Abstract:
A system for suppressing undesirable oscillations in a micro-electro-mechanical system (MEMS) scanner is provided. The system includes a tunable notch filter and a MEMS scanner. The tunable notch filter is operable to receive an original drive signal and to generate a compensated drive signal based on the original drive signal. The MEMS scanner, which is coupled to the tunable notch filter, is operable to receive the compensated drive signal and to be driven by the compensated drive signal without oscillating at a first mode resonance frequency.

Description:
TECHNICAL FIELD 
     This disclosure is generally related to MEMS technology and, more specifically, to a system for suppressing undesirable oscillations in a MEMS scanning mirror for miniaturized projection systems. 
     BACKGROUND 
     Video projectors have been used extensively in business environments and have recently come into wide use in large-screen projection systems in home theaters. The miniaturization of projection systems has led to the development of “pico-projectors” that may be embedded in other systems, such as mobile phones and heads-up displays for vehicle dashboards, or may be implemented as stand-alone devices, such as pocket or ultra-mobile projectors that may be powered from a battery or an external power source. These miniature systems use highly efficient LED or LASER light sources. 
     One example of a pico-projector system is the PicoP™ projector engine developed by Microvision, Inc. The PicoP engine includes RGB laser sources, a micro-electro-mechanical system (MEMS) scanning mirror, optics and video processing electronics for receiving video data from a source and generating an image to be projected onto any viewing surface (e.g., a screen, a wall, a sheet of paper or a chair back). However, projection systems that use a MEMS scanning mirror face some unique technical problems that are not evident with other methodologies. 
     A conventional MEMS scanning mirror implemented in a pico-projection system is a two-dimensional scanning mirror that sweeps laser beams across a viewing surface similar to the vertical and horizontal sweep of an electron beam in a CRT-based television or monitor. The horizontal sweep is typically done at one of the resonant mode frequencies of the scanning mirror that is on the order of 18 kHz. Operating on a resonant mode allows maximum beam deflection with minimal input energy. Although the horizontal movement is sinusoidal, the image may be pre-warped by an image processor in order to compensate for the sinusoidal movement. The vertical sweep is generally desired to be an ideal saw tooth to provide a linear sweep movement from top-to-bottom with minimal retrace time, thus maximizing the allowable active video time. A typical MEMS may have a horizontal and vertical drive input and horizontal and vertical sensor outputs. Each sensor provides an electrical signal in proportion to mirror movement in that axis. In that way, the actual movement and/or position of the scanning mirror can be monitored and/or controlled. 
     Ideally, the MEMS scanning mirror would have only one resonant mode at the horizontal sweep frequency. As described, the resonant mode associated with horizontal sweep is beneficial. Unfortunately, the mirror has multiple resonant modes for both vertical and horizontal movement. The first mode typically falls inconveniently within the frequency spectrum occupied by the vertical drive. 
     While the horizontal drive is a narrow band signal, a sine wave, falling right on a resonant mode, the ideal vertical waveform is a saw tooth or a modified saw tooth. This wideband waveform has harmonics extending to over 1 kHz, including some which will inevitably fall on or near the first mode of the MEMS scanner. 
     The high Q of the MEMS at its first mode will cause an accentuation of nearby frequency components about its vertical axis motion. This will distort the vertical sweep waveform, resulting in visible distortion of the raster image. To suppress these first mode oscillations in the vertical axis, various filtering methods such as low pass filters and/or notch filters may be employed. Similarly, the waveform may be created from a lookup table which is created with low pass and/or notch response. 
     Low pass and/or notch filtering may be employed with some degree of success. However, each has specific problems that are difficult to overcome, especially in a high volume manufacturing environment. Low pass filtering with adequate attenuation of the first mode may distort the vertical sweep waveform causing visible distortion at the top and/or bottom of the raster. Alternatively, the number of horizontal sweep lines may be reduced to avoid displaying this distorted region. Either result is undesirable. 
