Method and apparatuses for controlling high wing loaded parafoils
An adaptive guidance system (AGS) regulates the altitude and heading of a parasail to arrive at a target at a prescribed altitude. Since the altitude profile depends both on unknown wing loading, and wind magnitude and direction, the AGS estimates the glide slope and wind on the fly and provides a command to a stability augmentation system (SAS) that results in the desired glide slope and heading by performing a sequence of maneuvers and sensing the response. According to one embodiment, the SAS operates in the linear region and includes a PID controller that uses the difference between the actual heading and heading command to create an actuator output. The actuator output is limited by a position/rate limiter that imposes the physical limitations of the response time of the actuator/servos and position limits to prevent entering the nonlinear region. Alternatively, an adaptive SAS operates in both the linear and nonlinear region and includes a neural network (NN) that receives an error signal (difference between a reference model and actual heading) which is used to adapt the weights of the NN.
1. A stability augmentation method for an adaptive guidance system for a parasail, for use in regulating the altitude and heading of the parasail, said method comprising the acts of:
generating a reference model output signal based on a reference model;
receiving from an attitude and heading reference system, an actual heading rate signal;
generating an error signal by a summer, said error signal proportionate to the difference between said reference model output signal and said actual heading rate signal; and
responsive to said error signal, generating by a neural network an adaptive signal, wherein said neural network is responsive to both weights and to a vector comprising a plurality of known variables, wherein said weights of the neural network are adapted based on said error signal for use in regulating the altitude and heading of the parasail.
2. The method as claimed in claim 1 wherein said plurality of known variable includes the actual heading rate signal, the reference model output signal, and a control input to an actuator.
3. The method as claimed in claim 1 wherein said reference model includes a low order model for a parasail dynamics.
4. The method as claimed in claim 1 wherein said act of receiving said actual heading rate includes receiving said actual heading rate from an attitude and reference system.
5. The method as claimed in claim 1 further including the act of adding said adaptive signal to a linear stability augmentation system to generate an augmenting signal.
6. The method as claimed in claim 1 wherein said weights of the neural network are adapted according to the adaptation law
W i ( n+ 1)= W i ( n )− F*T*e f ( n )*φ i ( x ( n ))
where n denotes a sample time, T is a sample interval, e f (n) is a filtered version of the error signal, and x(n) denotes an input vector.