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Tuesday, October 14, 2014

Control Logic

HVAC control systems are the central nervous system of the machine world. The most efficient, well-selected and installed mechanical equipment can be reduced to a problem-riddled, inefficient mechanical nightmare by a poor control system design
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1. Background

2. Acronyms/Definitions
3. Control Logic Process
4. Benefits
5. Risks/Issues
6. Success Criteria
7. Case Studies
8. Companies
9. Links

1.Background
  • The fundamental goal of a control system is to automatically adjust a piece of machinery to give us what we want by comparing what is going on to what we want to go on and making appropriate adjustments to the process we want to control

2. Acronyms/Definitions
  1. Actuation System - xxx

  2. Cascade: A control system with 2 or more controllers, a "Master" and "Slave" loop. The output of the "Master" controller is the setpoint for the "Slave" controller

  3. Closed Loop Feedback -

  4. Control Point - xxx

  5. Controlled Variable - aka Final Controlled Variable - The device to be controlled

  6. Controller - xxx

  7. Dead Time: The amount of time it takes for a process to start changing after a disturbance in the system.

  8. Device Tracking Control System - Operation based on the operating pattern of another device< /li>
  9. Error - In process controls, error is defined as: Error = setpoint - process variable.


  10. Floating Control - Does nothing if the control point is between two limits


  11. Mathematical Control System - Operation based on mathematical relationship driven by other process parameters


  12. PID Controller -  Proportional-Integral-Derivative controller -   A PID controller calculates an error value as the difference between a measured process variable and a desired setpoint. The controller attempts to minimize the error by adjusting the process through use of a manipulated variable.

    The PID controller algorithm involves three separate constant parameters, and is accordingly sometimes called three-term control: the proportional, the integral andderivative values, denoted P, I, and D. Simply put, these values can be interpreted in terms of time: P depends on thepresent error, I on the accumulation of past errors, and D is a prediction of future errors, based on current rate of change.  The weighted sum of these three actions is used to adjust the process via a control element such as the position of a control valve, a damper, or the power supplied to a heating element.

    PID controllers are designed to eliminate the need for continuous operator attention. They are used to automatically adjust system variables to hold a process variable at a setpoint. Error is defined above as the difference between setpoint and process variable.


    1. Proportional Control System - The "P" part of a PID controller. With proportional action the controller output is proportional to the amount of the error signal. By its nature, a proportional control system will always have a difference or “error” between the set point and the control point except at one specific condition. We could reduce the error by increasing the gain of the controller (making it more sensitive to a level change in this case)  … but at some point, feedback from the process would interact with the control loop in a way that would make it unstable

    2. Integral Control: The "I" part of a PID controller. With integral action the controller output is proportional to the amount and duration of the error signal.  By monitoring the error over time, the operator could adjust the float setting so that it always maintained the desired set point.   This is what the Integral function in a Proportional plus Integral plus Derivative control loop does

    3. Derivative Control: The "D" part of a PID controller. With derivative action the controller output is proportional to the rate of change of the process variable or error.  Similarly, the operator could monitor the process and if he or she saw the error start to rapidly change relative to time, they could quickly push the float up or down to minimize the deviation from set point.  Once the sudden change is over the operator could reset the float to match the current load condition and maintain the required set point.   This is what the Derivative function in a Proportional plus Integral plus Derivative Set Point control loop does

    4. PI and PID -  Similar to proportional but with compensation for error.

  13. Pneumatic Actuator - Converts energy (typically in the form of compressed air) into mechanical motion. The motion can be rotary or linear, depending on the type of actuator.


  14. Process Variable - The current status of a process under control. An example of this would be the temperature of a furnace. The current temperature is called the process variable, while the desired temperature is known as the set-point.

  15. Proportional Band - the change in the process variable that causes the controlled variable to go through its full range. Proportional negative-feedback systems are based on the difference between the required set point (SP) and process value (PV). This difference is called the error. Power is applied in direct proportion to the current measured error, in the correct sense so as to tend to reduce the error (and so avoid positive feedback). The amount of corrective action that is applied for a given error is set by the gain or sensitivity of the control system.

    At low gains, only a small corrective action is applied when errors are detected: the system may be safe and stable, but may be sluggish in response to changing conditions; errors will remain uncorrected for relatively long periods of time: it is over-damped. If the proportional gain is increased, such systems become more responsive and errors are dealt with more quickly. There is an optimal value for the gain setting when the overall system is said to be critically damped. Increases in loop gain beyond this point will lead to oscillations in the PV; such a system is under-damped.


  16. Quarter Decay Ratio -  Open loop systems typically use the quarter decay ratio (QDR) for oscillation dampening. This means that the ratio of the amplitudes of the first overshoot to the second overshoot is 4:1.