     Notch filtering has the ability to virtually eliminate first mode oscillations. Unfortunately, if the filter center frequency is even 1% different from the individual MEMS first mode frequency, unacceptable visible distortion of the raster image due to first mode oscillation will result. This makes implementation of a fixed frequency notch filter impractical in a high volume manufacturing environment. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       For a more complete understanding of this disclosure and its features, reference is now made to the following description, taken in conjunction with the accompanying drawings, in which: 
         FIG. 1  is a block diagram of a mobile phone that includes a pico-projection system according to one embodiment of the present disclosure; 
         FIG. 2  is a block diagram of selected portions of the projector module of  FIG. 1  according to one embodiment of the present disclosure; 
         FIG. 3  is a block diagram of a MEMS scanning mirror showing typical drive and sensor waveforms according to one embodiment of the present disclosure; 
         FIG. 4  is a graph illustrating a simplified conceptual MEMS response for various resonant modes according to one embodiment of the present disclosure; 
         FIG. 5  is a graph illustrating an unfiltered “perfect” saw tooth waveform; 
         FIG. 6  is a graph illustrating FFT derived spectral content of the “perfect” saw tooth waveform of  FIG. 5 ; 
         FIG. 7  is a graph illustrating a simulated vertical sensor waveform for the MEMS scanning mirror of  FIG. 3  with inadequate first mode suppression; 
         FIG. 8  is a graph illustrating FFT derived spectral content of the sensor waveform of  FIG. 7 ; 
         FIG. 9  is a raster plot, derived from the drive scenario of  FIGS. 7 and 8 , that shows first mode distortion; 
         FIG. 10  is a graph illustrating a simulated vertical sensor waveform for the MEMS scanning mirror of  FIG. 3  with adequate first mode suppression according to one embodiment of the present disclosure; 
         FIG. 11  is a raster plot, derived from the drive scenario of  FIG. 10 , that is uniform and shows no distortion according to one embodiment of the present disclosure; 
         FIG. 12  is a graph illustrating the first mode response of the MEMS scanner of  FIG. 2  according to one embodiment of the present disclosure; 
         FIG. 13  is a graph illustrating a notch frequency corresponding identically to the first mode response of  FIG. 12  according to one embodiment of the present disclosure; 
         FIG. 14  is a block diagram of the feedback loop from the MEMS scanner to the drive signal generator of  FIG. 2  according to one embodiment of the present disclosure; 
         FIGS. 15A-D  are graphs illustrating spectral error for various notch filter settings; 
         FIG. 16A  is a bode plot illustrating gain phase of the MEMS first mode according to one embodiment of the present disclosure; 
         FIG. 16B  is a bode plot illustrating open loop gain and phase margin according to one embodiment of the present disclosure; 
         FIG. 16C  is a bode plot illustrating closed loop response according to one embodiment of the present disclosure; 
         FIG. 16D  is a bode plot illustrating the MEMS drive according to one embodiment of the present disclosure; 
         FIG. 17  is a block diagram of the feedback loop from the MEMS scanner to the drive signal generator of  FIG. 2  according to another embodiment of the present disclosure; 
         FIGS. 18A-C  are simulated sensor waveforms showing the effect of gain adjustments in the feedback loop of  FIG. 17  according to one embodiment of the present disclosure; and 
         FIGS. 19A-C  are simulated raster diagrams showing the effect of gain adjustments in the feedback loop of  FIG. 17  according to one embodiment of the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
       FIGS. 1 through 19 , discussed below, and the various embodiments used to describe the principles of the present invention in this patent document are by way of illustration only and should not be construed in any way to limit the scope of the invention. Those skilled in the art will understand that the principles of the present invention may be implemented in any type of suitably arranged device or system. 
       FIG. 1  is a high-level block diagram of a mobile phone  100 , which includes an embedded pico-projection system according to one embodiment of the present disclosure. The mobile phone  100  is simply one particular embodiment of the present invention. Those skilled in the art will readily understand that the miniature projection system described herein may be embedded in other types of portable devices or may be implemented as a stand-alone device. 
     The illustrated mobile phone  100  comprises a main controller  105 , a memory block  110 , a communication bus  115 , a projector module  120 , a display block  130 , a user interface (IF)  135 , a transceiver  140  and an input-output interface (I/O IF)  145 . The main controller  105  is the central processor that supervises the overall operation of the mobile phone  100 . The memory block  110  may include one or more conventional read-only memory (ROM) devices and/or random access memory (RAM) devices (including a Flash RAM), as well as an optional removable memory card. The display block  130  may comprise typical LCD color display circuitry that is common to most mobile phones. The communication bus  115  enables the transfer of data between the main controller  105 , the memory  110  and the display  130 , as well as the projector module  120 . 
