  Multichannel active noise control (ANC) systems are designed to create a
large zone of quietness (ZoQ) around the error microphones, however, the
placement of these microphones often presents challenges due to physical
limitations. Virtual sensing technique that effectively suppresses the noise
far from the physical error microphones is one of the most promising solutions.
Nevertheless, the conventional multichannel virtual sensing ANC (MVANC) system
based on the multichannel filtered reference least mean square (MCFxLMS)
algorithm often suffers from high computational complexity. This paper proposes
a feedforward MVANC system that incorporates the multichannel adjoint least
mean square (MCALMS) algorithm to overcome these limitations effectively.
Computational analysis demonstrates the improvement of computational efficiency
and numerical simulations exhibit comparable noise reduction performance at
virtual locations compared to the conventional MCFxLMS algorithm. Additionally,
the effects of varied tuning noises on system performance are also
investigated, providing insightful findings on optimizing MVANC systems.
