Due to stringent requirements placed on current autoland systems for commercial aircraft, simulation has become an essential tool for the development and certification of autoland systems. This thesis presents a simulation designed to support autoland control system design for twin jet engine aircraft. The simulation runs in the SIMULINK graphical simulation environment in MATLAB. The SIMULINK environment enables the designer to implement sensor models and control system designs in block diagram form. This allows for the straightforward modification of feedback paths, gains, and functional blocks. The designer has access to aircraft states, actuator states, and environmental parameters for use in the development and testing of a control system or sensor design.
The simulation presented in this thesis was verified against an existing twin jet engine aircraft simulation maintained by the National Aeronautics and Space Administration (NASA). The test condition selected for the verification was an autoland scenario under high wind conditions that stimulated the aircraft dynamics. The guidance during the test condition was provided by an autoland control system simulation based on the instrument landing system (ILS). The NASA simulation was run under the test condition and the commanded control surface deflections and states were recorded. The simulation presented in this thesis was then run open-loop from the same initial state using the commanded control surface deflections recorded from the NASA simulation.
A comparison of the state histories of the two simulations run under the test scenario demonstrates that the simulation presented in this thesis is consistent with the NASA simulation. However, since these are complex nonlinear simulations, there may be scenarios where the simulations perform differently.
The simulation presented in this thesis is a useful tool for the design of autoland control systems or sensors for twin jet engine transport aircraft. The SIMULINK environment enables a designer to easily implement and modify a control system or sensor model. The designer may then evaluate the design by using the analysis tools available in MATLAB.