     The projector module  120  is a pico-projector device that uses, for example, three laser diodes (red, green and blue) to project an image onto any suitable surface, such as a wall, a screen, a sheet of paper, a desktop, or the like. The main controller  105  controls the projector module  120  in response to user commands that may be received via the user IF  135  or external commands that may be received via the transceiver  140 . By way of example, a user may enter commands that cause the main controller  105  to retrieve a slide show presentation file from the memory  110  and to display the slides via the projector module  120  and/or the display block  130 . 
       FIG. 2  is a block diagram of selected portions of the projector module  120  according to one embodiment of the present disclosure. For the illustrated embodiment, the projector module  120  comprises a video signal processor  205 , a laser diode driver  210 , a red laser diode (R LD)  215   a , a green laser diode (G LD)  215   b , a blue laser diode (B LD)  215   c , combiner optics  220 , a MEMS scanner with integrated sensors  225 , a controller  230  and a drive signal generator  235 . 
     The MEMS scanner  225  performs optical steering of the LASER beams provided by the combiner optics  220  to form a two-dimensional raster image  270 . As described in more detail below, the present disclosure provides a mechanism for suppressing undesirable oscillations in the MEMS scanner  225 . The disclosed embodiments are essentially tunable notch filters. For one embodiment, the MEMS vertical drive and sensor are placed in a phase-compensated feedback loop in order to provide a self-tuning notch filter that precisely removes the undesirable first mode oscillations. Another embodiment employs a tunable notch filter mechanism with feedback and suitable signal processing to determine the ideal filter setting. 
     The controller  230  generates control signals for the drive signal generator  235  and feeds back scanner position information to the video signal processor  205 . The control signals may be generated partly based on a sensor signal  265  received by the controller  230  from the scanner sensor of the MEMS scanner  225 , which is capable of sensing position and/or movement information related to the MEMS scanner  225 . The drive signal generator  235  is capable of generating horizontal and vertical drive signals  260  that cause the MEMS scanner  225  to sweep the light beam that is output by the combiner optics  220  across a viewing surface in order to generate the two-dimensional raster image  270 . 
       FIG. 3  is a block diagram of a MEMS scanning mirror  300  showing typical drive and sensor waveforms according to one embodiment of the present disclosure. For the illustrated embodiment, a horizontal drive signal  310  and a vertical drive signal  320  excite the mechanical motion of the MEMS scanner  225 . The drive signals  310  and  320  may be applied separately, as shown, or in any other suitable manner. For example, alternative methods may include using a drive signal comprising the composite of the signals  310  and  320  or composite differential of the signals  310  and  320 . Integral sensors (e.g., transducers) may convert the mechanical motion and/or position of the MEMS scanning mirror  300  into electrical signals for movement and/or position. For the illustrated embodiment, the sensor signals  330  correspond to horizontal axis movement and/or position and the sensor signals  340  correspond to vertical axis movement and/or position. 
       FIG. 4  is a graph  400  illustrating a simplified conceptual MEMS response for various resonant modes according to one embodiment of the present disclosure. This gain/phase plot  400  illustrates three resonant modes. An actual physical MEMS scanner  225  may have many more resonant modes. The first mode  410  in this example is at 780 Hz. As will be further described, the first mode  410  lies within the frequency range occupied by the vertical drive spectra and has mechanical response in the vertical axis. The third mode  420  in this example is at 18 kHz and has response in the horizontal axis. In this example, the third mode  420  is useful for horizontal sweep, while the first mode  410  is an artifact that interferes with vertical sweep. 
     Various means within the controller  230  and the drive signal generator  235  may be employed to match the frequency of the horizontal drive signal  310  to the appropriate MEMS resonant mode  420 . A more accurate match results in better horizontal drive-to-angular motion efficiency of the scanner  225 . 
