The remotely controlled laboratory setup for Active Noise Control (ANC) developed by Blekin-ge Institute of Technology, Sweden provides an efficient learning platform for the students to implement and learn ANC algorithms with real world physical system, hardware and signals. The initial laboratory prototype based on a Digital Signal Processor (DSP) TMS320C6713 from Texas Instruments (TI) was successfully tested with Filtered-x Least Mean Square (F-XLMS) algorithm applied to control noise in a ventilation duct. The resources of the DSP platform used in the remote laboratory setup enable testing and investigating substantially more challenging and computationally demanding algorithms. In this paper, we expand the horizon of the laboratory setup by testing more advanced and complicated single channel feed forward ANC algorithms. Filtered-x versions of algorithms such as the normalized least mean square (N-LMS), leaky least mean square (L-LMS), Filtered-U recursive least mean square (FURLMS) and recursive least square (RLS) algorithm etc. have been implemented utilizing the remote web based client provided in the remote laboratory. A comprehensive performance comparison of the aforementioned algorithms for the remote laboratory setup is presented to demonstrate the viability of the remote laboratory.