Seite - 204 - in Adaptive and Intelligent Temperature Control of Microwave Heating Systems with Multiple Sources

Bibliography [LJ00] Chin-Teng Lin and Chong-Ping Jou. GA-based fuzzy reinforcement learning for control of a mag- netic bearing system. Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on, 30(2):276– 289,2000. [Lju97] Lennart Ljung. Nonlinear black box models in sys- temidentification. InProceedingsof the1997IFACIn- ternationalSymposumonAdvancedControlofChemical Processes,pages1–13,1997. [Lju98] LennartLjung. Systemidentification. Springer,1998. [LLG14] Yingguang Li, Nanya Li, and James Gao. Tool- ing design and microwave curing technologies for themanufacturingoffiber-reinforcedpolymercom- posites in aerospace applications. The International Journal of Advanced Manufacturing Technology, 70(1- 4):591–606,2014. [LLHG14] NanyaLi,YingguangLi,XiaozhongHao,andJames Gao. A comparative experiment for the analysis of microwave and thermal process induced strains of carbon fiber/bismaleimide composite materials. CompositesScienceandTechnology, 2014. [LM03] NicholasELeadbeaterandMariaMarco. Rapidand amenable Suzuki coupling reaction in water using microwave and conventional heating. The Journal of organic chemistry, 68(3):888–892,2003. [LMAC02] D Limo´n Marruedo, T Alamo, and EF Camacho. Stabilityanalysisofsystemswithboundedadditive uncertainties based on invariant sets: Stability and feasibility of MPC. In American Control Conference, 2002. Proceedings of the 2002, volume 1, pages 364– 369. IEEE,2002. [LN95] Asriel U Levin and Kumpati S Narendra. Control of nonlinear dynamical systems using neural net- works. ii. observability, identification, and control. 204