CCST Process Optimization & Performance Tuning Flashcards
6 cards from real CCST practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 CCST Process Optimization & Performance Tuning flashcards as text
What is the primary objective of PID loop tuning in a process control system?
Answer: Achieving stable, accurate control with minimal overshoot and acceptable settling time
PID loop tuning seeks a balance of stability, accuracy, and speed of response — minimizing overshoot, oscillation, and steady-state error.
In the Ziegler-Nichols closed-loop tuning method, what is the 'ultimate gain' (Ku)?
Answer: The proportional gain at which the control loop first begins to oscillate with constant amplitude
The ultimate gain (Ku) is the critical proportional gain at which the closed-loop system sustains steady oscillation — used as the basis for Ziegler-Nichols PID parameter calculations.
What process control issue is described when a control valve alternates between two positions rapidly due to excessive controller gain and stiction in the valve?
Answer: Cycling (limit cycling)
Limit cycling occurs when a sticky valve and high controller gain cause the output to switch back and forth, creating a sustained oscillation at a fixed amplitude.
Which tuning parameter in a PID controller is responsible for eliminating steady-state offset (error) between the process variable and setpoint?
Answer: Integral (I)
The integral term accumulates error over time and adjusts the output until the steady-state error is driven to zero.
What is 'integral windup' in a PID controller, and when does it typically occur?
Answer: Accumulation of the integral term to very large values when the controller output is saturated and cannot correct the error
Integral windup occurs when the controller output is saturated (e.g., valve fully open) but error persists, causing the integral term to accumulate excessively and produce large overshoot when the constraint is removed.
A process has a long dead time relative to its time constant. Which control strategy is most effective for improving performance in such a process?
Answer: Implementing a Smith Predictor or dead-time compensator
A Smith Predictor uses a process model to compensate for dead time, allowing the controller to respond as if the dead time were not present and significantly improving closed-loop performance.