Loop control, MATLAB

Hence, our first step is to use root locus to find the closed-loop poles of a PI control system with a damping ratio of 0.8. The MATLAB statements to continue with Example 4.7B are ... 

This paper presents the application of a model based predictive control strategy for the primary stage of the freeze drying process, which has not been tackled until now. A model predictive control framework is provided to minimize the sublimation time. The problem is directly addressed for the non linear distributed parameters system that describes the dynamic of the process. The mathematical model takes in account the main phenomena, including the heat and mass transfer in both the dried and frozen layers, and the moving sublimation front. The obtained results show the efficiency of the control software developed (MPC CB) under Matlab. The MPC( CB based on a modified levenberg-marquardt algorithm allows to control a continuous process in the open or closed loop and to find the optimal constrained control. 

MATLAB and SIMULINK are invaluable tools for the finequency- and time-domain calculations required for C R analysis. In this section, several examples are carried out using MATLAB, it being assumed that the reader is familiar with the MATLAB syntax. The reader is referred to Bequette (1998) for details of MATLAB usage in dynamical analysis and control, and to the multimedia CD-ROM that accompanies this text for sources of these and other useful MATLAB functions and scripts for C R analysis. In particular, the interactive C R Tutorial CRGUI can be used to test three example linear processes for controllability and resiliency and simulate their closed-loop response under single-loop PI control. 

Control and dynamics MATLAB/Simulink System response to a perturbation Control loop... 

As a process simulator, we used Aspen HYSYS (see Figure 8.15). In all the scenarios, as initial values, we use the stream values obtained when the simulation is done in open loop. Moreover, instead of using the simnlator tools for converging the system (the recycle unit operation in HYSYS), we connect the simulator with external modules developed in MATLAB . In that way, we have a complete control over the numerical methods used for converging the system. In all the cases, a termination tolerance is eqnal to 10 , using a norm 1. 

The Nichols chart in Fig. J.15 provides a graphical display of the closed-loop frequency response characteristics for set-point changes when G is) = Kjn Contours of constant AR l and ql are shown on a plot of ARol vs. OL- In a typical Nichols chart application, ARq and ql are calculated from Gol s) and plotted on the Nichols chart as a series of points. Then AR l and CL are obtained by interpolation. For example, if ARol 1 and ql = -100° at a certain frequency, then interpolation of Fig. J.15 gives ARcl = 0.76 and CL = 50° for the same frequency. The Nichols chart can be generated in the MATLAB Control Toolbox by a single command, nichols. 

MATLAB [8]. For clarity, these equations are repeated below with their original numbering and are in the order that they appear in the control loop, with the values of the constant parameters showa... 

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