Design methodology of tensor product based control models via HOSVD and LMIs

This paper aims at solving the conflicts of the computational needs of building tensor product (TP) based control models having high approximation accuracy and practical aspects of their applicability w.r.t. system stability and feasibility. Therefore first we propose a HOSVD (higher order singular value decomposition) based methodology capable of implementing any differential equation systems of a dynamic model in TP model form with specific basis functions whereupon the linear matrix inequalities (LMI) based controller design techniques and stability analysis can be executed. Second, we intend to find a tradeoff between the TP modelling accuracy, hence system performance, and the controller complexity which is bounded by the available real time computation power at hand. As an example a detailed control design is given.