179 - 186 |
Two-stage subspace identification for softsensor design and disturbance estimation Kano M, Lee S, Hasebe S |
187 - 204 |
Intelligent state estimation for fault tolerant nonlinear predictive control Deshpande AP, Patwardhan SC, Narasimhan SS |
205 - 215 |
Improved performance in the multi-unit optimization method with non-identical units Woodward L, Perrier M, Srinivasan B |
216 - 230 |
Decentralized robust PI controller design for an industrial boiler Labibi B, Marquez HJ, Chen TW |
231 - 240 |
Application of gap metric to model bank determination in multilinear model approach Du JJ, Song CY, Li P |
241 - 246 |
Optimal time-varying potential profile for electro-hydro-dimerization reactions Boovaragavan V, Bashal CA |
247 - 260 |
Geometric estimation of nonlinear process systems Alvarez J, Fernandez C |
261 - 271 |
A self-growing hidden Markov tree for wafer map inspection Chen JH, Hsu CJ, Chen CC |
272 - 287 |
An alternative structure for next generation regulatory controllers. Part II: Stability analysis, tuning rules and experimental validation Mukati K, Rasch M, Ogunnaike BA |
288 - 296 |
Batch process monitoring with tensor factorization Hu KL, Yuan JQ |
297 - 313 |
Boundary geometric control of a counter-current heat exchanger Maidi A, Diaf M, Corriou JP |
314 - 327 |
Model predictive control monitoring using multivariate statistics AlGhazzawi A, Lennox B |
328 - 339 |
Unconstrained networked decentralized model predictive control Vaccarini M, Longhi S, Katebi MR |
340 - 348 |
Direct least-squares estimation and prediction of rational systems: Application to food storage Keesman KJ, Doeswijk TG |
349 - 352 |
Guaranteed dominant pole placement with PID controllers Wang QG, Zhang ZP, Astrom KJ, Chek LS |
353 - 357 |
Enhanced process activation method to remove harmonics and input nonlinearity Je CH, Lee J, Sung SW, Lee DH |
358 - 363 |
Computation of arrival cost for moving horizon estimation via unscented Kalman filtering Qu CC, Hahn J |
364 - 369 |
Synthesis of run-to-run repetitive control methods using finite impulse response models Lee KS, Won W, Lee JH |