On Useful Redundancy in Dynamic Inverse Problems Related Optimization

In this paper, it is pointed-out that inverse problems arising in nonlinear control systems design such as state reconstruction and/or parameter estimation are naturally redundant. It is also shown that this redundancy can be used to enhance avoiding singularity heuristics. Some related algorithms are discussed and illustrated on a simple example of chemical reactors. These algorithms can be added to any optimization algorithm in order to enforce the singularity avoidance capabilities.