The adjoint gradient computation for parameter identification of a tribology test bench

In this article, we discuss the application of an optimization algorithm to determine the parameters for the system dynamics of a tribometer. An optimization algorithm is used to identify the parameters through matching a simulation signal with a measurement signal from the real test rig. The optimization problem is solved using an indirect method that computes the gradient of a cost function with respect to a parameter set. To reduce the computational cost of the gradient determination, the adjoint gradient method is introduced. The method in this article avoids the numerical gradient computation and can be used for the iterative identification of optimal parameters. These parameters provide the basis for a digital twin of such a tribometer for e.g., studying the real friction by eliminating the tribometer vibrations from the measured force signal.