Self-tuning controllers

Foxboro developed a self-tuning PID controller that is based on a so-called expert system approach for adjustment of the controller parameters. The on-line tuning of K, Xi, and Xo is based on the closed-loop transient response to a step change in set point. By evaluating the salient characteristics of the response (e.g., the decay ratio, overshoot, and closed-loop period), the controller parameters can be updated without actually finding a new process model. The details of the algorithm, however, are proprietary... 

The development vehicle used to create and test the rule base must be as flexible as possible, allowing easy alterations and expansion of the rule base with whatever displays can convey the most information. The delivery vehicle, however, should be virtually transparent to the user, conveying only as much information as needed to solve the problem at hand. Self-tuning controllers can perform their task without explicitlv informing users, but their output and status is available on demanci, and their operation may be easily limited or interrupted. 

Roliani, S. and Bourne, J., 1990b. Self-tuning control of crystal size distribution in a batch cooling crystallizer. Chemical Engineering Science, 45, 3457-3466. 

Figure 3. Example of Graphical Output from Analysis Mode. Reaction progress for water-jacketted reactor, with Cascade coupled temperature controllers, both in self-tuning mode.

This result demonstrates that the self-spreading dynamics are controllable by tuning the bilayer-substrate interactions. The above-mentioned electrolyte dependence is an example of this fact. Considering that there are many parameters that alter the bilayer-substrate interaction, a diverse approach can be proposed. For example, Nissen et al. investigated the spreading dynamics on the substrate coated with polymetic materials [48]. They found that insertion of a hydrophilic and inert polymer layer under the self-spreading lipid bilayer strongly attenuated the bilayer-substrate interaction. 

Wellstead, P.E. and M. B. Zarrop, Self-Tuning Systems Control and Signal Processing, J. Wiley, New York, NY, 1991. 

Krstic, M., A. Knipadanam, and C. Jacobson. 1999. Self-tuning control of a nonlinear model of combustion instabilities. IEEE Plans, on Control Systems Technology 7 424-36. 

The architecture of the self-tuning regulator is shown in Fig. 7.99. It is similar to that of the Model Reference Adaptive Controller in that it also consists basically of two loops. The inner loop contains the process and a normal linear feedback controller. The outer loop is used to adjust the parameters of the feedback controller and comprises a recursive parameter estimator and an adjustment mechanism. 

Other self-tuning controllers have been designed which overcome these difficulties, e.g. the Generalised Minimum Variance self-tuning controller (GMV)m and the Generalised Predictive Controller (GPC)m. 

Supervisory control and data acquisition Solid-state relay Self-tuning regulator Temperature recorder controller Transistor-transistor logic Zero order hold element... 

Figure 23. Block diagram of self-tuning control loop for downstream reactors...

F. Cameron and D.E. Seborg. A self-tuning controller with a PID structure. International Journal of Control, 38 401, 1983. 

E. Katende and A. Jutan. A new constrained self-tuning PID controller. The Canadian Journal of Chemical Engineering, 71 625-633, 1993. 

P. Vega, P. Prada, and V. Aleixandre. Self-tuning predictive PID controller. In Proceeding of Inst. Electrical Engineering, pages 303-308, 1991. 

When the process changes cannot be measured or predicted, the adaptive control strategy must be implemented in a feedback manner. Many such controllers are referred to as self-tuning controllers, or self-adaptive controllers, and a typical block diagram is shown in Figure 13. 

Borisson, U. and Wittenmark, B., "An Industrial Application of a Self-Tuning Regulator," 4th IFAC Conference on Digital Computer Applications to Process Control, Zurich, Switzerland, 1974. 

Even starting off with poor initial controller parameter values, the self-tuning algorithm usually converges quite rapidly to a stable controller. After a certain amount of data has been collected one can test whether or not the assumed controller form is optimal (in the sense of the minimum variance) and then change it if necessary. 

Wittenmark, B. "A Self-Tuning Regulator", 1973, Technical Report 7311, Division of Automatic Control, Lund, Inst, of Tech., Lund, Sweden. 

There are many heat choices available and a wide choice of temperature controls as there is with other fabricating processes. They range from simple mechanical thermostats to solid state units with PID control, to microprocessors that are proportional, programmable, and self-tuning (Chapter 3). 

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