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Adaptive Fuzzy Torque Control of Passive Torque Servo Systems Based on Small Gain Theorem and Input-to-state Stability 被引量:10
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作者 WANG Xingjian 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2012年第6期906-916,共11页
Passive torque servo system (PTSS) simulates aerodynamic load and exerts the load on actuation system, but PTSS endures position coupling disturbance from active motion of actuation system, and this inherent disturb... Passive torque servo system (PTSS) simulates aerodynamic load and exerts the load on actuation system, but PTSS endures position coupling disturbance from active motion of actuation system, and this inherent disturbance is called extra torque. The most important issue for PTSS controller design is how to eliminate the influence of extra torque. Using backstepping technique, adaptive fuzzy torque control (AFTC) algorithm is proposed for PTSS in this paper, which reflects the essential characteristics of PTSS and guarantees transient tracking performance as well as final tracking accuracy. Takagi-Sugeno (T-S) fuzzy logic system is utilized to compensate parametric uncertainties and unstructured uncertainties. The output velocity of actuator identified model is introduced into AFTC aiming to eliminate extra torque. The closed-loop stability is studied using small gain theorem and the control system is proved to be semiglobally uniformly ultimately bounded. The proposed AFTC algorithm is applied to an electric load simulator (ELS), and the comparative experimental results indicate that AFTC controller is effective for PTSS. 展开更多
关键词 flight simulation adaptive control fuzzy control passive torque servo system electric load simulator extra torque small gain theorem input-to-state stability
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Energy Management System Design and Testing for Smart Buildings Under Uncertain Generation (Wind/Photovoltaic) and Demand
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作者 Syed Furqan Rafique Jianhua Zhang +3 位作者 Muhammad Hanan Waseem Aslam Atiq Ur Rehman Zmarrak Wali Khan 《Tsinghua Science and Technology》 SCIE EI CAS CSCD 2018年第3期254-265,共12页
This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management ... This study provides details of the energy management architecture used in the Goldwind microgrid test bed. A complete mathematical model, including all constraints and objectives, for microgrid operational management is first described using a modified prediction interval scheme. Forecasting results are then achieved every 10 min using the modified fuzzy prediction interval model, which is trained by particle swarm optimization.A scenario set is also generated using an unserved power profile and coverage grades of forecasting to compare the feasibility of the proposed method with that of the deterministic approach. The worst case operating points are achieved by the scenario with the maximum transaction cost. In summary, selection of the maximum transaction operating point from all the scenarios provides a cushion against uncertainties in renewable generation and load demand. 展开更多
关键词 microgrid economic optimization generation forecast load forecast energy management system fuzzy prediction interval heuristic optimization
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