Application of SCE Algorithm to determination of PID controller coefficients

Document Type : Complete scientific research article

Authors

Abstract

Abstract
Background and Objectives: Due to water resources shortage in our country, improvement of water distribution management is unavoidable matter for increase irrigation network performance. Control systems have an important role in water distribution irrigation network and network succesful depends on performance. Succesful modelling and running depends on tuning of control coefficients. Regarding the control, in general, the water level deviation from a pre-defined target level should be kept as small as possible. Aim of this study is determination of optimal control coefficients using SCE method.
Materials and Methods: In this study, PID controller (upstream control and downstream control) is developed for slide gate on the ICSS model. PID is the most commonly applied type of controller in control engineering. An error value is calculated as the difference between a measured water level and a desired target level. The controller attempts to minimize the error by adjusting the flow passing under the gates. The PID algorithm consists of three control terms: the proportional term (P) which depends on the present error; the integral term (I) which is based on accumulated errors; and the derivative term (D) which is based on rate of change of errors. For tuning PID coefficients, SCE algorithm is used for increment and decrement operation scenario in Mc canal of Alborz irrigation network with 12.6km length at 5hr time operation. The objective function consists of three performance indexes of MAE (Maximum Absolute Error), IAE (Integral of Absolute Error) and dimensionless form of SRT (System Response Time). Also Molden and gates indexes is used for performance assessment canal.
Results: Optimal coefficients controller are gained in operation scenario. Using gained coefficients, model will be able to tune water level in target level in increment and decrement process at short time. Maximum errors are related to C1 structure with 10cm in upstream controller and C3 structure with 6cm in downstream controller. Upstream controller are not able to tuning water level in downstream, so water supply in TO14 and TO16 is disturbed and MPA index is fair and poor performance classes Respectively for TO14 and TO16. The MPA index have been improved in downstream controller Compared to upstream controller. MPA, MPF, MPD indexes are good performance classes in both controller and MPE index is fair.
Conclusion: Results show gained optimal coefficients of the developed model to the upstream and downstream controllers is Responsive to changes in operation in a short time.

