适用于力反馈的圆筒式磁流变液执行器的设计

力/触觉反馈是虚拟现实交互技术中一种重要的交互形式。磁流变液执行器是最具发展潜力的力/触觉反馈装置。提出了一种适用于手指力反馈的便携式圆筒磁流变液执行器的设计方法,导出了基于B ingham塑性模型的阻力矩公式,分析了磁流变液特性和执行器结构参数对阻力矩的影响,并通过有限元分析进行优化设计,执行器的直径为31 mm,高度为38 mm,重200 g。实验测定了阻力矩和输入电流之间的关系,并采用二次多项式拟合。输入电流为0.6 A时,执行器产生的阻力矩为255 N.mm,结果表明,该执行器产生的阻力矩足以阻止手指抓取虚拟物体。     

Force control of hybrid actuator using learning vector quantization neural network

Hydraulic actuators are important in modern industry due to high power, fast response, and high stiffness. In recent years, hybrid actuation system, which combines electric and hydraulic technology in a compact unit, can be adapted to a wide variety of force, speed and torque requirements. Moreover, the hybrid actuation system has dealt with the energy consumption and noise problem existed in the conventional hydraulic system. Therefore, hybrid actuator has a wide range of application fields such as plastic injection-molding and metal forming technology, where force or pressure control is the most important technology. In this paper, the solution for force control of hybrid system is presented. However, some limitations still exist such as deterioration of the performance of transient response due to the variable environment stiffness. Therefore, intelligent switching control using Learning Vector Quantization Neural Network (LVQNN) is newly proposed in this paper in order to overcome these limitations. Experiments are carried out to evaluate the effectiveness of the proposed algorithm with large variation of stiffness of external environment. In addition, it is understood that the new system has energy saving effect even though it has almost the same response as that of valve controlled system.     

Robust control design for a wheel loader using and feedback linearization based methods

The heavy equipment industry is building more and more equipment with electro-hydraulic control systems. The existing industry practices for the design of control systems in construction machines primarily rely on classical designs coupled with ad-hoc synthesis procedures. Such practices produce desirable results, but lack a systematic procedure to account for invariably present plant uncertainties in the design process as well as coupled dynamics of the multi-input multi-output (MIMO) configuration. In this paper, two H_∞ based robust control designs are presented for an automatic bucket leveling mechanism of a wheel loader. In one case, the controller is designed for the base plant model. In another case, the controller is designed for the plant with a feedback linearization control law applied yielding improved stability robustness. A MIMO nonlinear model for an electro-hydraulically actuated wheel loader linkage is considered. The robustness of the controller designs are validated by using analysis and by simulation using a complete nonlinear model of the wheel loader linkage and hydraulic system.     

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H_∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement.     

Robust control of feedback linearizable large-scale systems

The design of decentralized controllers for a class of uncertain interconnected nonlinear systems is considered. The uncertainty considered here is time-varying and appears at each subsystem and interconnections. Two control techniques are explored. The first one, namely, the feedback linearization control, involves a known and autonomous nonlinear system. The second one, namely, the robust control, is especially suitable if any uncertainty and/or time-varying factors are involved in the nonlinear dynamics. These two controllers are combined to stabilize a class of large-scale nonlinear uncertain systems. Two decentralized robust controllers, nonadaptive and adaptive, are proposed and those results are proved.     

Robust control of a 3-DOF hybrid robot manipulator

This paper introduces a 3-DOF hybrid robotic manipulator which is constructed by combining a parallel mechanism and a pantograph to increase the high stiffness, as well the as workspace. We analyze its kinematics and dynamics by applying Lagrange’s method. Subsequently, we propose a robust tracking controller based on the Lyapunov approach for the manipulator in the presence of uncertainty. The scheme consists of two parts. The first part is the model-based computed torque controller, which is used to stabilize the nominal robot system. The second part is a robust compensating controller, which is designed to handle the uncertainty in the system. We propose a controller designed in Cartesian coordinates. The proposed controller guarantees practical stability.     

