Special Issue on Sparsity‐inducing Methods in Control Theory.

For example, sparsity-inducing optimization has proven to be a powerful principle for developing resilient estimation and control algorithms that can withstand random system failures and malicious attacks. From a methodological viewpoint, sparsity-inducing optimization is a powerful paradigm for developing control and estimation schemes that are robust to the aforementioned sparse uncertainties. Modern control theory is challenged by an increasing complexity of the systems to be controlled and meanwhile by the increasing level of demanded performance. [Extracted from the article]