Optimal Controller Design for Virtual Sensing With Independent Noise Source Measurement

In certain applications, when the placement of sensors at the target location is not feasible, a common practice is to obtain the target information indirectly via sensors at other locations. This technique is known as virtual sensing (or soft sensing), and involves various signal processing techniques. Virtual sensing is applied to such systems to estimate the error signal for feedback control. However, issues regarding both stability and performance degradation become significant because the estimation is not precise. In this brief, we propose a virtual sensing control (VSC) method using a feedforward controller to compensate the mismatch between an error sensor and virtual sensor under the feedback control. The results show that when an independent noise source measurement is available, a feedforward controller is more appropriate than estimation as it maintains the stability of the feedback system while achieving a good performance enhancement. For such a VSC system, the design of both feedforward and feedback controllers is coupled. In this brief, we derive an optimal controller design method to maximize the noise reduction capability. We show the advantages of the proposed VSC method by applying it to the implementation of an active noise control system.