Dynamic Response Simulation Through System Identification

Non-linear dynamic systems, such as those associated with structural testing of vehicles, are considered. The vehicle, or a substructure, is mounted in a test rig that is normally driven by servo-hydraulic actuators. The specimen and test rig form a non-linear dynamic system. These test systems assure the durability of vehicles by reproducing a structural response time history that has been measured in a road test of a vehicle. For this, a force or displacement input to the actuators ’ control system must be determined as a function of time. Current practice employs an iterative algorithm, using a frequency response func-tion to represent the system. The conventional iteration is a particular version of well established numerical techniques for solving non-linear systems. However, the success of the iteration is dependent on the degree of non-linearity and on the level of noise in the signals coming from the system. This paper advocates identifying the system to improve its representation in the iterative algorithm. The theory underpinning the alternative algorithm is presented and a comparison is made between the performances of the two algorithms, using computer simulations based on Duffing’s equation. These simulations show that, even for this simple model, the alternative algorithm is faster, more reliable and more tolerant of response noise. Key words: Laboratory simulation testing, dynamic system, spectral analysis, random signal, Duffing’s equation, non-linear algebraic equations, numerica