Hello DWG,
I think we are not talking about the same thing. what you are describing is the control command, that is the stability objective of the FCS. it is C*U for the 777, for most fighters it is either a pitch rate/AOA at low speeds, a G command at high speed.
To achieve this goal, an augmented system (an aircraft with a computerized FCS) will have input(pilots command)/output(achieved parameter). For the FCS to know how to move the control surfaces in relation to actual conditions, you need a model; and that model is based on the combination of the equations of motion for a rigid body and a state/output equation (the two equations that i described).
All my sources (research, graduate, engineering) clearly describe the FCS to be modeled after equations of motion(1,2). The F-35 CLAW is explicitly modeled after those equations too(3).
What changes between it and a linear quadratic system is the way the control surface movement needed is computed(1(chapter 4),3).
Linearity here refers to its theoritical definition, that is, superposition and proportionality and its application to FCS is understood to model control surfaces motion within a given speed/altitude frame as being purely linear in their output. This is not the case for high AOA, when aeromecanic coupling, surface saturation etc... In those cases the actual control surface motion to output relationship is not predictable. NDI system, by computing the control surface motion needed, taking into account the non linear evolution of the control surface efficiency matrix handles those kinds of non linearity.
I think you may be talking about gains, which are modified filters after the control surface needed is computed.
If that is not too personal, i'd be interested in knowing what your job consists in. As i've said, this is not my line of work and i'm only discussing based on the documentation i find 
I have probably mistaken a research paper developing an online NN based on the F-35 FCS for the operational one. my bad.
(1)Tian,L. 1999. A study of nonlinear flight control system designs. Iowa State University.
(2)Campbell S.F and Kaneshige J.T. 2009. A Nonlinear Dynamic Inversion Predictor-Based Model Reference Adaptive Controller for a Generic Transport Model. IEEE
(3)Nixon D.W 2004 Lockheed-MartinFlight Control Law Development for the F-35 Joint Strike Fighter. miadc presentation