  Linear variable differential transformer (LVDT) sensors are used in
engineering applications due to their fine-grained measurements. However, these
sensors exhibit non-linear input-output characteristics, which decrease the
reliability of the sensing system. The contribution of this article is
three-fold. First, it provides an experimental study of the non-linearity
problem of the LVDT. Second, it proposes the design of a functional link
artificial neural network (FLANN) based non-linearity compensator model for
overcoming it. Finally, it validates the feasibility of the solution in
simulation, and presents a proof-of-concept hardware implementation on a
SPARTAN-II (PQ208)FPGA using VHDL in Xilinx. The model has been mathematically
derived, and its simulation study has been presented that achieves nearly 100%
linearity range. The result obtained from the FPGA implementation is in good
agreement with the simulation result, which establishes its actualization as
part of a general manufacturing process for linearity compensated LVDT sensors.
