Collaborative Research: Hysteresis Compensation Using Linear Parameter Varying Control Methods

合作研究：使用线性参数变化控制方法的磁滞补偿

• 批准号: 0602508
• 负责人: Karolos Grigoriadis
• 金额: $ 26.3万
• 依托单位: University of Houston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-09-01 至 2011-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0602508&HistoricalAwards=false
• 关键词: Collaborative; Research; Hysteresis; Compensation; Using

Abstract: This project seeks to develop methodologies for precise compensation of hysteresis nonlinearities in controlled systems. Many electromechanical, structural and material systems at the macro-, meso- micro- and nano-scale exhibit hysteretic behavior due to friction, backlash, phase transition or material properties. Hysteresis in these systems can cause a number of undesirable effects including poor performance, steady-state errors, limit cycle behavior and loss of stability. In this project, the development of a novel Linear Parameter Varying (LPV) control synthesis approach to hysteresis compensation is proposed. In this approach an appropriate state augmentation and transformation is constructed to transform a general nonlinear hysteretic system to an equivalent LPV system with respect to the small-signal local linear gain of the hysteresis nonlinearity. This local linear gain of the hysteresis is proposed as a scheduling parameter to update the LPV feedback control gains. Furthermore, appropriate modeling and on-line identification of hysteresis is proposed that leads to a desired LPV formulation in systems where direct measurement of hysteresis information is not available. To this end, a new method for identification of the Preisach operator weighting function is proposed that provides a computationally efficient on-line estimate of the local linear behavior of the hysteresis nonlinearity. The proposed approach is seen to address many of the limitations of previously developed methods since it can be applied to general nonlinear systems with multiple hysteresis nonlinearities based on knowledge of the small-signal linear gain of the hysteresis at each instant of time. The proposed hysteresis identification and compensation methods will be applied to a large-scale hysteretic variable stiffness and damping structural system at the Rice Universitys Dynamic Systems Laboratory, and to a piezoceramic Thunder actuator micro-positioning system at the University of Houstons Smart Materials & Structures Laboratory. In addition, the project proposes the development of an interactive smart material experiment display that will be used for recruitment, outreach activities and high school demonstrations.Precise hysteresis compensation will greatly benefit the precise control of high performance electromechanical and material systems that exhibit hysteretic behavior. Examples of such systems include smart materials (shape memory alloys, piezoceramic materials, magnetostrictive materials, electro-active polymers, and electro-rheological and magneto-rheological fluids), concrete reinforced structures, gear systems and many vibrating systems. Hysteresis compensation in smart materials is of paramount importance in many high technology areas, including adaptive optics, high precision manufacturing and micro-positioning actuators with applications in micro-surgery, precision instrumentation, micro-pumps and micro-manipulation. The students involved in the project will acquire a broad interdisciplinary training and education in advanced controls, electromechanical systems and smart materials ranging from fundamental engineering sciences to experimentation, testing, and practical implementation.

翻译后摘要：该项目旨在开发控制系统中的磁滞非线性精确补偿的方法。由于摩擦、间隙、相变或材料特性，许多宏观、介观、微观和纳米尺度的机电、结构和材料系统表现出滞后行为。这些系统中的滞后会导致许多不期望的影响，包括性能差、稳态误差、极限环行为和稳定性损失。在这个项目中，提出了一种新的线性变参数（LPV）控制综合方法来补偿迟滞。在这种方法中，一个适当的状态增广和转换构造的一般非线性迟滞系统转换为一个等效的LPV系统的小信号局部线性增益的迟滞非线性。该滞后的局部线性增益被提出作为调度参数来更新LPV反馈控制增益。此外，提出了适当的建模和在线识别的滞后，导致所需的LPV制定在系统中的滞后信息的直接测量是不可用的。为此，提出了一种新的方法，用于识别的Preisach运营商的加权函数，提供了一个计算有效的在线估计的滞后非线性的局部线性行为。所提出的方法被认为是解决许多以前开发的方法的局限性，因为它可以被应用到一般的非线性系统的多个滞后非线性的基础上的知识的小信号的线性增益的滞后在每个时刻。所提出的滞后识别和补偿方法将被应用到一个大规模的滞后变刚度和阻尼的结构系统在莱斯大学的动态系统实验室，并在休斯顿大学的智能材料结构实验室的压电陶瓷雷霆致动器微定位系统。此外，该项目还建议开发一个交互式智能材料实验显示器，用于招聘，宣传活动和高中演示。精确的滞后补偿将大大有利于对具有滞后行为的高性能机电和材料系统的精确控制。这种系统的例子包括智能材料（形状记忆合金、压电陶瓷材料、磁致伸缩材料、电活性聚合物、电流变和磁流变流体）、混凝土加固结构、齿轮系统和许多振动系统。智能材料中的迟滞补偿在许多高技术领域中是至关重要的，包括自适应光学、高精度制造和微定位致动器，其应用于显微外科、精密仪器、微泵和微操作。参与该项目的学生将获得广泛的跨学科培训和教育，包括先进控制，机电系统和智能材料，从基础工程科学到实验，测试和实际实施。