Keywords


1.Amein, M. 1968. An implicit method for numerical flood routing. J. Water Resour. Res.
4: 3. 719-726.
2.Bayalski, C.P., Ehler, D.G., Falvey, H.T., Rogers, D.C., and Serfozo, E.A. 1991. Canal
Systems Automation Manual. United State Bureau of Reclamation. 1.
3.Baume, J.P., Malaterre, P.O., and Sau, J. 1999. Tuning of PI controllers for an irrigation canal
using optimization tools. USCID Workshop. Pp: 483-500.
4.Clemmense, A.J., Kacerek, T.F., Grawitz, B., and Schuurmans, W. 1998. Test Cases for Canal
Control Algorithms. J. Irrig. Drain. Engin. 124: 1. 23-29.
5.Chu, W., Gao, X., and Sorooshian, S. 2010. Improving the shuffled complex evolution
scheme for optimization of complex nonlinear hydrological systems: Application to the
calibration of the Sacramento soil-moisture accounting model. J. Resour. Res. 46: 1-12.
6.Duan, Q., Sorooshian, S., and Gupta, V.K. 1992. Effective and efficient global optimization
for conceptual Rainfall-Runoff models. J. Water Resour. Res. 28: 4. 2493-2508.
7.Emadi, A. 2007. Mathematical Models Development of Optimal Operation in Irrigation
Canals Considering Conjunctive Use of Surface and Ground Water. Ph.D. Thesis of
Agricultural Department. Tarbiat Modaress University, 171p. (In Persian)
8.Emadi, A.R., and Kakouei, S. 2014. Determination of Optimal Parameters of Empirical Area
Reduction Method in Karaj Reservoir Dam using SCE. J. Water Soil Cons. 21: 3. 179-195.
(In Persian)
9.Henderson, F.M. 1966. Open channel flow. Macmillan Publishing Co. NewYork, 273p.
10.Hosseinzadeh, Z. 2010. Design and preparation of mathematical and physical models of
automatic overshot gate and its automatin system test. M.Sc. Thesis of Agricultural
Department. Tarbiat Modaress University, 162p. (In Persian)
11.Isapour, S. 2008. Modelling and Assessment of control algorithm in development of
management operation irrigation network (Case study: dez irrigation network). M.Sc. Thesis
of Tehran University, 128p. (In Persian)
12.Isapour, S., and Montazer, A.A. 2010. Assessment of global automatic downstream control
system PI in Dez irrigation network. P 1-8, 3th National Conference on irrigation and
drainage network management, Ahwaz. (In Persian)
13.Jamali, S. 2011. Development of Optimization Model for PID Automatic Control Parameters
in ICSS Model Using GA. M.Sc. Thesis of Agricultural Department. Tarbiat Modaress
University, 145p. (In Persian)
14.Jeon, J.H., Park, C.G., and Engel, B.A. 2014. Comparison of Performance between Genetic
Algorithm and SCE-UA for Calibration of SCS-CN Surface Runoff Simulation. J. Water.
6: 3433-3456.
15.Joes, V.A., Pedro, L., Joes, R., Lorenzo, L., and Keloudia, H. 2016. Predictive control of
irrigation canals – robust design and real-time implementation. J. Water Resour. Manage.
30: 3829-3843.
16.Litrico, X., Malatterre, J.P., Voin, P.Y., and Ribot– Bruno, J. 2007. Automatic Tuning of PI
controllers for Irrigation Canal Pool. J. Irrig. Drain. Engin. 133: 1. 27-37.
17.Mahab Ghods (Consulting Engineers). 2009. Instruction for operation and maintenance of
MC canal, 121p. (In Persian)
18.Malaterre, P.O., Roggers, D.C., and Schuurmans, J. 1998. Classification of canal control
algorithm. J. Irrig. Drain. Engin. 124: 1. 3-10.
19.Manz, D.H. 1985. System analysis of irrigation conveyance system. Thesis as a Part of the
Requirements of Doctor of Philosophy in Civil Engineering. University of Alberta.
Edmonton. Alberta, Canada, 435p.
20.Merkley, G.P. 1997. Canalman User's Guide. Dept. of Biological and Irrigation Engineering,
Utah State University.
21.Molden, D.J., and Gates, T.K. 1990. Performance measures for evaluation of irrigation water
delivery systems. J. Irrig. Drain. Engin. 116: 6. 804-822.
22.Monem, M.J., and Mamizadeh, J. 2005. Development of Mathmatical model of BIVAL
Downstream Control System in Irrigation Canals. 5th Iranian Hydroulic Conference. Kerman,
Pp: 1-10. (In Persian)
23.Onyari, E., Taigbenu, A., and Ndiritu, J. 2016. Groundwater Pollution Source Identification
by Optimization and the Green Element Method. World Environmental and Water Resources
Congress, Pp: 1-10.
24.Qaderi, K., Samani, J.M.V., Eslami, H.R., and Saghafian, B. 2006. Auto calibration of
a rainfall- runoff model based on sce method. J. Iarn- Water Resour. Res. 2: 2. 39-52.
(In Persian)
25.Sadeghi Tebs, S., and Pourreza Bilandi, M. 2015. Comparison of optimization and uncertainty
analysis methods in hydrological modeling. J. Range Water. Manage. 68: 3. 533-552.
(In Persian)
26.Schuurmans, J. 1997. Control of Water Levels in Open-Channels. Desertation (TUDelft),
235p.
27.Seyedmousavi, S.M., Parvaresh Rizi, A., and Isapour, S. 2015. Improving the Coefficients of
Proportional-Integral Controller Based On System Identification Process on Doosti Irrigation
Network. J. Water Soil. 29: 4. 850-860. (In Persian)
28.Slambolchzadeh, H. 2006. Assessment and improvement of the reservoir management in
operation irrigation network (case study: Moghan irrigation network). M.Sc. Thesis of
Agricultural Department. Tarbiat Modaress University, 105p. (In Persian)
29.Sorooshian, S., Duan, Q., and Gupta, V.K. 1993. Calibration of Rainfall-Runoff models:
application of global optimization to the Sacramento soil moisture accounting model.
Water Resources Research. 29: 4. 1185-1194.
30.Strekloff, T. 1969. One dimensional equation of open channel flow. J. Hydr. Divi. ASCE.
7: 4. 861-876.
31.Van Overloop, P.J., Schuurmans, J., Brouwer, R., and Burt, CM. 2005. Multiple model
optimization of proportional integral controllers on canals. Irrigation and Drainage
Engineering. 131: 190-196.
32.Zhou, B., Clough, D.E., and Fuentes, Y.O. 1995. A PID Controller with Adaptive Error
Dispersion for Interacting Gates on Main Irrigation Canals. American Control Conference,
Pp: 1-5