The research issue addressed in this research initiation proposal is to develop a design methodology of corrective filters which would recognize and compensate the impact of the working environment on the dynamic characteristics of sensors. Significant improvements in the accuracy and reliability of measurements may be possible with these self-tuning sensors to improve the performance of existing production systems. This approach may be able to improve the feasibility of implementing high performance control, monitoring and diagnosis of manufacturing systems needed for the factories of the future. The systematic approach to the design of self-tuning sensors for manufacturing systems will attempt to advance in-process metrology by integrating two important elements of modern engineering. These elements are: (1) The modeling of sensors installed on particular machine tools as components of multi-degree-of-freedom systems. The derived models, based on first principles, will encapsulate the a priori knowledge about the sensors, machines tools and relevant manufacturing processes; and (2) the time series based, on-line identification of real-time parameters of these models in the presence of stochastic disturbances. The goal of this research is to implement a prototype corrective filter capable of tracking and compensating the impact of the environment on the dynamic performance of typical force and torque sensors. This filter will be built as a high speed, multi-processor system.
