tailieunhanh - RECENT ADVANCES IN ROBUST CONTROL – NOVEL APPROACHES AND DESIGN METHODSE Part 4

Tham khảo tài liệu 'recent advances in robust control – novel approaches and design methodse part 4', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | Robust Control Using LMI Transformation and Neural-Based Identification for Regulating Singularly-Perturbed Reduced Order Eigenvalue-Preserved Dynamic Systems 79 x t x t u t _ 0 0 _ 0 y t x t u t where the objective of eigenvalue preservation is clearly achieved. Investigating the performance of this new LMI-based reduced order model shows that the new completely transformed system is better than all the previous reduced models transformed and nontransformed . This is clearly shown in Figure 9 where the 3rd order reduced model based on the LMI optimization transformation provided a response that is almost the same as the 5th order original system response. Fig. 9. Reduced 3rd order models . transformed without LMI non-transformed transformed with LMI output responses to a step input along with the non reduced _ original system output response. The LMI-transformed curve fits almost exactly on the original response. Case 2. For the example of case 2 in subsection for Ts sec. 200 input output data learning points and n with initial weights for the Ad matrix as follows w 80 Recent Advances in Robust Control - Novel Approaches and Design Methods the transformed A was obtained and used to calculate the permutation matrix P . The complete system transformation was then performed and the reduction technique produced the following 3rd order reduced model x t x t u t _ 0 0 y t x t u t with eigenvalues preserved as desired. Simulating this reduced order .