  In remote control, efficient compression or representation of control signals
is essential to send them through rate-limited channels. For this purpose, we
propose an approach of sparse control signal representation using the
compressive sampling technique. The problem of obtaining sparse representation
is formulated by cardinality-constrained L2 optimization of the control
performance, which is reducible to L1-L2 optimization. The low rate random
sampling employed in the proposed method based on the compressive sampling, in
addition to the fact that the L1-L2 optimization can be effectively solved by a
fast iteration method, enables us to generate the sparse control signal with
reduced computational complexity, which is preferable in remote control systems
where computation delays seriously degrade the performance. We give a
theoretical result for control performance analysis based on the notion of
restricted isometry property (RIP). An example is shown to illustrate the
effectiveness of the proposed approach via numerical experiments.
