| 575 - 575 |
Multiple model approaches to modelling and control
Johansen TA, Foss BA |
| 576 - 590 |
Process identification with multiple neural network models
Eikens B, Karim MN |
| 591 - 604 |
Non-linear dynamic system identification: a multi-model approach
Boukhris A, Mourot G, Ragot J |
| 605 - 619 |
Analytic Framework for blended multiple model systems using linear local models
Leith DJ, Leithead WE |
| 620 - 628 |
On the interpretation of local models in blended multiple model structures
Shorten R, Murray-Smith R, Bjorgan R, Gollee H |
| 629 - 642 |
Estimation of multiple order models in the delta-domain
Kuznetsov AG, Bowyer RO, Clark DW |
| 643 - 658 |
Lazy learning for local modelling and control design
Bontempi G, Birattari M, Bersini H |
| 659 - 675 |
Estimation and model predictive control of non-linear batch processes using linear parameter varying models
Lakshmanan NM, Arkun Y |
| 676 - 685 |
Non-linear control system design via fuzzy modelling and LMIs
Kiriakidis K |
| 686 - 701 |
Constrained quadratic stabilization of discrete-time uncertain non-linear multi-model systems using piecewise affine state-feedback
Slupphaug O, Foss BA |
| 702 - 715 |
A parametrization of piecewise linear Lyapunov functions via linear programming
Julian P, Guivant J, Desages A |
| 716 - 726 |
A minimax approach for multi-objective controller design using multiple models
Piguet Y, Holmberg U, Longchamp R |
| 727 - 739 |
A multi-model solution for the control of chaos
Duchateau A, Bradshaw NP, Bersini H |
| 740 - 754 |
Neural-fuzzy scheduling of H-infinity robust controllers for a high performance fighter aircraft under a Herbst-like manoeuvre
Wang JL, Zhang WQ |
