Model-Based Robust Control Designs for High Performance Magnetostrictive Transducers

hysteresis;magnetostictives;nonlinear control;smart materials;nonlinear parameter estimation

Nealis, James Matthew ; Fen Wu, Committee Member,Kazufumi Ito, Committee Member,Hien Tran, Committee Member,Ralph C. Smith, Committee Chair,Nealis, James Matthew ; Fen Wu ; Committee Member ; Kazufumi Ito ; Committee Member ; Hien Tran ; Committee Member ; Ralph C. Smith ; Committee Chair

University:North Carolina State University

关键词: hysteresis;    magnetostictives;    nonlinear control;    smart materials;    nonlinear parameter estimation;   

Others  :  https://repository.lib.ncsu.edu/bitstream/handle/1840.16/3466/etd.pdf?sequence=1&isAllowed=y

美国|英语

来源: null

【 摘 要 】

The increasing employment of smart structures in industrial processes necessitates the study of materials exhibiting constitutive nonlinearities and hysteresis.The high performance and high speed demands of such processes can often be met by transducers utilizing piezoceramic, shape memory alloy, or magnetostrictive elements.Here, the focus is place on magnetostrictive materials. These material provide several benefits such as the ability to generate large forces and strains and provide precision placement.However, to achieve the full potential of magnetostrictive materials, models and control laws which accommodate the inherent nonlinearities and hysteresis must be employed.An emphasis has been placed on the design of models for magnetostrictive transducers and control strategies that are implementable in real time and incorporate realistic operating conditions.To this end, models of the nonlinearities and hysteresis exhibited by magnetostrictive materials are developed considering not only accuracy, but the computational efficiency and the existence of an inverse or partial inverse as well. To attenuate the nonlinear and hysteretic behaviors, we employ the inverses of the material models as filters of the input to the transducer. The models describing the nonlinearities and hysteresis for the smart materials, contain several material dependent parameters which must be identified in order to effectively utilize resulting inverse compensators. A nonlinear adaptive parameter estimation algorithm is developed to identify nonlinearly occurring parameters which may not be identified by physical measurements or may be slowly varying.Once an inverse filter has been developed and the material parameters identified, feedback control laws are designed to meet the performance specifications. A successful controller must provide accurate tracking of a reference signal while accommodating the hysteretic behavior and other external disturbances such as sensor noise. Several initial feedback control methods are considered to motivate the investigation of robust control designs. Robust techniques including H₂ and H[subscript ∞] optimal control as well as multiple objective control designs are employed to control a magnetostrictive transducer and the performance is illustrated through simulations.