938 research outputs found

    Iterative learning fault-tolerant control for differential time-delay batch processes in finite frequency domains

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    This paper develops a fault-tolerant iterative learning control law for a~class of~linear time-delay differential batch processes with actuator faults using the repetitive process setting. Once the dynamics are expressed in this setting, stability analysis and control law design makes use of the generalized Kalman-Yakubovich-Popov (KYP) lemma in the form of the corresponding linear matrix inequalities (LMIs). In particular, sufficient conditions for the existence of a fault-tolerant control law are developed together with design algorithms for the associated matrices. Under the action of this control law the ILC dynamics have a monotonicity property in terms of an error sequence formed from the difference between the supplied reference trajectory and the outputs produced. An extension to robust control against structured time-varying uncertainties is also developed. Finally, a simulation based case study on the model of a~two-stage chemical reactor with delayed recycle is given to demonstrate the feasibility and effectiveness of the new designs

    Relaxing Fundamental Assumptions in Iterative Learning Control

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    Iterative learning control (ILC) is perhaps best decribed as an open loop feedforward control technique where the feedforward signal is learned through repetition of a single task. As the name suggests, given a dynamic system operating on a finite time horizon with the same desired trajectory, ILC aims to iteratively construct the inverse image (or its approximation) of the desired trajectory to improve transient tracking. In the literature, ILC is often interpreted as feedback control in the iteration domain due to the fact that learning controllers use information from past trials to drive the tracking error towards zero. However, despite the significant body of literature and powerful features, ILC is yet to reach widespread adoption by the control community, due to several assumptions that restrict its generality when compared to feedback control. In this dissertation, we relax some of these assumptions, mainly the fundamental invariance assumption, and move from the idea of learning through repetition to two dimensional systems, specifically repetitive processes, that appear in the modeling of engineering applications such as additive manufacturing, and sketch out future research directions for increased practicality: We develop an L1 adaptive feedback control based ILC architecture for increased robustness, fast convergence, and high performance under time varying uncertainties and disturbances. Simulation studies of the behavior of this combined L1-ILC scheme under iteration varying uncertainties lead us to the robust stability analysis of iteration varying systems, where we show that these systems are guaranteed to be stable when the ILC update laws are designed to be robust, which can be done using existing methods from the literature. As a next step to the signal space approach adopted in the analysis of iteration varying systems, we shift the focus of our work to repetitive processes, and show that the exponential stability of a nonlinear repetitive system is equivalent to that of its linearization, and consequently uniform stability of the corresponding state space matrix.PhDElectrical Engineering: SystemsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133232/1/altin_1.pd

    Genetic algorithm optimization and control system design of flexible structures

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    This paper presents an investigation into the deployment of genetic algorithm (GA)-based controller design and optimization for vibration suppression in flexible structures. The potential of GA is explored in three case studies. In the first case study, the potential of GA is demonstrated in the development and optimization of a hybrid learning control scheme for vibration control of flexible manipulators. In the second case study, an active control mechanism for vibration suppression of flexible beam structures using GA optimization technique is proposed. The third case study presents the development of an effective adaptive command shaping control scheme for vibration control of a twin rotor system, where GA is employed to optimize the amplitudes and time locations of the impulses in the proposed control algorithm. The effectiveness of the proposed control schemes is verified in both an experimental and a simulation environment, and their performances are assessed in both the time and frequency domains

    Spin Transport and Polarimetry in the Beam Delivery System of the International Linear Collider

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    Polarised electron and positron beams are key ingredients to the physics programme of future linear colliders. Due to the chiral nature of weak interactions in the Standard Model - and possibly beyond - the knowledge of the luminosity-weighted average beam polarisation at the e+ee^+e^- interaction point is of similar importance as the knowledge of the luminosity and has to be controlled to permille-level precision in order to fully exploit the physics potential. The current concept to reach this challenging goal combines measurements from Laser-Compton polarimeters before and after the interaction point with measurements at the interaction point. A key element for this enterprise is the understanding of spin-transport effects between the polarimeters and the interaction point as well as collision effects. We show that without collisions, the polarimeters can be cross-calibrated to 0.1 %, and we discuss in detail the impact of collision effects and beam parameters on the polarisation value relevant for the interpretation of the e+ee^+e^- collision data.Comment: 34 pages, 11 figure