     Typically, the fundamental vertical drive frequency of the vertical drive signal  320  will be a fixed integer quotient of the horizontal frequency. For example, the vertical drive frequency may be the horizontal frequency divided by 300. This scheme allows a fixed number of lines per raster frame. In the example MEMS response shown in the graph  400 , the horizontal sweep would be 18 kHz and the vertical sweep could be, for example, 60 Hz. In a display requiring 480 lines, bidirectional horizontal sweep allows an entire raster in 240 horizontal cycles, which amounts to 13.33 ms. 
       FIG. 5  is a graph  500  illustrating an unfiltered “perfect” saw tooth waveform. For this illustrated example, the saw tooth waveform has a 1/32 rise time and a 31/32 fall time. This results in a potential linear sweep region from a high point  510  to a low point  520  of 16.15 ms, which exceeds the requirement of 13.33 ms for the above-described example. 
       FIG. 6  is a graph  600  illustrating FFT derived spectral content of the “perfect” saw tooth waveform shown in the graph  500  of  FIG. 5 . The 60 Hz fundamental  610  is evident, but a strong harmonic component  620  at 780 Hz is also evident. This is identical to the first mode frequency  410  shown in the graph  400  of  FIG. 4 . In this worst case example, the harmonic stimulating the offending MEMS first mode response lies directly over the top of the first mode. However, with a 60 Hz sweep frequency, the nearest harmonic will be no farther than 30 Hz from the first mode in a best case condition. 
       FIG. 7  is a graph  700  illustrating a simulated vertical sensor waveform for the MEMS scanning mirror  300  with inadequate first mode suppression. As seen in the graph  700 , this waveform shows evidence of first mode oscillation  710 . In this simulated scenario, a notch filter was applied to the waveform of  FIG. 5  prior to the MEMS scanner  225 . However, the notch center frequency was set 0.2% higher than the 780 Hz first mode frequency. Consequences of this slightly imperfect filtering are evident in the oscillation  710 . 
       FIG. 8  is a graph  800  illustrating FFT derived spectral content of the sensor waveform shown in the graph  700  of  FIG. 7 . A harmonic  810 , which falls over the first mode, is slightly elevated above the next lower frequency harmonic. This is a deviation from a normal saw tooth spectra, which decreases at 6 db per octave. 
       FIG. 9  is a raster plot  900 , derived from the drive scenario of  FIGS. 7 and 8 , that shows first mode distortion  910 . Although aberrations at  710  and  810  seemed minor, significant first mode distortion  910  is evident in the raster plot  900 . It is evident that maintaining MEMS manufacturing tolerances to much less than 0.2% is not practical; therefore, the fixed notch solution is not a practical one for high volume production. 
       FIG. 10  is a graph  1000  illustrating a simulated vertical sensor waveform  1010  for the MEMS scanning mirror  300  with adequate first mode suppression according to one embodiment of the present disclosure. For this example, the notch filter frequency is set exactly to the first mode frequency. Filter Q is equivalent to the MEMS first mode Q. As seen in the graph  1000 , no first mode oscillations are evident in the waveform  1010 . 
       FIG. 11  is a raster plot  1100  derived from the drive scenario of  FIG. 10 . This raster plot  1100  is uniform and shows no distortion  1110  according to one embodiment of the present disclosure. Thus, when the notch filter frequency exactly matches the first mode frequency, no first mode distortion  1110  is evident. 
       FIG. 12  is a graph  1200  illustrating the first mode response  1210  of the MEMS scanner  225  according to one embodiment of the present disclosure. This response  1210  is modeled using a two-pole transfer function MEMS at a first mode of 780 Hz and Q MEMS  of 500. 
       FIG. 13  is a graph  1300  illustrating a notch frequency  1310  corresponding identically to the first mode response  1210  in the graph of  FIG. 12  according to one embodiment of the present disclosure. For this example, a transfer function  1320  with an NOTCH center frequency of 780 Hz and Q NOTCH  of 500 is used. 
     For the particular example as illustrated in  FIGS. 10-13 , the first mode frequency is 780 Hz with a Q of 500. This combination (MEMS NOTCH and Q MEMS =Q NOTCH ) yields a virtually perfect vertical motion response in simulations. Simulations also show that results are much less sensitive to notch filter Q (Q NOTCH ) than to notch center frequency NOTCH). These ideal results correspond to one embodiment of the present disclosure, which comprises an adaptive tunable notch filter that will be described further below. 
