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#21 |
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diyAudio Member
Join Date: Feb 2004
Location: Illinois
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TMS320C549 is in the process of being aquired, there may be a bit of work involved with getting it set up as I do not know what exactly the DSP will come with (DAC, ADC, connectors etc). Algorithm/modeling is still on the drawing board. MATLAB will be a friend of the project for the next few weeks.
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#22 | ||||||
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diyAudio Member
Join Date: Feb 2004
Location: Texas
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Second, we are not bothered by the 2nd order distortion. It is the 3rd and higher order that I am interested (because the audible curves of human hearing). The 2nd order distortion is simply less audible. More important, it is the spider distortion and temperature memory effect that we are trying to reduce. Quote:
My view on this issue is the DSP is best suited for feedforwad error correction where latency is not an issue. And feedforward correction needs correct modeling of the subject (which is the driver) and constantly refine the models to compensate for time-to-time and unit-to-unit variations. This is possible for consistent, tight tolerance components. But speakers are not. In addition, if we look at those Tripath amplifiers, they still need closed loop feedback even though they have tons of feedforward distortion reduction. The last few miles will be from closed loop, only. Let us keep in mind Dr. Klippel's feedforward error correction papers were published almost 8 years ago (correct me if I am wrong) and I yet to see a feasible, robust, and mass-reproduceable implementation. The difficulty is definitely there and your accessment of the number of parameters are definitely true. And personably I think the issue is inherited and cannot be resolved. Brian D. Rythmik Audio |
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#23 |
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diyAudio Member
Join Date: Feb 2004
Location: Texas
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Another point about all mighty DSP. There is another long-forgotten name for the feedforward error correction (distortion reduction) circuit (algorithms?) used by DSP --- it is called "pre-distortion" circuit. This name will give you a better idea what DSP cannot do and what closed loop feedback can do. A closed loop does not care the amount of distorion in the system. If the system does not have any distortion (or lower distortion), it works even better. Same thing cannot be say about feedforard system.
Cheers Brian |
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#24 |
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diyAudio Member
Join Date: Feb 2003
Location: ..
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i believe the beolab 5 claims voice coil resistance compensation is done by modeling the temp rise by the dsp - an example of a consumer loudspeaker feedforward correction application
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#25 | |
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diyAudio Member
Join Date: Feb 2004
Location: Texas
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The idea of feedforward system is that it anticipates a distortion (or characterisitic change) and inject the distortion (that is, pre-distortion) in hope it will exactly cancel the actual distortion. So there are 2 distortion components in the system, one from distortion of the system itself and one from the pre-distortion. What if they don't match because incorrect or incompletely modelling or incorrect measurement of the parameters? In this case, will hear one "natural" distortion plus one "synthetic distortion". Even worse, what if the pre-distortion component is always one step behind the actual distortion. It is like hearing some form of echo. It is true feedforward system will not oscillate. But it has its own set of problems. Servo is still managable using closed loop feedback. It is just that most people do not understand the control theory behind it, what makes it work and what makes it break. The effect of creep and flux modulation can be addressed with a closed loop feedback system. Cheers Brian |
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#26 |
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diyAudio Member
Join Date: Feb 2004
Location: Illinois
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I thought I should provide updates in case anyone is interested.
The DSP has been setup and a few function generators gathered for testing. The current scheme is using a derivative of the LMS (Least Mean Squared) algorithm, the same type used by many noise canceling devices and motor control circuits. After matlab simulations everything looked well. Using two function generators, one for the desired signal and one for the "distorted" signal the system was able to match the two signals very well. While wrentching on the voltage of one signal, the two remained close to eachother. It is not a very stressful and true to life situation though so now the sub and accelerometer have been brought into the equation while using a function generator as the input. The system proved to be unstable at first but tweaking the "mu" for the algorithm has helped and can now be run for extended periods of time. Its performance isn't where we would like it yet, but there are places for improvement. The accelerometer is only taped onto the sub and this poor coupling appears to be causing problems as it mechanically vibrates on its own. The next step is to epoxy it to the dust cap (which happens to be extremely rigid). Further improving and at the suggestion of a professor who is very familiar with adaptive algorithms, tonight we moved from the dlms (delayed lms) to the ndlms (normallized delayed lms) which has a dynamic "mu" and converges faster than the dlms with a slight increase in computational complexity. Additionally, we are implementing a leakage factor to take into accound the fixed point precision of the DSP. Round off errors accumulate over time and "bleeding" the filter coefficients very slowly keeps it under control and helps make sure this does not cause an overflow in the filter taps. So as you can see we haven't gone the way of a feed forward system. I wish I had time to investigate all of this but the way the class and my undergrad schedule goes, my lab partner and I had to pick a method and pretty much go with it. Making an attempt at a few different situations would end up giving me a brief experience of them all and possibly running out of time to make an at least decent functional system. Hopefully in the next five weeks we can continue improving and make the system work very well. Random Specs: Filter Implementation: FIR Filter Length: 128-768 still experimenting DSP: TMS320C549, 100MHz Current Algorithm: ndlms with tap leakage Sampling Rate: 44.1kHz wish I could lower this but that appears to be all that can be gotten from the board we have unless a crystal replacement is attempted Buffer size: 512-4096 samples, still experimenting with this as well There are quite a few algorithm parameters we are considering as well but those would prove to be too numerous to provide as we still do not have anywhere close to a "solid" range of what is going to be settled on. |
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