Dynamic maskless holographic lithography (DMHL) is a new micro-manufacturing technique that has no moving
parts. The laser light used for patterning is directed in all three dimensions with a hologram displayed on a
liquid-crystal spatial light modulator (SLM). Optical aberrations, like spherical aberration due to refractive index
mismatch between the photoresist and the immersion oil of the high-NA objective or astigmatism due to the
deformations in the surface of the SLM, can degrade the performance of the system. Degraded performance
includes a decrease in potential patterning volume and pattern fidelity and an increase in patterning time.
This paper presents a way to correct for these aberrations using Zernike polynomials. The optimal Zernike
coefficients are found by maximizing a sharpness metric. The effect of aberration correction on the DMHL process
is quantified by measuring the patterning volume. DMHL manufactured features made with this aberration
correction method show a marked improvement over features made without correction. It is even possible to
correct for misaligned optics with this method.
Dynamic maskless holographic lithography (DMHL) is a new micro-manufacturing technique that uses holograms
to create patterns on a substrate instead of a mask. In DMHL, gratings and Fresnel lenses are displayed on
nematic liquid crystal spatial light modulators (SLMs) to steer light to desired locations to expose sensitive
photopolymers. Micro-manufacturing can be done in two modes, serial or parallel. Serial refers to a beam being
scanned through a set of points and parallel refers to an entire intensity pattern being created at once. The
field over which patterning can be performed is affected by the diffraction efficiency of the displayed hologram,
the maximum possible spatial frequency of the SLM, and aliasing (light being steered to unintended spots due
to mismatches between designed and displayed phase patterns). This paper presents a technique to compensate
for these inherent inefficiencies by properly adjusting the amount of time spent by the beam at each point
in the desired feature, the dwell-time, during the lithographic process. The relationship between the spatial
frequency of the appropriate grating or Fresnel lens and the dwell time is discussed. Experiments are presented
with and without this technique applied, and results show that feature uniformity is improved with dwell-time
compensation.
Holographic or diffractive optical components, such as a spatial
light modulator (SLM), can be used in optical tweezers for the
creation of multiple and modified optical traps. In addition to
this, SLMs can also be used to correct for aberrations within the
optical train resulting in an improved trapping performance.
Typically an electrically addressed SLM may deviate from flatness
by up to 4λ, dominated by astigmatism due to the overall
curvature of the SLM surface. This astigmatism may be corrected by
adding the appropriate hologram to the SLM display resulting in a
dramatic improvement in the fidelity of the focussed spot. The
impact that this correction has on the performance of the optical
trap is most noticeable for small particles. For the SLM used in
this study, the improvement in trap performance for a 0.8 μm
diameter particles can be in excess of 25%. However, for 5 μm
diameter particles our results show an improvement of less than
0.5%. This dependence upon particle size is most probably
associated with the relative size of the PSF and the trapped
particle. Once the PSF is significantly smaller than the particle
diameter, further reduction brings little improvement in trap
performance.
The measurement of binding forces between specific antigen-antibody pairs presents a powerful tool for sensitive detection with applications in medical diagnostics, bioagent sensing, and environmental monitoring. The ability to detect single molecular binding events with an AFM, using the technique of dynamic force spectroscopy, is a known capability; however, reliance on traditional AFM architectures limits the use of this method to laboratory environments. The approach presented here uses active piezoelectric microcantilevers, providing electronic output for detection of molecular binding. Functionalization of this device with specific antibodies provides a platform for a stand-alone detection device. As the microcantilever can be operated as both a sensor and an actuator, the detection scheme includes actuating the cantilever to present an antibody bound to the cantilever tip to a second antibody bound to a fixed substrate. If a target antigen is present in solution, the cantilever detects the mechanical strain and vibrational response created by the binding force and subsequent rupture of the antigen-antibody pair. This detection strategy distinguishes this work from resonance-based cantilever devices that respond to changes in cantilever mass based on adsorption of numerous antigen molecules. In this research, piezoelectric microcantilevers were fabricated, and initial results were obtained demonstrating transient response caused by rupture of nonspecific adhesion forces in air and water environments. Analytical results are also presented relating geometrical parameters with sensor performance.
Using feedback control, a versatile optical trap can be constructed that can be used to control either the position of trapped objects or apply specified forces. Yet, while the design, development, and use of optical traps has been extensive and feedback control has played a critical role in pushing the state of the art, it is surprising to note that few comprehensive examinations of feedback control of optical traps have been undertaken. Furthermore, as the requirements are pushed to ever smaller distances and forces, the performance of optical traps reach limits. It is well understood that feedback control can result in both positive and negative effects in controlled
systems. This paper discusses the performance and analytical limits that must be considered in the development and design of control systems for optical traps.
