Abstract
Almost all the industrial processes are multivariable in nature and are very difficult to control, since it involves many variables, strong interactions and nonlinearities. Conventional controllers are most widely used with its optimal parameters for such processes because of its simplicity, reliability and stability. Coal gasifier is a highly nonlinear multivariable process with strong interactions among the loop and it is difficult to control at 0% operating point with sinusoidal pressure disturbance. The present work uses Normalized Normal Constraint (NNC) algorithm to tune the parameters of decentralised PI controller of coal gasifier. Maximum absolute error (AE) and Integral of Absolute Error (IAE) are objective function while the controller parameters of decentralised PI controller are the decision variables for the NNC algorithm. With the optimal controller the coal gasifier provides better response at 0%, 50% and 100% operating points and also the performance tests shows good results.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Dixon, R., Pike, A.W.: Alstom Benchmark Challenge II on Gasifier Control. IEE Proceedings - Control Theory and Applications 153(3), 254–261 (2006)
Chin, C.S., Munro, N.: Control of the ALSTOM gasifier benchmark problem using H2 methodology. Journal of Process Control. 13(8), 759–768 (2003)
Al Seyab, R.K., Cao, Y., Yang, S.H.: Predictive control for the ALSTOM gasifier problem. IEE Proceedings - Control Theory and Application 153(3), 293–301 (2006)
Al Seyab, R.K., Cao, Y.: Nonlinear model predictive control for the ALSTOM gasifier. Journal of Process Control 16(8), 795–808 (2006)
Agustriyanto, R., Zhang, J.: Control structure selection for the ALSTOM gasifier benchmark process using GRDG analysis. International Journal of Modelling, Identification and Control 6(2), 126–135 (2009)
Tan, W., Lou, G., Liang, L.: Partially decentralized control for ALSTOM gasifier. ISA Transactions 50(3), 397–408 (2011)
Sivakumar, L., Anitha Mary, X.: A Reduced Order Transfer Function Models for Alstom Gasifier using Genetic Algorithm. Int. J. of Computer Applications 46(5), 31–38 (2012)
Kotteeswaran, R., Sivakumar, L.: Lower Order Transfer Function Identification of Nonlinear MIMO System-Alstom Gasifier. International Journal of Engineering Research and Applications 2(4), 1220–1226 (2012)
Huang, C., Li, D., Xue, Y.: Active disturbance rejection control for the ALSTOM gasifier benchmark problem. Control Engineering Practice 21(4), 556–564 (2013)
Simm, A., Liu, G.P.: Improving the performance of the ALSTOM baseline controller using multiobjective optimization. IEE-Control Theory and Applications 153(3), 286–292 (2006)
Nobakhti, A., Wang, H.: A simple self-adaptive Differential Evolution algorithm with application on the ALSTOM gasifier. Applied Soft Computing 8(1), 350–370 (2008)
Xue, Y., Li, D., Gao, F.: Multi-objective optimization and selection for the PI control of ALSTOM gasifier problem. Control Engineering Practice 18(1), 67–76 (2010)
Zhou, A., Qu, B.Y., Li, H., Zhao, S.-Z., Suganthan, P.N., Zhang, Q.: Multiobjective Evolutionary Algorithms: A Survey of the State-of-the-art. Swarm and Evolutionary Computation 1(1), 32–49 (2011)
Zhao, S.Z., Willjuice Iruthayarajan, M., Baskar, S., Suganathan, P.N.: Multi-objective robust PID controller tuning using two lbests multi-objective particle swarm optimization. Information Sciences 181(16), 3323–3335 (2011)
Messac, A., Ismail-Yahaya, A., Mattson, C.A.: The Normalized Normal Constraint Method for Generating the Pareto Frontier. Structural and Multidisciplinary Optimization 25(2), 86–98 (2003)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Kotteeswaran, R., Sivakumar, L. (2013). Normalized Normal Constraint Algorithm Based Multi-objective Optimal Tuning of Decentralised PI Controller of Nonlinear Multivariable Process – Coal Gasifier. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8297. Springer, Cham. https://doi.org/10.1007/978-3-319-03753-0_30
Download citation
DOI: https://doi.org/10.1007/978-3-319-03753-0_30
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-03752-3
Online ISBN: 978-3-319-03753-0
eBook Packages: Computer ScienceComputer Science (R0)