Algorithms and Architectures for Real-Time Control 1991: by P. J. Fleming, D. I. Jones

By P. J. Fleming, D. I. Jones

Desktop scientists have lengthy preferred that the connection among algorithms and structure is essential. normally the extra really good the structure is to a specific set of rules then the extra effective often is the computation. The penalty is that the structure becomes dead for computing something except that set of rules. This message holds for the algorithms utilized in real-time automated keep watch over up to the other box. those lawsuits will supply researchers during this box with an invaluable up to date reference resource of contemporary advancements.

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Additional info for Algorithms and Architectures for Real-Time Control 1991: Proceedings of the IFAC Workshop, Bangor, North Wa (IFAC Workshop Series)

Example text

In orde r to asses s the performanc e of this new technique , we have built a real-tim e implementation , programme d in OCCA M and execute d on INMO S transputers . A descriptio n is given of the main constituen t blocks , with a specia l emphasi s on the block whic h is responsibl e for the adaptatio n mechanism . The result s obtaine d are presente d for simulate d plant s with varyin g time-dela y and varyin g number , and locations , of the poles . Keyword s . PID autotuning , paralle l processing , neura l networks , adaptiv e control , multilaye r perceptrons , OCCAM .

In orde r to asses s the performanc e of this new technique , we have built a real-tim e implementation , programme d in OCCA M and execute d on INMO S transputers . A descriptio n is given of the main constituen t blocks , with a specia l emphasi s on the block whic h is responsibl e for the adaptatio n mechanism . The result s obtaine d are presente d for simulate d plant s with varyin g time-dela y and varyin g number , and locations , of the poles . Keyword s . PID autotuning , paralle l processing , neura l networks , adaptiv e control , multilaye r perceptrons , OCCAM .

We have solved that proble m by splittin g the adaptatio n bloc k betwee n two processe s (runnin g on differen t processors) , the secon d of thes e bein g responsibl e for the actua l computatio n of F(a), and subsequently , the PID parameters . RESULT S Off-lin e trainin g of the thre e MLP s is conducte d usin g MATLA B (Mole r 1987 ) runnin g on a Sun Spar c station . 30 adaptiv e tuning . Durin g step 4 the plan t was identified . When the fifthstep was detected , Τχ was compute d by the first adaptatio n block , and its valu e transmitte d to the secon d adaptatio n block , alon g with the contro l sample s referrin g to the fourt h step and othe r data neede d to comput e F(a) .

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