six-degree-o f-freedom simulation with nonlinear aerodynamic and engine models, actuator models with position and rate saturations, and turbulence. Simulation resu lts include a variety of single- and multiple-axis maneuvers in normal oper ation and with failures or damage, The specific failure and damage cases th at are examined include single and multiple lost surfaces, actuator hardove rs, and an oscillating stabilator case. There are also substantial differen ces between the control law design and simulation models, which are used to demonstrate some robustness aspects of the different control laws.