The quantitative study of displacements and forces of motor proteins and processes that occur at the microscopic level and below require a high level of sensitivity. For optical traps, two techniques for position sensing have been accepted and used quite extensively: quadrant photodiodes and an interferometric position sensing technique based on DIC imaging. While quadrant photodiodes have been studied in depth and mathematically characterized, a mathematical characterization of the interferometric position sensor has not been presented to the authors' knowledge. The interferometric position sensing method works off of the DIC imaging capabilities of a microscope. Circularly polarized light is sent into the microscope and the Wollaston prism used for DIC imaging splits the beam into its orthogonal components, displacing them by a set distance determined by the user. The distance between the axes of the beams is set so the beams overlap at the specimen plane and effectively share the trapped microsphere. A second prism then recombines the light beams and the exiting laser light's polarization is measured and related to position. In this paper we outline the mathematical characterization of a microsphere suspended in an optical trap using a DIC position sensing method. The sensitivity of this mathematical model is then compared to the QPD model. The mathematical model of a microsphere in an optical trap can serve as a calibration curve for an experimental setup.
KEYWORDS: Digital filtering, System identification, Acoustics, Filtering (signal processing), Control systems, Adaptive control, Algorithm development, Linear filtering, Systems modeling, Data modeling
The generalized predictive control (GPC) concept is extended to an adaptive control algorithm by combining with a least-squares lattice filter. A least-squares lattice (LSL) filter, another class of exact least-squares filters, has a modular structure that is advantageous in the application of on-line system identification. The modular structure passes system information from lower order to higher order in a wave motion. The adaptive GPC algorithm combined with a LSL filter is implemented for a real-time computer algorithm and its performance is experimentally demonstrated to a structural system and an acoustic enclosure. In addition, the adaptive GPC algorithm with a LSL filter is compared with the adaptive GPC algorithm combined with a classical recursive least-squares (RLS) filter in terms of complexity, computational cost and other on-line application concerns. The average task execution time (TET) --- the measured processing time to run the algorithm during each sample interval --- is reduced by over 35 \% by using the adaptive GPC algorithm with a LSL filter.
KEYWORDS: Control systems, System identification, Sensors, Acoustics, Data modeling, Systems modeling, Feedback control, Error analysis, Adaptive control, Mirrors
The recursive generalized predictive control (RGPC), which combines the process of system identification using recursive least-squares (RLS) algorithm and the process of generalized predictive feedback control design, has been presented and successfully implemented on testbeds. In this research, the RGPC algorithm is extended when the disturbance measurement signal is available for feedforward control. First, the feedback and feedforward RGPC design algorithm is presented when the disturbance is stochastic or random, and is applied to an optical jitter suppression testbed. Second, the feedback and feedforward algorithm is further extended when the disturbance is deterministic or periodic. The deterministic disturbance measurement is used to estimate the future disturbance values that are then used in the control design to enhance the performance. The RGPC with future disturbance estimation algorithm is applied to a structural system and an acoustic system.
Aeroelastic control of flutter by means of trailing edge surfaces can be a very effective method, providing that
the actuation system is capable of generating suffcient force and displacement over the bandwidth of interest.
This effort describes the mechanical design aspects of a flap actuation system using V-stack piezoelectric
actuator and Q-parameterization technique for identifying the plant at supercritical speeds. A flap actuation
mechanism that takes advantage of the shape of the actuator (V) was designed. In order to validate the
actuation concept the actuator was integrated into a NACA 0015 typical section that was tested in the wind
tunnel at Duke University. An initial nominal controller was designed to stabilize the typical section for a
limited range of speeds above the open-loop flutter boundary. The technique of Q-parameterization was then
used to parameterize the unstable system as a function of stable systems, each derived from the nominal
controller. Operating in closed loop, flutter was suppressed at the speed it occurred in open loop, and the
flutter boundary was extended by more than 50%.
Vibration-induced jitter degrades the pointing and imaging performance of precision optical systems. Practical active jitter reduction is achieved by maintaining beam alignment with mirror-positioning control systems. In the presence of time-varying or uncertain disturbances, jitter control systems using fixed-gain feedback control loops cannot operate without significant limitations on their performance. A feedback control technique called Q-parameterization can adapt to time-varying disturbances by adjusting its parameters in real time to maintain optimal performance. Adaptive feedback jitter control using Q-parameterization is experimentally verified on an optical testbed, increasing jitter reduction compared to an H2-optimal fixed-gain controller.
KEYWORDS: Picosecond phenomena, Information technology, Data modeling, Data conversion, System identification, Bismuth, Digital filtering, Control systems, Weapons of mass destruction, Neodymium
The concept of generalized predictive control (GPC) design is extended by combining it with the recursive least squares (RLS) system identification algorithm. In this paper, GPC is combined with the classical RLS system identification algorithm, and with the fast transversal filter (FTF), a modified version of the classical RLS algorithm. The classical RLS algorithm is a straightforward approach for identifying a model from input and output data, and one of the advantages of the classical RLS algorithm is that a model is obtained without time-consuming processes like matrix inversion. The FTF is also an RLS algorithm, but it exploits the shifting property of serialized data and thereby results in a substantial reduction in computational complexity. The advantages of both combined algorithms are no prior system model is required, since the process of system identification is performed recursively from real-time system input and output data, and the controller is updated adaptively in the presence of a changing operating environment.
