5. Neural networks

3. Objective

140 Adaptive Robust Control Systems

tuned to a particular quadrotor.

The basic inner loop controller of any helicopter deals with maintaining a specified height above ground, i.e. altitude, and maintaining a particular pose, or attitude. The attitude in turn

The standard approach is decentralized or cascaded PID controllers for the various control variables (in this case: roll f, pitch θ, yaw ψ, altitude z), these controllers will have to be tuned for each particular quadrotor UAV. In general, any non-adaptive controller will need to be

In this chapter we employ neural networks to design an adaptive controller that is system unspecific, i.e. it should work for any quadrotor system. It learns the system parameters online,

Indirect adaptive control is when the controller estimates the plant to predict its state variables

Direct adaptive control is when there is no plant identification, instead the controller parame-

MRAC is a direct adaptive control method (refer Figure 2), however in this chapter we shall be

In MRAC we define a reference model that responds to the input signal (r) as we would like our plant to respond. The controller generates a control signal (u) based on its control law which it expects will make the plant output (y) follow the reference output (yref). Depending on the deviation (or error), the adjustment mechanism will update the control law (by modifying parameters) of the controller. This process is repeated iteratively so that the plant follows the reference. The beauty of the approach taken in this chapter is that we needn't formalize the control logic. We will delve deeper into neural networks before returning to the problem at hand. For the

allows the helicopter to translate in the x-y plane assuming altitude is held constant.

i.e. in-flight. The challenge is to keep the system stable during online learning.

ters are modified on the basis of the error the system has with the reference.

4. Indirect model reference adaptive control

and these are used to modify the controller parameters.

Figure 2. MRAC block diagram. Image courtesy of Wikipedia under CC license.

taking a mixed approach to the problem.
