Honeywell AUTOMATIC CONTROL, Engineering Manual

Page: 36 / 518

ENGINEERING MANUAL OF AUTOMATIC CONTROL
CONTROL FUNDAMENTALS
26
The start value EPID setpoint sets the output to a fixed value
at startup. For a VAV air handling system supply fan, a suitable
value might be twenty percent, a value high enough to get the
fan moving to prove operation to any monitoring system and
to allow the motor to self cool. For a heating, cooling, and
ventilating air handling unit sequence, a suitable start value
would be thirty-three percent, the point at which the heating,
ventilating (economizer), and mechanical cooling demands are
all zero. Additional information is available in the Air Handling
System Control Applications section.
The error ramp time determines the time duration during
which the PID error (setpoint minus input) is slowly ramped,
linear to the ramp time, into the PID controller. The controller
thus arrives at setpoint in a tangential manner without
overshoot, undershoot, or cycling. See Figure 41.
Adaptive control is also used in energy management
programs such as optimum start. The optimum start program
enables an HVAC system to start as late as possible in the
morning and still reach the comfort range by the time the
building is occupied for the lease energy cost. To determine
the amount of time required to heat or cool the building, the
optimum start program uses factors based on previous building
response, HVAC system characteristics, and current weather
conditions. The algorithm monitors controller performance by
comparing the actual and calculated time required to bring the
building into the comfort range and tries to improve this
performance by calculating new factors.
PROCESS CHARACTERISTICS
As pumps and fans distribute the control agent throughout
the building, an HVAC system exhibits several characteristics
that must be understood in order to apply the proper control
mode to a particular building system.
LOAD
Process load is the condition that determines the amount of
control agent the process requires to maintain the controlled
variable at the desired level. Any change in load requires a
change in the amount of control agent to maintain the same
level of the controlled variable.
Load changes or disturbances are changes to the controlled
variable caused by altered conditions in the process or its
surroundings. The size, rate, frequency, and duration of
disturbances change the balance between input and output.
Four major types of disturbances can affect the quality of
control:
— Supply disturbances
— Demand disturbances
— Setpoint changes
— Ambient (environmental) variable changes
Supply disturbances are changes in the manipulated variable
input into the process to control the controlled variable. An
example of a supply disturbance would be a decrease in the
temperature of hot water being supplied to a heating coil. More
flow is required to maintain the temperature of the air leaving
the coil.
Demand disturbances are changes in the controlled medium
that require changes in the demand for the control agent. In
the case of a steam-to-water converter, the hot water supply
temperature is the controlled variable and the water is the
controlled medium (Fig. 42). Changes in the flow or
temperature of the water returning to the converter indicate a
demand load change. An increased flow of water requires an
increase in the flow of the control agent (steam) to maintain
the water temperature. An increase in the returning water
temperature, however, requires a decrease in steam to maintain
the supply water temperature.
SETPOINT
T1 T2 T3 T4 T5 T6
M13038
ELAPSED TIME
OFFSET
T7 T8
CONTROL
POINT
0
100
START
VALUE
ERROR
RAMP
TIME
ACTUATOR POSITION
PERCENT OPEN
Fig. 41. Enhanced Proportional-Integral-Derivative
(EPID) Control.
ADAPTIVE CONTROL
Adaptive control is available in some microprocessor-based
controllers. Adaptive control algorithms enable a controller to
adjust its response for optimum control under all load
conditions. A controller that has been tuned to control
accurately under one set of conditions cannot always respond
well when the conditions change, such as a significant load
change or changeover from heating to cooling or a change in
the velocity of a controlled medium.
An adaptive control algorithm monitors the performance of
a system and attempts to improve the performance by adjusting
controller gains or parameters. One measurement of
performance is the amount of time the system requires to react
to a disturbance: usually the shorter the time, the better the
performance. The methods used to modify the gains or
parameters are determined by the type of adaptive algorithm.
Neural networks are used in some adaptive algorithms.
An example of a good application of adaptive control is
discharge temperature control of the central system cooling
coil for a VAV system. The time constant of a sensor varies as
a function of the velocity of the air (or other fluid). Thus the
time constant of the discharge air sensor in a VAV system is
constantly changing. The change in sensor response affects
the system control so the adaptive control algorithm adjusts
system parameters such as the reset and rate settings to maintain
optimum system performance.