Longitudinal flight control in a windshear via H-infinity methods

Gain-scheduled directional guidance controller design using a genetic algorithm for automatic precision landing

“…10, the following parameters of the controller were optimized: the shapes of the error derivative membership functions shown in Fig. 6, the scaling parameters defined in (14), and the decay rate σ given in (12). The influence of wind shear turbulence on the aircraft in landing flight was considered in the optimization of those parameters.…”

“…Examples include a linear quadratic Gaussian with a Loop Transfer Recovery technique for commercial aircrafts encountering wind shear [7,8], an H ∞ − output feedback synthesis technique for an F-14 aircraft [9], and finite horizon H ∞ − techniques for the F/A-18A [10]. Other examples include a mixed 2 / H H ∞ − technique with gain scheduling [11], an H ∞ − control problem in which the wind shear effect is minimized [12], and an H ∞ − control technique for robust gain-scheduled controller design to handle the longitudinal auto-landing maneuvers of aircraft encountering dangerous wind shear [13]. Furthermore, [14,15] propose an optimal path and control law to enhance the survival capabilities of aircraft in dangerous auto-landing with wind shear, and an inverse dynamic model approach to auto-landing controller design combined with a neural network is proposed in [16].…”

Automatic landing control using H-inf control and dynamic inversion

“…1 Most aircraft have ALSs based on the instrumental landing system (ILS), using different conventional control laws (proportional-derivative (PD), proportional-integral (PI), proportional-integral-derivative (PID)) for the altitude and descent velocity control, [2][3][4][5][6] PD or PID conventional laws for the pitch angle and pitch rate control as well as different laws based on the state vector, dynamic inversion concept, with command filters, dynamic compensators, and state observers. [7][8][9][10][11][12][13] In recent years, lots of scientific researchers have applied the intelligent concepts for the automatic landing of the aircraft; they use the optimal synthesis H 2 , H 1 , H 2 =H 1 , 5,14,15 the adaptive synthesis based on dynamic inversion theory and neural networks theory, [16][17][18][19] or fuzzy techniques. [20][21][22] In the research area of optimal synthesis, Shue and Agarwal 23 have developed a mixed technique for the H 2 /H 1 control of the landing, while Ochi and Kanai 24 have used the H 1 control technique to design aircraft automatic approach and landing.…”