一种稳健的窄带反馈型主动噪声控制系统

传统窄带反馈型主动噪声控制系统采用并型自适应滤波器结构,用于合成参考信号时,仍存在参考信号合成质量较差、 滤波器权值的初值设置难度高、应对非平稳窄带噪声的能力不足等问题。 为解决以上问题,通过引入高效的串并型自适应滤波 器结构来合成参考信号,提出新型的窄带反馈型主动噪声控制系统,改善参考信号合成质量,进而提升系统的整体降噪性能。 新型系统不仅有效解决了传统系统存在的参考信号合成质量较差的问题,还降低了滤波器权值的初值设置复杂度,同时还提升 了系统应对非平稳窄带噪声的能力。 实验结果表明,新型系统较传统系统的前后两部分的降噪量分别提升了 7. 89 和 9. 18 dB。 仿真和实验结果共同验证了提出的系统较传统系统具有更强的稳健性和降噪性能。     

Robust feedback linearization for nonlinear processes control

In this research, a robust feedback linearization technique is studied for nonlinear processes control. The main contributions are described as follows: 1) Theory says that if a linearized controlled process is stable, then nonlinear process states are asymptotically stable, it is not satisfied in applications because some states converge to small values; therefore, a theorem based on Lyapunov theory is proposed to prove that if a linearized controlled process is stable, then nonlinear process states are uniformly stable. 2) Theory says that all the main and crossed states feedbacks should be considered for the nonlinear processes regulation, it makes more difficult to find the controller gains; consequently, only the main states feedbacks are utilized to obtain a satisfactory result in applications. This introduced strategy is applied in a fuel cell and a manipulator.     

应用控制理论实现反馈控制

明确阐述了控制理论和控制工程的关系,指出应用控制理论设计控制系统是整个控制工程的锦上添花部分.文章分析了控制理论应用方面的现况和问题,并且谈了笔者的看法和建议.希望工程人员在控制工程中应用控制理论,实现真正意义上的自动控制.     

一种改进的主/被动结合的力反馈技术

根据虚拟现实、遥操作机器人系统和远程外科手术等领域的需要,针对主、被动力反馈存在的问题,在现有的主/被动混合型力反馈实现方法的基础上,提出了一种改进的串联弹性元件的主/被动相结合的力反馈实现方法,自行研制了制动力矩可控的磁流变液制动器用于实现被动力反馈,给出了该制动器的设计原理,建立了动力学模型。利用研制出的磁流变液制动器,组建了简单的能够实现主/被动力反馈功能的实验系统,利用不同弹性系数的弹簧模拟不同的实验环境及极端情况,对实验系统进行了力跟踪实验,实验结果验证了所提方法的有效性。     

Robust decentralized hybrid adaptive output feedback fuzzy control for a class of large-scale MIMO nonlinear systems and its application to AHS

This paper presents a novel observer-based decentralized hybrid adaptive fuzzy control scheme for a class of large-scale continuous-time multiple-input multiple-output (MIMO) uncertain nonlinear systems whose state variables are unmeasurable. The scheme integrates fuzzy logic systems, state observers, and strictly positive real conditions to deal with three issues in the control of a large-scale MIMO uncertain nonlinear system: algorithm design, controller singularity, and transient response. Then, the design of the hybrid adaptive fuzzy controller is extended to address a general large-scale uncertain nonlinear system. It is shown that the resultant closed-loop large-scale system keeps asymptotically stable and the tracking error converges to zero. The better characteristics of our scheme are demonstrated by simulations.     

A pressure output feedback control of turbo compressor surge with a thrust magnetic bearing actuator

This paper presents a pressure output feedback control of turbo compressor surge using tip clearance actuation with a thrust magnetic bearing actuator. First, static and dynamic compressor models were obtained for a commercial turbocharger, and the surge point was found through local stability analysis. Then, the effect of tip clearance on the compressor pressure rise was derived, and Lyapunov analysis was used to establish a limit of stability with tip clearance modulation. After that, a linear quadratic (LQ) state feedback control was designed considering the limit established by the Lyapunov analysis. In addition, an extended Kalman filter (EKF) was designed to estimate the mass flow rate from the measured compressor pressure. Finally, the pressure output feedback controller was built by combining the LQ state feedback control and EKF. Control simulation proved the effectiveness of the output feedback controller. This paper was recommended for publication in revised form by Associate Editor Dong Hwan Kim Dr. Ahn earned Ph.D. from Seoul National University in 2001. He was a research associate of University of Virginia. He is currently an assistant professor of department of mechanical engineering at Soongsil University and serving as an editor of international journal of rotating machinery. His research interests are rotordynamics, control and mechatronics. Mr. Park is a junior research engineer in Doosan infracore. He received his master from Seoul National University. His research area is on dynamics and control of rotating machinery. Dr. Sanadgol is an assistant Professor of Physics and Engineering at Sweet Briar College. She earned her PhD in Mechanical and Aerospace Engineering with a focus in controls from the University of Virginia in 2006. Her research interests are in controlling flow instabilities in compressors and application of nonlinear control theories to mechatronics systems. Dr. Park received his PhD degree from the Seoul National University, Korea in 2007. He is currently director of research institute at KMB&SENSOR company. His research interests include the precision machine design, rotor dynamics, and magnetic actuators. Dr. Han received the Dipl.-Ing. and Dr.-Ing. in mechanical engineering from University of Karsruhe, Germany in 1975 and 1979, respectively. In 1982, he joined the school of mechanical and aerospace engineering, Seoul National University as an assistant professor. He is currently an honorary professor of mechanical engineering. His research interests are in machine element design, magnetic bearing, lubrication engineering and Bio-MEMS devices. Dr. Maslen is a Professor of Mechanical and Aerospace Engineering at the University of Virginia. He earned his Bachelor of Science in 1980 from Cornell University and his doctorate from the University of Virginia in 1991. His research focuses on application of automatic controls to electromechanical systems with a concentration in magnetic bearings.     