     Differing mathematical representations may be substituted for the transfer functions  1220  and  1320 . The illustrated example results in an approximate two-pole response of the resulting sensor signal  265  starting at the notch frequency. At lower first mode frequencies, this may cause distortion at the top and bottom of the raster due to excessive bandwidth limiting of the MEMS drive. Alternate transfer functions for the notch could include those that, when combined with the MEMS response, result in single-pole attenuation or even flat response, for example. 
     For the embodiment in which the tunable notch filter is an adaptive tunable notch filter, the notch filter has a center NOTCH) that is adaptively tuned to coincide to the MEMS first mode frequency MEMS) with a high degree of accuracy. Likewise, it is desirable to match the Q (bandwidth) of the notch filter to that of the MEMS first mode, but in practice it may be acceptable to set Q NOTCH  to a nominal value. 
       FIG. 14  is a block diagram of the feedback loop from the MEMS scanner  225  to the drive signal generator  235  according to one embodiment of the present disclosure. For this embodiment, the drive signal generator  235  comprises an original signal generator  1410 , a tunable notch filter  1430 , and a filter adapter  1450 . Tunable and/or adaptive tunable notch filters have been used widely in communications and instrumentation to eliminate unwanted interference frequencies. 
     However, the drive signal generator  235  uniquely implements an adaptive notch filter  1430  to precisely counteract the undesirable response of the MEMS scanner  225  (e.g., transducer) in the first mode. In other words, the adaptive notch filter  1430  does not attenuate an offending signal. Instead, the filter  1430  compensates for an offending transducer response in the MEMS scanner  225 . 
     Various discrete time or continuous time tunable notch filters may be employed to achieve these results. Physical filter size is a discrete time filter advantage at the relatively low first mode frequency. More important for adaptive filtering, discrete time filters are precisely programmable and repeatable. 
     The filter adapter  1450  may implement one of various adaptive filtering algorithms to control the tunable notch filter  1430 . Adaptive filtering is an extensive field of its own. An example is the Widrow-Hoff Least Means Squared Filter (LMS), invented in 1960 by Stanford University professor Bernard Widrow and Ted Hoff. Exploration of the LMS filter or other various adaptive algorithm possibilities is outside the scope of this disclosure. 
     For this embodiment, there are several considerations in choosing the adaptive process to be implemented by the filter adapter  1450 . Because the original signal generator  1410  generates a waveform  1420  (such as the saw tooth waveform  500  or other similar waveform) to be applied to the tunable notch filter  1430 , the exact harmonic frequencies are always known. Also, the ideal spectra (such as spectra  600 ) are known. However, the frequency and magnitude of the MEMS first mode response are unknown. 
     Knowledge of the fundamental and harmonic frequencies allows quadrature sampling of the sensor signal  265  at those specific frequencies, within the frequency range of interest. The frequency range would be selected to include, at minimum, the harmonic above and below the notch frequency. The filter adapter  1450  compares derived spectral content to the expected spectral content and, based on the comparison, generates an error signal  1440 , which can be used to tune the notch filter  1430 . 
       FIGS. 15A-D  are graphs illustrating spectral error for various notch filter settings. For the purpose of these simulations, the MEMS first mode frequency is set to 750 Hz, which is between waveform harmonics. The error signals are derived by subtracting the actual spectra from the expected spectra after some amplitude normalization. 
     While  FIGS. 15A-D  are based on FFT-derived spectra of the sensor signal  265 , it is nevertheless instructive of how spectra derived from quadrature sampling at harmonic frequencies provide information used to tune the notch filter  1430 . The primary relevant difference is that spectra  1530 ,  1550  and  1570 , all at 750 Hz, would not exist since there would be no samples taken at those frequencies. 
     The spectral error graph  1500  has no error, indicating that the notch filter  1430  is precisely set. The spectral error graph  1520 , which is simulated with the notch frequency 1% lower than the MEMS first mode frequency, shows spectra  1535  greater than spectra  1525 , indicating that the notch is to be moved to a higher frequency. The spectral error graph  1540 , which is simulated with the notch frequency 1% higher than the MEMS first mode frequency, shows spectra  1555  less than spectra  1545 , indicating that the notch is to be moved to a lower frequency. The spectral error graph  1560 , which is simulated with the notch frequency 0.1% lower than the MEMS first mode frequency, shows spectra  1575  greater than spectra  1565 , indicating that the notch is to be moved to a higher frequency. 