Optical jitter, the centroid-shifting of a light image, concerns engineers and scientists working with lasers and electro-optical systems. Even micron-level relative motion between individual optical components such as mirrors and lenses causes optical jitter, resulting in pointing inaccuracy, blurred high-resolution images, and poor nanotechnology quality. Typical jitter control technology uses fast-steering mirrors to correct for structural and acoustic disturbances in the beam train. Unknown or time-varying disturbance characteristics necessitate a controller that can adapt its parameters in realtime. The application of one such adaptive feedback controller algorithm has been proposed by the authors. The algorithm uses a technique known as Q-parameterization to structure the controller as a function of plant coprime factors and a free parameter, Q. An inherent property of this structure is the formation of a disturbance estimate based on subtraction of the controller influence from the feedback signal. The free parameter, Q, filters this estimate to form a portion of the control signal. If the controller influence on the feedback signal is estimated from accurately modeled plant dynamics, the disturbance estimate contains no feedback information allowing Q to be designed in an open-loop fashion. A gradient descent Least Mean Squares (LMS) algorithm updates the coefficients of the filter Q in realtime to minimize the frequency-weighted RMS jitter. Experiments on an optical jitter control testbed with Q set to a 200-tap digital finite impulse response (FIR) filter resulted in jitter reductions of 35% - 50%, without requiring prior knowledge of the disturbance spectrum.
An algorithm is presented which uses adaptive Q-parameterized compensators for control of stable or unstable systems. Internal stability is maintained by forming the compensator out of plant-stabilizing coprime factors, and an on-line gradient descent method adapts the free parameter to minimize the mean squared error between the desired and actual output. The adaptation algorithm is derived for a compensator in the form of a finite impulse response (FIR) filter and a lattice infinite impulse response (IIR) filter. Simulations predict good performance for both tonal and broadband disturbances, and a duct noise control experiment results in a 37 dB tonal reduction.
KEYWORDS: Sensors, Analog electronics, Modal analysis, Systems modeling, Digital signal processing, Filtering (signal processing), Capacitance, Control systems, Mechanical engineering, Materials science
It has been shown that passive electronic damping can be successfully achieved using tuned RL circuits to shunt piezoelectric materials on structures. These designs provide electronic equivalents of tuned-vibration dampers where the coupling coefficient plays the role of the mass ratio in similar mechanical devices and is the primary factor in determining performance. However, in many applications the coupling coefficient is too small to produce desired or acceptable changes in performance. In addition, changes in system parameters, such as the piezoelectric's capacitance, detune the system also limiting performance. A sensoriactuator circuit offers the ability to eliminate the effects of the piezoelectric's capacitance and improve the coupling coefficient. Thus, electronic dampers built with a sensoriactuator circuit could see improved performance over their strictly passive counterparts. A cantilevered beam test article is modeled with a sensoriactuator attached. The sensoriactuator and appropriate control filter are used in place of the passive shunt circuitry. An optimal circuit design criteria somewhat analogous to that of the resonant shunt damper is developed. The sensoriactuator circuit is built using this design criteria, and the effects of the sensoriactuator electronic damping scheme are included in the model.
This paper discusses the use of genetic algorithms (GA) as a global search technique to solve a loading bridge regulator control problem. The theory, design and implementation of the algorithm is discussed in detail. An improved selection scheme and two advanced genetic operators are introduced. Three different GA-based feedback controllers are designed: Simple GA (SGA), Improved GA (IGA), and Advanced GA (AGA). Their results performance results are compared. Among the three GA approaches considered, AGA is the most robust one for the design of feedback controllers.
Various control methods of rotor blade vibration reduction based on individual blade control are presented and compared. The benchmark model used is based on a four-bladed helicopter at hover conditions. In this paper, three control strategies are investigated: LQR method of feedback control, feedforward control, and hybrid control (a combination of feedback and feedforward control). It was found that the LQR method provided substantial improvements in the system and very low gains. Feedforward control was found to be somewhat less effective and the hybrid control method, which combines both feedforward and LQR feedback methods, was proven to be the most effective method.
The development of simultaneous sensing and actuation for a single piezoelectric element, called a sensoriactuator in this paper, provides the opportunity for truly collocated control in adaptive structures. Issues related to collocation are discussed in terms of their effects on active structural acoustic control (ASAC). A variation on earlier feedback ASAC methods, direct radiation feedback (DRFB), is suggested for the sensoriactuator adaptive structure. The DRFB method relies on a discrete-point formulation of the associated radiated energy norm. The influence of the acoustic dynamics on proven sufficient conditions for globally stable collocated velocity feedback is discussed for the first time. Selection of an appropriate Lyapunov function for the stability analysis of collocated DRFB is discussed and compared to previous results for direct velocity feedback in active vibration control.
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