Process controls parameter changes

The documents shall be verified, approved, and filed essential documents are the protocol, records for operation, in-process control parameters, change control document, specification test as quality control, and final report. 

The Smith predictor is a model-based control strategy that involves a more complicated block diagram than that for a conventional feedback controller, although a PID controller is still central to the control strategy (see Fig. 8-37). The key concept is based on better coordination of the timing of manipulated variable action. The loop configuration takes into account the facd that the current controlled variable measurement is not a result of the current manipulated variable action, but the value taken 0 time units earlier. Time-delay compensation can yield excellent performance however, if the process model parameters change (especially the time delay), the Smith predictor performance will deteriorate and is not recommended unless other precautions are taken. 

The choice of phosphate is inextricably linked to the FW alkalinity in order to control the precipitation process. A minimum BW hydroxide alkalinity (hydroxyl, OH, O, or P2 alkalinity) must be maintained. A maximum total alkalinity (M or T alkalinity), as well as a control range for phosphate (usually given as ppm or mg/1 P04) also must be maintained. These various control parameters change not only with the level of FW hardness, but also with boiler pressure. 

Adaptive Control. An adaptive control strategy is one in which the controller characteristics, ie, the algorithm or the control parameters within it, are automatically adjusted for changes in the dynamic characteristics of the process itself (34). The incentives for an adaptive control strategy generally arise from two factors common in many process plants (/) the process and portions thereof are really nonlinear and (2) the process state, environment, and equipment s performance all vary over time. Because of these factors, the process gain and process time constants vary with process conditions, eg, flow rates and temperatures, and over time. Often such variations do not cause an unacceptable problem. In some instances, however, these variations do cause deterioration in control performance, and the controllers need to be retuned for the different conditions. 

Adaptive Control Process control problems inevitably require on-hne tuning of the controller constants to achieve a satisfactory degree of control. If the process operating conditions or the environment changes significantly, the controller may have to be retuned. If these changes occur quite frequently, then adaptive control techniques should be considered. An adaptive control system is one in which the controller parameters are adjusted automatically to compensate for changing process conditions. 

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... 

In petrochemical and bulk commodity chemical manufacture, real-time process control has been a fact of life for many years. There is considerable understanding of processes and control of process parameters is usually maintained within tight specifications to ensure statistical process control to within six sigma, or the occurrence of one defect in a million. This has been enabled through the use of real-time analytical capability that works with programmable logic circuits to make small changes to various process inputs and physical parameters as required. 

An adaptive control system can automatically modify its behaviour according to the changes in the system dynamics and disturbances. They are applied especially to systems with non-linear and unsteady characteristics. There are a number of actual adaptive control systems. Programmed or scheduled adaptive control uses an auxiliary measured variable to identify different process phases for which the control parameters can be either programmed or scheduled. The "best" values of these parameters for each process state must be known a priori. Sometimes adaptive controllers are used to optimise two or more process outputs, by measuring the outputs and fitting the data with empirical functions. 

The equality is valid if the control parameter is changed reversibly, i.e., if the system is in equilibrium at all times during the transformation. Equivalently, this result can be stated as the maximum work theorem [34] the amount of work delivered by a system during a transformation from a specific initial to a specific final state is always smaller than the free energy difference between the initial and final states. The work is maximum and equal to the free energy difference for a reversible process, hence the term reversible work for the equilibrium free energy. 

Displacement sensors are used in a very wide field of applications in research, development, quality inspection, automation, machinery and process control. Many physical parameters can be reduced to a displacement or change of distance, and can be measured with highest precision. Displacement sensors detect physical parameters like bending, deflection, deformation, diameter, eccentricity, elongation, gap, length, play, position, revolution, roundness, shift, stroke, thickness, tilt, tolerances, vibration, wear and width. 

The input for most chemical processes is normally constrained, (e.g., a valve ranges between 0 and 100 percent open). An unconstrained minimum variance controller might not be able to achieve the desired input trajectory for the response. The controller design should take the process input constraints into account. The results of a simulated setpoint change for such a controller with bounds of —40 and 40 for the input and controller parameters w = 1 and A = 0 is given by the dashed line in Figure El6.3. 

Production control data set boundaries and parameters for production operations of resources, processes, output and input products, process groups and change-overs. 

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