       FIGS. 15A-D  demonstrate that information is available to tune the notch filter  1430  in the desired direction, allowing various feedback schemes to be employed by the filter adapter  1450 . Other methods for deriving a suitable error signal  1440  may also be employed. The filter adapter  1450  may use this signal  1440  to tune the notch filter  1430 , thus suppressing first mode oscillation effects in the MEMS scanner  225 . 
     For another embodiment described below in connection with  FIGS. 16-19 , the MEMS scanner  225  is included in a feedback loop so that its drive becomes roughly the inverse of its first mode response. This inverse response is the functional equivalent of the adaptive tunable notch filter  1430  described of the above-described embodiment. Thus, this second embodiment provides all the advantages of the adaptive tunable notch filter  1430  without the need for a complex algorithm (implemented by the filter adapter  1450 ) to achieve perfect tuning. 
       FIGS. 16A-D  are bode plots relating to this second embodiment of the present disclosure. Since the MEMS scanner  225  is in a feedback loop for this embodiment, the gain and phase of the first mode are considered so that the loop may be compensated for stability. 
       FIG. 16A  is a bode plot  1600  illustrating gain phase of the MEMS first mode according to one embodiment of the present disclosure. The bode plot  1600  represents a MEMS scanner  225  with first mode Q of 300 and frequency of 720 Hz. This corresponds to a peak response  1605  of +49.5 db over the baseline, which is at −29.5 db, resulting in a peak first mode response  1605  of 20 db. Baseline magnitude is the drive-to-sensor transfer function of the MEMS scanner  225 . It takes into account the electrical-to-mechanical transducer function of drive-to-mirror movement, as well as mechanical-to-electrical transducer function of mirror movement-to-sensor signal. The exact baseline magnitude relationship may vary for various MEMS designs, and even unit-to-unit, due to manufacturing variation. 
     The drive-to-sensor phase response is −90° at the first mode peak  1605 . The relationship is expected to remain constant, though some MEMS sensor scenarios may alter this relationship. If so, the phase compensation, which will be further explained, are modified to ensure loop stability and first mode suppression. 
       FIG. 16B  is a bode plot  1620  illustrating open loop gain and phase margin according to one embodiment of the present disclosure. The bode plot  1620  illustrates ideal open loop response with gain plot  1630  and phase margin plot  1635  with gain. This response is achieved via gain and phase compensation applied to the response of  1600 . Ideal first mode suppression is achieved when gain is exactly 2Q MEMS  at the first mode peak  1625 , and phase margin is exactly 180° at the first mode frequency  1625 . The phase margin  1627  of 90° insures stability. 
       FIG. 17  is a block diagram of the feedback loop from the MEMS scanner  225  to the drive signal generator  235  according to the second embodiment of the present disclosure. For this embodiment, the drive signal generator  235  is configured to achieve a self-tuning notch filter drive at signal  260  using the MEMS scanner  225  first mode response at sensor signal  265 , in conjunction with an adder  1730 , an adjustable gain  1750  and a compensator  1760 . In the result graph  1620 , a 90° phase boost is achieved with a feedback consisting of a pure derivative phase boost  1760  with open loop feedback gain of 2Q MEMS  (55.6 db) set with adjustable gain  1750 . Open loop gain is determined by disconnecting the signal  1740  from the adder  1730  and by driving at the signal  1720  with a resulting open loop signal  1740 . 
     For the simulation graphs of  FIGS. 16A-D , the adjustable gain  1750  is set as follows: gain required 2Q MEMS  is +55.6 db. The pure derivative compensator  1760  gain of MEMS is +73.1 db. The MEMS scanner  225  first mode gain is +20 db. Thus, 55.6 db−73.1 db−20 db=−37.5 db for an adjustable gain  1750 . 
