A toaster is set to 'medium' darkness and toasts bread for a fixed 90 seconds regardless of whether the bread comes out burnt or pale. This is an example of which type of control?

Closed-loop control Open-loop control PID control Cascade control

A robot joint is commanded to move to 90°. The encoder reads 87°. What is the current error, and in which direction should the controller drive the motor?

Error = −3°; the motor should drive the joint backwards toward 0° Error = +3°; the motor should drive the joint further in the positive direction to increase the angle toward 90° Error = 0°; the joint has already reached the setpoint Error = +87°; the motor must undo all previous movement

A proportional-only (P) controller is used to regulate the temperature of a chemical reactor at 80°C. After settling, the temperature stabilises at 77°C and never reaches the setpoint, even though the system is stable. What is this phenomenon called?

Integral windup Steady-state error (offset) Derivative kick Overshoot

An engineer increases Kp in a PID controller step by step. At first, the response gets faster and the overshoot increases. Eventually, the system output oscillates continuously without settling. What has happened?

The integral term has accumulated too much error (integral windup) The system has become unstable — Kp is too high, causing the feedback loop to overcorrect repeatedly, producing growing oscillations The derivative term is dampening the response so strongly that it oscillates The encoder has reached its maximum measurement frequency

A drone's altitude controller uses a PID loop. The pilot commands an abrupt step increase from 2 m to 10 m altitude. The derivative term momentarily produces a very large negative output spike when the setpoint changes. What is this phenomenon and how can it be prevented?

Integral windup — prevented by clamping the integral term to a maximum value Overshoot — prevented by reducing Kp to slow the response Derivative kick — caused by the instantaneous spike in error rate when the setpoint changes; it is prevented by applying the derivative only to the measured value, not the error Proportional saturation — prevented by increasing the sensor sampling rate

A PID controller for a robot arm joint includes an integral term. The arm is commanded to a position that is mechanically blocked (someone is holding it). After 30 seconds, the block is removed. The arm violently shoots past the setpoint. What caused this?

Derivative kick — the sudden motion caused a large derivative spike Integral windup — the integrator accumulated a very large value while the arm was blocked because the error persisted, then released all at once when the block was removed Overshoot from Kp being too large for the system inertia The encoder failed during the blocked period, causing a position mismatch

A cruise control system maintains a car at 100 km/h. The car climbs a hill, which is a disturbance. In a closed-loop system, how does the controller detect and respond to the hill before the speed drops significantly?

The controller uses a map to anticipate hills and pre-emptively increases throttle It cannot anticipate the hill in pure feedback control — it waits until speed drops below 100 km/h (error appears), then increases throttle to restore speed The derivative term senses the rate of speed decrease and corrects before the setpoint is reached The integral term corrects for the hill by predicting future error

A CNC machine tool uses cascade control: an outer position loop and an inner velocity loop. Why is this two-loop structure superior to a single position-only PID loop?

Cascade control eliminates the need for encoder feedback altogether The outer loop controls velocity and the inner loop controls acceleration for smoother motion The fast inner velocity loop rejects friction and load disturbances before they affect position, allowing the outer position loop to run at a slower rate with better overall accuracy Two loops are used because a single PID controller cannot handle angles and positions simultaneously

Feed-forward control is added to a robot arm's position PID. The feed-forward term uses a dynamic model to predict the motor torque required for the planned trajectory. What advantage does this provide over feedback-only control?

Feed-forward replaces the PID controller entirely, simplifying the control system The robot does not need to wait for a position error to develop before correcting — the predicted torque is applied proactively, reducing tracking error during motion Feed-forward eliminates the need for any sensors on the robot Feed-forward increases stability by adding extra damping to the feedback loop

Using the Ziegler-Nichols tuning method, an engineer slowly increases Kp until the closed-loop system oscillates continuously with a period Tu = 2 seconds at the critical gain Ku = 8. Using Ziegler-Nichols, what should the initial Kp setting be?

Kp = Ku = 8 Kp = 0.5 × Ku = 4.0 Kp = 0.6 × Ku = 4.8 Kp = Tu / Ku = 0.25

A temperature control system is designed to cool a server room. The cooling unit takes 5 minutes to reach full capacity after being switched on. How does this 'lag' affect the choice of derivative gain Kd?

High Kd makes the system unstable because slow systems cannot process derivative signals fast enough High Kd is beneficial because the slow system lag means errors accumulate gradually — derivative action anticipates the growing error and triggers corrective action earlier Kd should be set to zero for slow systems because derivative action has no effect on lag High Kd eliminates the need for an integral term in slow systems

Two engineers debate adding a derivative term to a flow-control PID loop measuring liquid flow with a noisy turbine flowmeter. Why is it often unwise to use a large Kd with a noisy sensor?

A large Kd causes the control loop to run slower, missing fast flow changes The derivative term amplifies high-frequency noise in the sensor signal, causing rapid, large actuator oscillations that wear out valves and destabilise the loop Kd causes the integral to wind up faster in noisy environments Derivative control only works in digital systems, not analogue flow loops