Auto Floodgate Control Using EnKf-NMPC Method

Evita Purnaningrum, Erna Apriliani

Abstract


One of the flood controls, especially in the downstream areas are barrage. Those are optimized using Ensemble Kalman filter based non linear predictive control. Ensemble Kalman Filter is used to predict water levels and flow of waters when it reaches the barrage. The results obtained from this method is then used as input for controlling the floodgates. Simulations are performed in three circumstances, namely the normal flow, flooding and drought. For normal flow, using optimum quantities are obtained from NMPC by opening the floodgates. Simulations were performed for 100 hours, with a gap of 5 per hour of observation. EnKf fulfilled with RMSE yields accuracy of the system and estimates of less than 1, RMSE debit is 0.5346 and RMSE water level is 0.2716. Furthermore the operation of the opening gate achieves optimum value, with the movement of between 40 - 65 per cent, with an average difference of movement is 0.10065 percent. Flood conditions, the water flow 2.000 m3/s and the water level 10 m operation of opening gate ranging between 98 - 100 per cent and the amount of the difference opening gate is 0.028835. RMSE to estimate the flow rate of 1.5835, while for the water level of 0.3145. While the flow conditions dry, with water flow 10 m3/s and the water level 1 m operation of opening gate ranging between 0 - 1 percent and the amount of the difference opening gate is 0.41289 percent. RMSE to estimate the flow rate of 0.0826, while for the water level of 0.0677.

Keywords


Floodgate Control; estimation; ensemble Kalman filter; nonlinear MPC

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References


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DOI: http://dx.doi.org/10.12962/j24775401.v2i1.1579

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International Journal of Computing Science and Applied Mathematics by Department Mathematics ITS is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Based on a work at http://iptek.its.ac.id/index.php/ijcsam.