Experimental validation of LMI approaches for robust control design of a spatially three-dimensional heat transfer process

In this paper, two alternative control procedures are compared for a spatially three-dimensional distributed heating system. In both cases, the system model is derived as a finite volume representation that assumes a piecewise homogeneous distribution of the temperature in each finite volume element. The parameterization of both control strategies is performed by using linear matrix inequalities in combination with a polytopic model for uncertain system parameters. The basic difference between both implementations is that either parameter-independent or parameter-dependent candidates for Lyapunov functions are assumed in the derivation of the control laws. It is shown experimentally that both approaches lead to an accurate tracking of smooth temperature trajectories. However, the parameter-dependent approach is less conservative and, in such a way, leads to a smaller amplification of measurement noise in an observer-based closed-loop control structure.

[1]  Andreas Rauh,et al.  Reliable finite-dimensional models with guaranteed approximation quality for control of distributed parameter systems , 2012, 2012 IEEE International Conference on Control Applications.

[2]  E. Yaz Linear Matrix Inequalities In System And Control Theory , 1998, Proceedings of the IEEE.

[3]  N. Nedialkov,et al.  Solving differential algebraic equations by Taylor Series(III): the DAETS Code , 2008 .

[4]  L. Vandenberghe,et al.  Extended LMI characterizations for stability and performance of linear systems , 2009, Syst. Control. Lett..

[5]  J. Lofberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004, 2004 IEEE International Conference on Robotics and Automation (IEEE Cat. No.04CH37508).

[6]  Andreas Rauh,et al.  An integrodifferential approach to modeling, control, state estimation and optimization for heat transfer systems , 2016, Int. J. Appl. Math. Comput. Sci..

[7]  Johan Löfberg,et al.  YALMIP : a toolbox for modeling and optimization in MATLAB , 2004 .

[8]  Andreas Rauh,et al.  Finite element modeling for heat transfer processes using the method of integro-differential relations with applications in control engineering , 2014, 2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR).

[9]  H. Aschemann,et al.  A differential-algebraic approach for robust control design and disturbance compensation of finite-dimensional models of heat transfer processes , 2013, 2013 IEEE International Conference on Mechatronics (ICM).

[10]  N. Nedialkov,et al.  Solving Differential-Algebraic Equations by Taylor Series (I): Computing Taylor Coefficients , 2005 .

[11]  Andreas Rauh,et al.  Design and experimental validation of control strategies for commercial gas preheating systems , 2013, 2013 18th International Conference on Methods & Models in Automation & Robotics (MMAR).

[12]  B. Ross Barmish,et al.  New Tools for Robustness of Linear Systems , 1993 .

[13]  Jos F. Sturm,et al.  A Matlab toolbox for optimization over symmetric cones , 1999 .

[14]  N. Nedialkov,et al.  Solving differential algebraic equations by Taylor Series(III): the DAETS Code , 2005 .

[15]  Stephen P. Boyd,et al.  Linear Matrix Inequalities in Systems and Control Theory , 1994 .

[16]  Andreas Rauh,et al.  Robust Control for a Spatially Three-Dimensional Heat Transfer Process , 2015 .

[17]  O. Sawodny,et al.  Flatness-based disturbance decoupling for heat and mass transfer processes with distributed control , 2006, 2006 IEEE Conference on Computer Aided Control System Design, 2006 IEEE International Conference on Control Applications, 2006 IEEE International Symposium on Intelligent Control.