This paper deals with the analysis and design of a model predictive control (MPC) strategy used in connection with level control in conically shaped industrial liquid storage tanks. The MPC is based on a non-linear dynamic model describing changes of the liquid level concerning changes in the inlet flow of the liquid. Euler discretization of the dynamic system was applied to transform con-tinuous time dynamics to its discrete-time counterpart used in non-linear MPC (NMPC) design. By means of a simulation case study, NMPC has been shown to track the changes of the liquid level, hence provides increased control performance. This paper also compares the traditional approach of optimal control, linear MPC, with the NMPC strategy.
Al-Shahrani MH, Mahfoud M, Anvarbatcha R, Athar T, Asmari AA (2017) Pharmacognosy Communications 7: 34–40.
Allgöwer F, Findeisen R, Nagy ZK (2004) Nonlinear model predictive control: From theory to application.
Bakošová M, Oravec J (2014) Robust mpc of an unstable chemical reactor using the nominal system optimization. Acta Chimica Slovaca, 7(2): 87–93.
Camacho EF, Bordons C (2007) Model Predictive Control. Springer, 2nd edition.
Jelemenský M, Klaučo M, Paulen R, Lauwers J, Logist F, Impe JV, Fikar M (2016) Time-optimal control and parameter estimation of diafiltration processes in the presence of membrane fouling. In 11th IFAC Symposium on Dynamics and Control of Process Systems, including Biosystems, volume 11, pages 242–247.
King M (2010) Process Control: A Practical Approach. Wiley.
Kvasnica M, Herceg M, Čirka Ľ, and Fikar M (2010) Model predictive control of a cstr: A hybrid modeling approach. Chemical papers, 64(3): 301–309.
Lawryńczuk M (2017) Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation. ISA Transactions, 67: 476–495.
Mayne DQ, Rawlings JB, Rao CV, Scokaert POM (2000) Constrained model predictive control: Stability and optimality. Automatica, 36(6): 789–814.
Mikleš J, FikarM(2007)ProcessModelling,Identification, and Control. Springer Verlag, Berlin Heidelberg.
Muske KR (1997) Steady-state target optimization in linear model predictive control. In American Control Conference, 1997. Proceedings of the 1997, volume 6, pages 3597–3601.
Muske KR, Badgwell TA (2002) Disturbance modeling for off set-freelinear model predictive control. Journal of Process Control, 12(5): 617–632.
Nocedal J, Wright SJ (2006) Numerical Optimization. Springer, New York, 2nd edition.
Primbs J (2007) A soft constraint approach to Stochastic Receding Horizon Control. In Decision and Control, 2007 46th IEEE Conference on, pages 4797–4802.
Rawlings JB, Mayne DQ (2009) Model predictive control: Theory and design.
Sharma A, Fikar M, Bakošová M (2015) Comparative study of time optimal controller with pid controller for a continuous stirred tank reactor. Acta Chimica Slovaca, 8(1): 27–33.
Zeilinger M, Jones C, Morari M (2010) Robust stability properties of soft constrained mpc. In Decision and Control (CDC), 2010 49th IEEE Conference on, pages 5276–5282.