  17. Response Testing 

    1. Forced Response
    2. Natural Response
  18. Sensor - A device that detects events or changes in quantities and provides a corresponding output, generally as an electrical or optical signal.  If the sensor is not ideal, several types of deviations can be observed:
    1. The sensitivity may in practice differ from the value specified. This is called a sensitivity error.
    2. Scale - Since the range of the output signal is always limited, the output signal will eventually reach a minimum or maximum when the measured property exceeds the limits. The full scale range defines the maximum and minimum values of the measured property.
    3. Bias. - aka offset - The output signal is not zero when the measured property is zero,   This is defined as the output of the sensor at zero input.
    4. Non Linearity - The sensitivity is not constant over the range of the sensor, . Usually this is defined by the amount the output differs from ideal behavior over the full range of the sensor, often noted as a percentage of the full range.
    5. Dynamic error - The deviation is caused by a rapid change of the measured property over time,  Often, this behavior is described with a bode plot showing sensitivity error and phase shift as function of the frequency of a periodic input signal.
    6. Drift  - The output signal slowly changes independent of the measured property,   .Long term drift usually indicates a slow degradation of sensor properties.
    7. Noise -  a random deviation of the signal that varies in time.
    8. Hysteresis  - An  error caused by when the measured property reverses direction, but there is some finite lag in time for the sensor to respond, creating a different offset error in one direction than in the other.
    9. Digitization error - If the sensor has a digital output, the output is essentially an approximation of the measured property. 
    10. Aliasing errors - If the signal is monitored digitally, limitation of the sampling frequency also can cause a dynamic error,  if the variable or added noise changes periodically at a frequency near a multiple of the sampling rate.
    11. External Error - The sensor may to some extent be sensitive to properties other than the property being measured. For example, most sensors are influenced by the temperature of their environment.

      All these deviations can be classified as systematic errors or random errors. Systematic errors can sometimes be compensated for with a calibration strategy. Noise is a random error that can be reduced by signal processing, such as filtering, usually at the expense of the dynamic behavior of the sensor.

  19. Setpoint - he desired or target value for an essential variable of a controlled process often used to describe a standard configuration or norm for the system. Departure of a variable from its setpoint is one basis for error-controlled regulation,that is, the use of feedback to return the system to its norm, as in homeostasis. For example, a boiler might have a temperature setpoint, which is the temperature the boiler control system aims to maintain.


  20. Schedule - Operation based on time of day


  21. Two position - Device is either “on” or “off”, “open” or “closed” etc.


3. Control Logic Process
  1. Identify the devices to be controlled  (a.k.a. the controlled variable)

  2. Identify the nature of their control signal ( Figure out what you have to do to control each device)

  3. Identify the process variable (Figure out what you need to monitor to let you control each devi ce) Measurables for process systems include:
    Temperature
    Pressure
    Flow rate
    pH
    Humidity
    Level
    Concentration
    Viscosity
    Conductivity
    Turbidity
    Redox/potential
    Electrical behavior
    Flammability

  4. Identify the controlled device to process variable relationship (Figure out how to make the process variable interact appropriately with the controlled variable)

  5. Identify the parameters associated with the relationship  (Figure out what other things (secondary control processes) impact the primary control process for each device)

  6. Identify the logic required to produce the desired parameters (Figure out how to monitor the secondary control processes and integrate them with the primary control process)

  7. Identify the conditions that constrain the process (Figure out if there are any limiting conditions that apply to the control process)

  8. Document the logic and/or write the sequence (Write it all down)

4. Benefits
  • Logic diagrams communicate control system sequence information

5. Risks/Issues
  • Control logic needs to address not only the requirements of the design day but also the requirements of all of the other days of the year

  • As long as the demand does not exceed the capacity of the delivery system (i.e. steady state can be achieved inside the proportional band) the system will be under control

  • Condensation - For example, humid air enters the water tight area via the conduit system.  Ambient temperatures drop below the dew point inside the housing.  Water condenses and accumulates inside the housing. Electrodes can’t tell the difference between water shorting them out at the bottom or at the top.

  • Gain - if the gain is too high, the oscillations become unstable and grow larger and larger with time.

  • Oversized valves are forced to try to control over a very limited portion of their span where small movements make big changes

  • Lag - Big duct can have 10 - 20 second delay between when fan starts and duct pressure comes up

  • Simultaneous Heating & Cooling - xx

  • Short Cycle Compressor - xx

  • Freezing Coils - xx

  • Blowing Things up - Too much pressure
  • Non-Linear Systems -A little change in the control can result in a big change in the system
6. Success Criteria
  1. Repeatable - To make, do, or perform (an action) again (and again, and again, and again ….)

  2. Reliable - Giving the same result on successive trials

  3. Robust - Sturdy; capable of performing without failure under a wide range of conditions

7. Case Studies
  • xxx
8. Companies
  1. Automated Logic ( part of UTC Building & Industrial Systems,
    a unit of United Technologies Corp)  Kennesaw, GA  - EIKON® is a graphical programming tool which eliminates line-by-line programming.. 
9. Links
  1. A Field Perspective on Engineering -  Buildings are talking to us .... we just need to learn to listen
    1. Resources for Understanding PID Control
    2. The Control Fundamentals chapter of the Honeywell Gray Manual, which will give you a good overview of control systems written in fairly understandable terms.

  2. Control Systems: Design, Performance, and Commissioning Issues - Simulcast Tue 10/14/2014 - Pacific Energy Center
  3. The Control Design Guide - Provides an overview of the control design and procurement process and some of the reasons things go wrong and a design approach that addresses those issues.

1 comment:

  1. It is really nice sharing. Thanks for the sharing and just keep up the good work.

    Gene Cage,
    Pnuematic Switches

    ReplyDelete