Advanced Control Techniques Dr. U. D Dwivedi (Assistant Professor) Rajiv Gandhi Institute of Petroleum Technology, Raeb
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Advanced Control Techniques
Dr. U. D Dwivedi (Assistant Professor) Rajiv Gandhi Institute of Petroleum Technology, Raebareli
Instrument Abbreviations • • • • • • • • • • • • • • •
AT Analyzer (Composition) Transmitter FT Flow Transmitter LT Level Transmitter PT Pressure Transmitter TT Temperature Transmitter FC Flow Controller LC Level Controller TC Temperature Controller PC Pressure Controller LL Liquid Level LI Level Indicator TI Temperature Indicator PV Pressure Valve PI Pressure Indicator I/P Current to Pressure transducer
Chapter 15
Feedforward and Ratio Control
Chapter 15
Chapter 15
Chapter 15
Chapter 15
Introduction : Feedforward Control
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Control Objective: Maintain Y at its set point, Ysp, despite disturbances.
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Feedback Control: • Measure Y, compare it to Ysp, adjust U so as to maintain Y at Ysp. • Widely used (e.g., PID controllers) • Feedback is a fundamental concept
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Feedforward Control: • Measure D, adjust U so as to maintain Y at Ysp. • Note that the controlled variable Y is not measured.
Chapter 15
Comparison of Feedback and Feedforward Control
Chapter 15
1) Feedback (FB) Control Advantages: •Corrective action occurs regardless of the source and type of disturbances. •Requires little knowledge about the process (For example, a process model is not necessary). •Versatile and robust (Conditions change? May have to re-tune controller). Disadvantages: •FB control takes no corrective action until a deviation in the controlled variable occurs. •FB control is incapable of correcting a deviation from set point at the time of its detection. •Theoretically not capable of achieving “perfect control.” •For frequent and severe disturbances, process may not settle out.
Chapter 15
2) Feedforward (FF) Control Advantages: •Takes corrective action before the process is upset (cf. FB control.) •Theoretically capable of "perfect control" •Does not affect system stability Disadvantages: •Disturbance must be measured (capital, operating costs) •Requires more knowledge of the process to be controlled (process model) •Ideal controllers that result in "perfect control”: may be physically unrealizable. Use practical controllers such as lead-lag units 3) Feedforward Plus Feedback Control FF Control •Attempts to eliminate the effects of measurable disturbances. FB Control •Corrects for unmeasurable disturbances, modeling errors, etc. (FB trim)
4) Historical Perspective : •1925: 3 element boiler level control •1960's: FF control applied to other processes
Chapter 15
EXAMPLE : Heat Exchanger
w = Liquid flow rate w s = Steam flow rate T1 = Inlet liquid temperature T2 = Exit liquid temperature
Chapter 15
•Control Objective: Maintain T2 at the desired value (or set-point), Tsp, despite variations in the inlet flow rate, w. Do this by manipulating ws. •Feedback Control Scheme: Measure T2, compare T2 to Tsp, adjust ws. •Feedforward Control Scheme: Measure w, adjust ws (knowing Tsp), to control exit temperature,T2.
Chapter 15
Feedback Control
Feedforward Control
Chapter 15
Feedforward/Feedback Control of a Heat Exchanger
Chapter 15
Chapter 15
Ratio Control Objective: maintain the ratio of two process variables at a specified value
where, u and d are physical variables, Used in mixing systems where an uncontrolled flow of material (wild flow) is monitored and used to control the second material which is controlled according to the desired ratio between the two components.
Chapter 15 Method I
Chapter 15 Method II
Chapter 15
Cascade Control • A cascade control system is a multiple-loop system. Desirable when Single-loop performance unacceptable and a measured variable is available.
• Cascade control systems use a second feedback loop with a separate sensor and controller. – Cascade reduces the effect of specific types of disturbances. – objective in cascade control is to divide a difficult process control into two portions – a secondary control loop is formed around a major disturbances – thus leaving only minor disturbances to be controlled by the primary controller
• Better control of the primary variable • Primary variable less affected by disturbances • Faster recovery from disturbances
Chapter 16
Cascade Control (multi-loop):
Chapter 16
Cascade Control (multi-loop):
Analysis of Cascade Example • Without a cascade controller, changes in the pressure of fuel gas supply will disturb the hot oil temperature. Sluggish response • With cascade controller, changes in gas pressure will be corrected by the pressure controller (PC) before it can significantly affect hot oil temperature because the PC responds faster to this disturbance than TC (the primary controller).
Cascade Control (multi-loop)
Chapter 16
•
Distinguishing features:
1. Two FB controllers but only a single control valve (or other -final control element). 2. Output signal of the "master" controller is the setpoint for “slave" controller. 3. Two FB control loops are "nested" with the "slave" (or "secondary") control loop inside the "master" (or "primary") control loop. •
Terminology
slave vs. master secondary vs. primary inner vs. outer
SELECTIVE CONTROL SYSTEMS (Overrides) For every controlled variable, there must be at least one manipulated variable.
Chapter 16
In some applications
# of controlled variables •Low selector:
•High selector:
NC ≠ NM # of manipulated variables
Chapter 16
multiple measurements one controller one final control element
Inferential Control
Chapter 16
• Problem: Controlled variable cannot be measured or has large sampling period. • Possible solutions: 1. Control a related variable (e.g., temperature instead of composition). 2. Inferential control: Control is based on an estimate of the controlled variable. • The estimate is based on available measurements. –
Examples: empirical relation, Kalman filter, Artificial Intelligence (AI), Neural Network
• Modern term: soft sensor
Chapter 16
Adaptive Control
Chapter 16
• A general control strategy for control problems where the process or operating conditions can change significantly and unpredictably. Example: Catalyst decay, equipment fouling
• Many different types of adaptive control strategies have been proposed. • Self-Tuning Control (STC): – A very well-known strategy and probably the most widely used adaptive control strategy. – Basic idea: STC is a model-based approach. As process conditions change, update the model parameters by using least squares estimation and recent u & y data.
• Note: For predictable or measurable changes, use gain scheduling instead of adaptive control Reason: Gain scheduling is much easier to implement and less trouble prone.
Chapter 16
Chapter 16
Time Delay Compensation •
Model-based feedback controller that improves closed-loop performance when time delays are present
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Effect of added time delay on PI controller performance for a second order process (τ1 = 3, τ2 = 5) shown below
Chapter 16
Chapter 16
* −θ s No model error: = G G= e G *e −θ s
GC′
GC GC′ G Y = Ysp 1 + GC′ G 1 + GC G* 1 − e −θ s
(
)
GC G*e −θ s GC G Y = = Ysp 1 + GC G* 1 + GC G*
(16 − 22)
(sensitive to model errors > +/- 20%)
Chapter 16
Chapter 16
Chapter 16
Chapter 16
Chapter 16
Chapter 16
Chapter 16
Gain Scheduling
Chapter 16
• Objective: Make the closed-loop system as linear as possible. • Basic Idea: Adjust the controller gain based on current measurements of a “scheduling variable”, e.g., u, y, or some other variable.
• Note: Requires knowledge about how the process gain changes with this measured variable.