Research Experience and InterestRobust Design and Its Integration with Control Development of integrated approaches for robust design for both static and dynamic system under various uncertainties with help of the perturbation theory, and control theory, which includes q Variable sensitivity robust design for unknown process; q Multi-objective optimization based robust design under model uncertainties; q Stability-based robust design for dynamic system under model uncertainty; q Intelligent integration of design and control for complex process Intelligent Modeling and Control of Distributed Parameter Systems (DPS) q Development of novel spatiotemporal LS-SVM modeling approach for the nonlinear DPS; q Development of novel spatiotemporal ELM modeling approach and the adaptive KL-Fuzzy modeling approach for the time-varying DPS. Data Learning and Intelligent Manufacture q Development of various LS-SVM method, including the probabilistic LS-SVM for distribution modeling, and robust LS-SVM for uncertain data, and the local LS-SVM modeling with the global regularization for nonlinearly distributed data; q Development of several ELM method, including the robust ELM method for uncertain data, and the online RELM with adaptive regulation factor for time-varying nonlinear system, and the online probabilistic ELM for distribution modeling of complex batch forging processes. Modeling and Control for Forging Process q Development of various modeling methods in order to represent the dynamics of forging process under different working conditions. The work involves the physical and data-driven modeling approaches. q Development of some control approaches based on the feature of the forging process, which are employed to satisfy the different forging requirements under different working conditions. |
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