基于人工免疫思想的电动执行机构智能控制研究

电动执行器是自动化系统中大量使用的一种执行部件，但电动执行器难以实现高性能控制，其原因在于执行机构系统中存在的不灵敏区、间隙、摩擦等非线性因素，且使用场合不同造成的负载特性不同，整机性能随着执行机构的运行方向、机械磨损和负载的变化而改变。该文借鉴生物免疫反馈响应过程的调节作用和模糊逻辑推理的自适应能力，提出了一种电动执行器模糊自调整免疫PD控制策略。该控制方法具有模糊控制、免疫控制方法的优点，具有较强抗干扰能力和鲁棒性。仿真研究证明了该控制方法的可行性和有效性。     

A hybrid feedback linearizing-Kalman filtering control algorithm for a distillation column

This paper studies the design of a discrete-time multivariable feedback linearizing control (FLC) structure. The control scheme included (i) a transformer [also called the input/output (I/O) linearizing state feedback law] that transformed the nonlinear u-y to a linearized v-y system, (ii) a closed-loop observer [extended Kalman filter (EKF)], which estimated the unmeasured states, and (iii) a conventional proportional integral (PI) controller that was employed around the v-y system as an external controller. To avoid the estimator design complexity, the design of EKF for a binary distillation column has been performed based on a reduced-order compartmental distillation model. Consequently, there is a significant process/predictor mismatch, and despite this discrepancy, the EKF estimated the required states of the simulated distillation column precisely. The FLC in conjunction with EKF (FLC-EKF) and that coupled with a measured composition-based reduced-order open-loop observer (FLC-MCROOLO) have been synthesized. The FLC structures showed better performance than the traditional proportional integral derivative controller. In practice, the presence of uncertainties and unknown disturbances are common, and in such situations, the proposed FLC-EKF control scheme ensured the superiority over the FLC-MCROOLO law.     

Robust control for rotational inverted pendulums using output feedback sliding mode controller and disturbance observer

This paper presents a system modeling, controller design and implementation for a rotational inverted pendulum system (RIPS), which is an under-actuated system and has the problem of unattainable velocity state. Two control strategies are applied to theRIPS. One is a sliding mode control method using the parameterization of both the hyperplane and the compensator for output feedback. The other is the disturbance observer which estimates disturbance and some modeling errors of RIPS with less computational effort. Some simulations and various kinds of experiments are performed in order to verify that the proposed controller has the ability to control RIPS whose velocity is assumed to be unavailable. The results of the simulations and experiments show that the proposed control system has superior performance for disturbance rejection and regulation at certain initial conditions as well as the robustness to model uncertainties.     

Signal-to-noise ratio constrained feedback control: Robust stability analysis

The explicit consideration of a communication channel model in a feedback control loop is known to be constrained by a fundamental limitation for stabilizability on the channel signal-to-noise ratio (SNR) when the linear time invariant (LTI) plant model is unstable. The LTI modelling approach for real, usually nonlinear, processes compromises accuracy versus complexity of the resulting model. This in turn introduces a gap between the proposed model and the real process, which is known as the model uncertainty. In this paper we then study SNR limitations by considering the continuous-time scenario and the case of an additive coloured Gaussian noise (ACGN) channel with bandwidth limitation, for which we then quantify the infimal SNR subject to the simultaneous presence of plant, channel and noise model uncertainties. We observe, for the special case of memoryless additive white Gaussian noise (AWGN) channels, that the obtained SNR limitation subject to plant model uncertainty can be redefined as a channel capacity limitation for stabilization.     

Robust control approach to force estimation in a constant position optical tweezers

Feedback enhanced optical tweezers with position regulation capability enable detection and estimation of forces in the pico-Newton regime. In this article we delineate the fundamental limitations and challenges of existing approaches for regulating position and force estimation in an optical tweezer. A modern control systems approach is shown to improve the bandwidth of force estimation by three to four times which is corroborated experimentally.