Abstract
AbstractIn this paper, we investigate the design of a safe hybrid controller for an aircraft that switches between a classical linear quadratic regulator (LQR) controller and a more intelligent artificial neural network (ANN) controller. Our objective is to switch safely between the controllers, such that the aircraft is always recoverable within a fixed amount of time while allowing the maximum time of operation for the ANN controller. There is a priori known safety zone for the LQR controller operation in which the aircraft never stalls, over accelerates, or exceeds maximum structural loading, and hence, by switching to the LQR controller just before exiting this zone, one can guarantee safety. However, this priori known safety zone is conservative, and therefore, limits the time of operation for the ANN controller. We apply reachability analysis to expand the known safety zone, such that the LQR controller will always be able to drive the aircraft back to the safe zone from the expanded zone (“recoverable zone") within a fixed duration. The “recoverable zone" extends the time of operation of the ANN controller. We perform simulations using the hybrid controller corresponding to the recoverable zone and observe that the design is indeed safe.
Highlights
Different types of controller designs have been investigated for aircraft control, such as Linear Quadratic Regulators [28], Fuzzy Logic (FL) [8], and Artificial Neural Networks [26]
Our solution is a “hybrid controller” consisting of a simplex like architecture [7], wherein, we switch between the artificial neural network (ANN) and linear quadratic regulator (LQR) controller in such a way that safety is guaranteed by the switching logic, that is, the aircraft is always recoverable from a stall within a fixed amount of time if it occurs
A longer duration of operation for the ANN controller is desirable for the learning process, so we provide a method to extend the safe zone to a larger set (“recoverable zone”), which guarantees that the aircraft recovers within a fixed amount of time if a stall occurs
Summary
Different types of controller designs have been investigated for aircraft control, such as Linear Quadratic Regulators [28], Fuzzy Logic (FL) [8], and Artificial Neural Networks [26]. The LQR controllers provide an optimal controller for linear time invariant (LTI) systems that minimizes a quadratic cost function and guarantees stability and robustness. Things like over-acceleration can cause the aircraft to gain too much energy and enter into unstable modes, while rapid de-acceleration and hard maneuvers will cause increased structural loading, leading to broken lifting platforms. Another issue is that of stall, in which the airflow over the lifting section crosses a “critical angle of attack”, compromising the lift generation. Though ANN-based adaptive controllers are capable of handling these situations, guaranteeing safe functionality of these systems remains a challenge due to the complexity of these controllers. Our solution is a “hybrid controller” consisting of a simplex like architecture [7], wherein, we switch between the ANN and LQR controller in such a way that safety is guaranteed by the switching logic, that is, the aircraft is always recoverable from a stall within a fixed amount of time if it occurs
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