In remote control systems, efficient representation of control signals is one of the crucial issues because of bandwidth-limitedness of the communication channel, such as a wireless communication link, between the controller and the controlled object. Recently, a new method based on compressed sensing has been proposed, in which control signals are sparsely representation based on l^1-l^2 optimization. There exist however so many methods other than l^1-l^2 optimization for compressed sensing. In this study, we perform a comparative study of sparsity-promoting methods in compressed sensing, and reveal their advantages and disadvantages by simulation in view of remote control over rate-limited networks.