     Adequate stability can be achieved at significantly less than 90° phase margin  1627 . For example, a pole at higher frequency, such as 7 kHz, would tend to degrade the phase margin  1627  but would still leave adequate phase margin for stability. Adequate first mode suppression can be achieved when open loop gain falls in the range of approximately 20 LOG(2Q MEMS )±3 DB. A phase margin of 180° at the first mode frequency is ideal but somewhat less is acceptable. Care should be taken to minimize phase boost degradation at the first mode frequency. 
       FIG. 16C  is a bode plot  1640  illustrating closed loop response according to one embodiment of the present disclosure, and  FIG. 16D  is a bode plot  1660  illustrating the MEMS drive according to one embodiment of the present disclosure. The bode plot  1660  shows the closed loop drive signal  260  of  FIG. 17  applied to the MEMS scanner  225 . The notch  1665  is at exactly the first mode resonant frequency of peak response  1605 . Since this notch  1665  is actually created with the first mode response of the MEMS scanner  225 , the notch  1665  moves with temperature variations, manufacturing variations and/or design variations. 
       FIGS. 18A-C  and  19 A-C show the effect of proper adjustment of the gain  1750  of  FIG. 17 .  FIGS. 18A-C  are simulated sensor waveforms showing the effect of gain adjustments in the feedback loop of  FIG. 17  according to one embodiment of the present disclosure.  FIGS. 19A-C  are simulated raster diagrams showing the effect of gain adjustments in the feedback loop of  FIG. 17  according to one embodiment of the present disclosure. 
     The waveform  1800  is a simulation with the adjustable gain  1750  set to 10 db lower than ideal. Under-damping resulting in first mode ringing  1810  reduces the linear sweep time  1820  available for an undistorted raster. This results in visible first mode distortion  1910  of the raster  1900 , as shown in  FIG. 19A . 
     The waveform  1830  is a simulation with the adjustable gain  1750  set to its ideal value, as described above. Critical damping  1840  maximizes the linear sweep time  1820  available for an undistorted raster. This results in the perfectly formed raster  1930  of  FIG. 19B . 
     The waveform  1860  is a simulation with the adjustable gain  1750  set to 10 db higher than ideal. Over-damping resulting in rounding  1870  reduces the linear sweep time  1880  available for an undistorted raster. This results in visible rounding distortion  1970  of the raster  1960 , as shown in  FIG. 19C . 
     Adjustment of the adjustable gain amplifier  1750  may be implemented in any suitable manner. For example, the gain adjustment may be automated into the design so that the projector module  120  adjusts itself, the gain may be adjusted at manufacturing time by automated pattern and/or waveform recognition, or the gain may be roughly adjusted “by design” with the end user given the ability to provide fine adjustments. As another alternative, the gain may be adjusted by deterministically tracking the Q of the MEMS scanner  225  and using the tracked Q to set the gain at manufacturing time based on a tabular or closed-form solution. 
     In order to give a more intuitive understanding of the methodology, most of this disclosure has been in reference to continuous time representations. However, both the adaptive tunable notch filter  1430  and the self-tuned notch filter of  FIG. 17  may also be realized with mixed signal discrete time implementations. 
     It may be advantageous to set forth definitions of certain words and phrases used within this patent document. The term “couple” and its derivatives refer to any direct or indirect communication between two or more components, whether or not those components are in physical contact with one another. The terms “transmit,” “receive,” and “communicate,” as well as derivatives thereof, encompass both direct and indirect communication. The terms “include” and “comprise,” as well as derivatives thereof, mean inclusion without limitation. The term “or” is inclusive, meaning and/or. The term “each” means every one of at least a subset of the identified items. The phrases “associated with” and “associated therewith,” as well as derivatives thereof, may mean: to include, to be included within, to interconnect with, to contain, to be contained within, to connect to or with, to couple to or with, to be communicable with, to cooperate with, to interleave, to juxtapose, to be proximate to, to be bound to or with, to have, to have a property of, or the like. 
     While this disclosure has described certain embodiments and generally associated methods, alterations and permutations of these embodiments and methods will be apparent to those skilled in the art. Accordingly, the above description of example embodiments does not define or constrain this disclosure. Other changes, substitutions, and alterations are also possible without departing from the spirit and scope of this disclosure, as defined by the following claims.