    Experimental study of a two-DOF five bar closed-loop mechanism

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    This research is to carry out an experimental study to examine and verify the effectiveness of the control algorithms and strategies developed at the Advanced Engineering Design Laboratory (AEDL). For this purpose, two objectives are set to be achieved in this research. The first objective is to develop a generic experiment environment (test bed) such that different control approaches and algorithms can be implemented on it. The second objective is to conduct an experimental study on the examined control algorithms, as applied to the above test bed. To achieve the first objective, two main test beds, namely, the real-time controllable (RTC) mechanism and the hybrid machine, have been developed based on a two degree of freedom (DOF) closed-loop five-bar linkage. The 2-DOF closed-loop mechanism is employed in this study as it is the simplest of multi-DOF closed-loop mechanisms, and control approaches and conclusions based on a 2-DOF mechanism are generic and can be applied to a closed-loop mechanism with a higher number of degrees of freedom. The RTC mechanism test bed is driven by two servomotors and the hybrid machine is driven by one servomotor and a traditional CV motor. To achieve the second objective, an experimental study on different control algorithms has been conducted. The Proportional Derivative (PD) based control laws, i.e., traditional iii PD control, Nonlinear-PD (NPD) control, Evolutionary PD (EPD) control, non-linear PD learning control (NPD-LC) and Adaptive Evolutionary Switching-PD (AES-PD) are applied to the RTC mechanism; and as applied to the Hybrid Actuation System (HAS), the traditional PD control and the SMC control techniques are examined and compared. In the case of the RTC mechanism, the experiments on the five PD-based control algorithms, i.e., PD control, NPD control, EPD, NPD-LC, and AES-PD, show that the NPD controller has better performance than the PD controller in terms of the reduction in position tracking errors. It is also illustrated by the experiments that iteration learning control (ILC) techniques can be used to improve the trajectory tracking performance. However, AES-PD showed to have a faster convergence rate than the other ILC control laws. Experimental results also show that feedback ILC is more effective than the feedforward ILC and has a faster convergence rate. In addition, the results of the comparative study of the traditional PD and the Computed Torque Control (CTC) technique at both low and high speeds show that at lower speeds, both of these controllers provide similar results. However, with an increase in speed, the position tracking errors using the CTC control approach become larger than that of the traditional PD control. In the case of the hybrid machine, PD control and SMC control are applied to the mechanism. The results show that for the control of the hybrid machine and the range of speed used in this experimental study, PD control can result in satisfactory performance. However, SMC proved to be more effective than PD control

    High-performance torque control of switched reluctance motor

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    Ph.DDOCTOR OF PHILOSOPH

    A Study of the Beam Physics in the CLIC Drive Beam Decelerator

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    CLIC is a study for a Multi-TeV e+e- linear collider, in which the rf power for the main linacs is extracted from 100 ampere electron drive beams, by the use of specially designed power extraction structures. Up to 90% of the beam energy is extracted from the drive beams along one kilometer long decelerator sectors, rendering the beam transport challenging. We have identified two major challenges for robust beam transport: the significant transverse wakes in the power extraction structures, and the large energy spread induced by the power extraction process. By beam dynamics studies we have qualified power extraction structure designs, leading to the present CLIC baseline structure in which the transverse wakes are sufficiently mitigated. We have further shown that the beam energy spread induced by the deceleration implies that standard 1-to-1 correction might not ensure satisfactory drive beam transport. As alternative, we propose a decelerator orbit correction scheme based on dispersion-free steering and exploiting the structure beam loading. By simulation the proposed scheme shows excellent performance, assuming sufficient beam position monitor resolution. We have performed successful demonstrations of similar orbit correction schemes in the linac of the CLIC Test Facility 3. The results of the beam dynamics studies have lead to specifications for decelerator instrumentation and magnets, described in detail in this w ork. The first prototype of the baseline power extraction structure has been tested with beam in the Two-beam Test Stand in the CLIC Experiment Area, where a field recirculator has been installed to boost power production. We have derived formulae for rf power production and voltage, including a simple model describing power extraction with recirculation. The model has been applied to the first Two-beam Test Stand experimental result. We compare the measured rf power, phase and energy loss with reconstructed signals based on beam intensity measurements, and a good agreement between the measurements and the reconstruction is shown

    Iterative learning control in the commissioning of industrial presses

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    182 p.This thesis presents solutions to the control problems that exist nowadays in industrial presses, followed by a discussion of the most appropriate control schemes that may be used for their solution. Iterative Learning Control is subsequently analyzed, as the most promising control scheme for machine presses, due to its capability to improve the performance of a system that operates repeatedly.A novel Iterative Learning Control design is presented, which makes use of the dynamic characteristics of the system to improve the current controller performance and stability. This, results in an adaptation of the presented Iterative Learning Control design to two use cases: the single-input-single-output force control of mechanical presses and the multiple-input-multiple-output position control of hydraulic presses. While existing Iterative Learning Control approaches are also described and applied to the previously mentioned use cases, the presented novel approach has been shown to outperform the existing algorithms in terms of control performance.The proposed Iterative Learning control algorithms are validated in an experimental hydraulic test rig, in which the performance, robustness and stability of the algorithm have been demonstrated

    Accuracy Enhancement for High Precision Gantry Stage

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    Ph.DDOCTOR OF PHILOSOPH
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