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Control tuning

The dynamics of the secondary control loop should be approximately two to four times as fast as the dynamics of the primary control loop in order to achieve stable control. The secondary controller is actually part of the primary controller s process system. Hence, changes in the secondary controller tuning constants change the process system of the primary controller. Therefore, cascade control loops should always be tuned by first tuning the secondary controller and then the primary controller. If the secondary controller tuning is changed for any reason, the primary controller may need to be retuned also. [Pg.70]

The performance of a controller depends as much on its tuning as its design. Tuning must be apphed by the end user to fit the controller to the controlled process. Tnere are many different approaches to controller tuning based on the particular performance criteria selected. [Pg.727]

Basic process control system (BPCS) loops are needed to control operating parameters like reactor temperature and pressure. This involves monitoring and manipulation of process variables. The batch process, however, is discontinuous. This adds a new dimension to batch control because of frequent start-ups and shutdowns. During these transient states, control-tuning parameters such as controller gain may have to be adjusted for optimum dynamic response. [Pg.111]

Fig. 4.35 Closed-loop step response of temperature control system using PID controller tuned using Zeigler-Nichols process reaction method. Fig. 4.35 Closed-loop step response of temperature control system using PID controller tuned using Zeigler-Nichols process reaction method.
Adequate PC and its associated instrumentation are essential for product quality control. The goal in some cases is precise adherence to a single control point. In other cases, maintaining the temperature within a comparatively small range is all that is necessary. For effortless controller tuning and the lowest initial cost, the processor should select the simplest controller (of temperature, time, pressure, melt-flow, rate, etc.) that will produce the desired results. [Pg.531]

Anodic shipping voltammetry (ASV) is the most widely used form of stripping analysis, hi this case, the metals are preconcenhated by elechodeposition into a small-volume mercury electrode (a tiiin mercury film or a hanging mercury drop). The preconcenhation is done by catiiodic deposition at a controlled tune and potential. The deposition potential is usually 0.3-0.5 V more negative than E° for the least easily reduced metal ion to be determined. The metal ions reach die mercury electrode by diffusion and convection, where diey are reduced and concentrated as amalgams ... [Pg.76]

One should note the use of engineering units in the controller tuning parameters. The units become important when one must compare different controllers tuning parameters using different units for the PID calculation. [Pg.494]

The cost functional is the indicator of how well the control loop is functioning. The lAE criterion used essentially says "measure the cumulative difference between the actual value and the desired set point" this cumulative score is a measure of control system performance. With this code in the model, the commands to do the controller tuning are ... [Pg.500]

The purpose of controller tuning is to choose the correct controller constants to obtain the desired performance characteristics. This usually means that the control variables should be restored in an optimal way to acceptable values, following either a change in the set point or the appearance of an input disturbance. Simulation examples TEMPCONT and CONTUN, provide exercises for controller tuning using the methods explained below. [Pg.101]

Figure 5.164. Tank temperature versus time for two values of Kc (1.5 and 2.0), with XI = 10000. The changes at T=10 and T=20 are programmed step changes in the inlet water flow rate. Oscillations and offset are caused by sub-optimal controller tuning. Figure 5.164. Tank temperature versus time for two values of Kc (1.5 and 2.0), with XI = 10000. The changes at T=10 and T=20 are programmed step changes in the inlet water flow rate. Oscillations and offset are caused by sub-optimal controller tuning.
Trial and error method controller tuning 101 Tube 623... [Pg.700]

With higher order models, we can construct approximate reduced-order models based on the identification of dominant poles. This approach is used later in empirical controller tuning relations. [Pg.45]

At this point, one may be sufficiently confused with respect to all the different controller tuning methods. Use Table 6.3 as a guide to review and compare different techniques this chapter and also Chapters 7 and 8. [Pg.120]

This process also lasts several minutes, which makes it globally a very penalizing step and relatively complex to implement from an engine control/tuning point of view. [Pg.226]

How could one control/tune electron transport through single molecules ... [Pg.123]

Continuous Binary Distillation Column 496 Controller Tuning Problem 427 Three-Stage Reactor Cascade with Countercurrent Cooling 287... [Pg.606]

Then in Chaps. 7 and 8 we will look at closedloop systems. Instrumentation hardware, controller types and performance, controller tuning, and various types of control systems structures will be discussed. [Pg.166]

In this chapter we will study control equipment, controller performance, controller tuning, and general control-systems design concepts. Some of the questions that wc will explore are how do we decide what kind of control valve to use what type of sensor can be used and what are some of the pitfalls that you should be aware of that can give faulty signals what type of controller should we select for a given application and how do we tune the controller. [Pg.205]

There are a variety of feedback controller tuning methods. Probably 80 percent of all loops are tuned experimentally by an instrument mechanic, and 75 percent of the time the mechanic can guess approximately what the settings will be by drawing on experience with similar loops. We will discuss a few of the time-domain methods below. In subsequent chapters we will present other techniques for tinding controller constants in the Laplace and frequency domains. [Pg.231]

Therefore, the pairing of Xj, with V and Xg with R gives a closedloop system that is integrally unstable for any controller tuning. [Pg.573]

This selection of control structure is independent of variable pairing and controller tuning. The MRI is a measure of the inherent ability of the process (with the specified choice of manipulated variables) to handle disturbances, changes in operating conditions, etc. [Pg.598]


See other pages where Control tuning is mentioned: [Pg.715]    [Pg.717]    [Pg.727]    [Pg.790]    [Pg.368]    [Pg.46]    [Pg.496]    [Pg.101]    [Pg.514]    [Pg.700]    [Pg.701]    [Pg.180]    [Pg.159]    [Pg.73]    [Pg.73]    [Pg.427]    [Pg.632]    [Pg.71]    [Pg.231]    [Pg.231]    [Pg.237]    [Pg.368]   
See also in sourсe #XX -- [ Pg.107 ]




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Based Pi-Controller Tuning

CONTUN - Controller Tuning Problem

Closed-Loop Tuning of Controllers

Computer-controlled tuning

Controlled Wavelength Tuning

Controlled Wavelength Tuning of Single-Mode Lasers

Controller Tuning Guidelines

Controller Tuning and Disturbances

Controller tuning

Controller tuning definitions

Controller tuning for capacity and dead time processes

Controller tuning problem

Controllers self-tuning

Feedback controllers tuning

Flow control tuning

Flow controller tuning

Heat integration controller tuning

Internal Model Control (IMC) Tuning Rules

Level control tuning

Model predictive control tuning parameters

Multi-loop controller tuning

Optimal Design and Practical Considerations of Tuned Mass Dampers for Structural Control

PID Controller Tuning

Particle size control tuning

Pre-Tuned Temperature Controllers

Process control scheduling controller tuning

Quarter Decay Ratio Tuning of Control Loops

Running the Simulation and Tuning Controllers

Self-tuning control

Self-tuning temperature controllers

The Ziegler-Nichols methods for tuning PID controllers

Trial-and-Error Tuning of Control Loops

Tuning

Tuning Rules for PID Controllers

Tuning discrete time controllers

Tuning of PID Controllers

Tuning of the Controller Parameters

Tuning the Control Loop

Tuning the controller

Tuning the controllers for multi-loop systems

Ultimate Gain Tuning of Control Loops

Ultimate controller tuning

Ziegler controller tuning

Ziegler-Nichols controller tuning paramete

Ziegler-Nichols method controller tuning

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