@article { author = {Gholaminejad, Tahereh and Khaki-Sedigh, A. and Bagheri, P.}, title = {Adaptive Tuning of Model Predictive Control Parameters Based on Analytical Results}, journal = {AUT Journal of Modeling and Simulation}, volume = {50}, number = {2}, pages = {109-116}, year = {2018}, publisher = {Amirkabir University of Technology}, issn = {2588-2953}, eissn = {2588-2961}, doi = {10.22060/miscj.2017.12143.5005}, abstract = {In dealing with model predictive controllers (MPC), controller tuning is a key designing step. Various tuning methods are proposed in the literature which can be categorized as heuristic, numerical and analytical methods. Among the available tuning methods, analytical approaches are more interesting and useful. This paper is based on a proposed analytical MPC tuning approach for plants which can be approximated by first-order plus dead-time models. The performance of such methods fails to deal with unknown or time-varying parameter plants. To overcome this problem, adaptive MPC tuning strategies are practical alternatives. The adaptive MPC tuning approach proposed in this paper is based on on-line identification and analytical tuning formulas. Simulation results are used to show the effectiveness of the proposed methodology. Also, a comparison of the proposed adaptive tuning method with a well-known online tuning method is presented briefly which shows the superiority of the proposed adaptive tuning method.}, keywords = {Adaptive model predictive control,analytical tuning,first order plus dead time models}, url = {https://miscj.aut.ac.ir/article_1036.html}, eprint = {https://miscj.aut.ac.ir/article_1036_7b98492c49f6aa0e244c1fa259403256.pdf} } @article { author = {Nazari-Monfared, M. and Yazdanpanah, M. J.}, title = {Elimination of Hard-Nonlinearities Destructive Effects in Control Systems Using Approximate Techniques}, journal = {AUT Journal of Modeling and Simulation}, volume = {50}, number = {2}, pages = {117-122}, year = {2018}, publisher = {Amirkabir University of Technology}, issn = {2588-2953}, eissn = {2588-2961}, doi = {10.22060/miscj.2017.12217.5016}, abstract = {Many of the physical phenomena, such as friction, backlash, drag, etc., which appear in mechanical systems are inherently nonlinear and have destructive effects on the control system behavior. Generally, they are modeled by hard nonlinearities. In this paper, two different methods are proposed to cope with the effects of hard nonlinearities which exist in various models of friction. Simple inverted pendulum on a cart (SIPC) is considered as a test bed system, as well. In the first technique, a nonlinear optimal controller based on the approximate solution of Hamilton-Jacobi-Bellman (HJB) partial differential equation (PDE) is designed for the system and finally, an adaptive anti disturbance technique is proposed to eliminate the friction destructive effects. In the second one, three continuous functions are used to approximate hard nonlinearities when they are integrated into the system model. These techniques are compared with each other using simulations and their effectiveness is shown.}, keywords = {adaptive,approximate functions,Friction,hard nonlinearities,HJB PDE}, url = {https://miscj.aut.ac.ir/article_991.html}, eprint = {https://miscj.aut.ac.ir/article_991_0bbb7e64c33709ae19230729043012f2.pdf} } @article { author = {Davarnejad, R. and Hekmat, M.}, title = {Numerical study on influence of a type of nanoparticles and volume fraction on turbulent heat transfer coefficient and pressure loss inside a tube}, journal = {AUT Journal of Modeling and Simulation}, volume = {50}, number = {2}, pages = {123-128}, year = {2018}, publisher = {Amirkabir University of Technology}, issn = {2588-2953}, eissn = {2588-2961}, doi = {10.22060/miscj.2018.13315.5069}, abstract = {Conventional liquids have some limitations regarding the thermal properties. The nanoparticles addition is one of the techniques which can transcend them. In this research, heat transfer coefficient (h) and pressure loss (Δp) of various nanofluids containing Al2O3, SiO2, and MgO nanoparticles dispersed in water in an annular tube with constant wall temperature is considered. According to the literature, five different nanofluid volume concentrations (1%, 2%, 3%, 4% and 5%) are selected. Two models involving the mixture and VOF are applied, and the results are compared. The average convective heat transfer coefficient and pressure loss is enhanced with volume fraction and Reynolds number (Re) increment (3000