1. Model Predictive Control (MPC) is based on:
A) Predicting future system behavior and optimizing control actions
B) Fixed gain feedback control
C) Frequency response analysis
D) State-space representation
Answer: A) Predicting future system behavior and optimizing control actions
2. In MPC, the prediction model is used to:
A) Forecast the future behavior of the system
B) Design state observers
C) Analyze frequency response
D) Implement PID control
Answer: A) Forecast the future behavior of the system
3. The primary objective of MPC is to:
A) Minimize a cost function over a finite prediction horizon
B) Design fixed controllers
C) Analyze the system’s stability
D) Implement adaptive control
Answer: A) Minimize a cost function over a finite prediction horizon
4. In MPC, the “cost function” typically includes:
A) A term for tracking error and a term for control effort
B) Only tracking error
C) Only control effort
D) System frequency response
Answer: A) A term for tracking error and a term for control effort
5. The “horizon” in Model Predictive Control refers to:
A) The future time period over which predictions are made and optimization is performed
B) The time period over which the system is observed
C) The time needed to solve the optimization problem
D) The time interval between control actions
Answer: A) The future time period over which predictions are made and optimization is performed
6. “Constraint handling” in MPC refers to:
A) Managing system constraints like input and state limits within the optimization process
B) Designing controllers for specific conditions
C) Analyzing the system’s poles and zeros
D) Implementing frequency response analysis
Answer: A) Managing system constraints like input and state limits within the optimization process
7. The “state-space model” used in MPC is used to:
A) Predict future system states based on current states and inputs
B) Design fixed controllers
C) Analyze system stability
D) Implement PID control
Answer: A) Predict future system states based on current states and inputs
8. “Open-loop MPC” refers to:
A) MPC where the control actions are calculated without feedback correction
B) MPC with feedback correction
C) MPC with adaptive parameters
D) MPC using a linear model
Answer: A) MPC where the control actions are calculated without feedback correction
9. “Closed-loop MPC” involves:
A) Using feedback to update the control actions based on actual system performance
B) Designing fixed controllers
C) Analyzing frequency response
D) Implementing state-space models
Answer: A) Using feedback to update the control actions based on actual system performance
10. The “control horizon” in MPC refers to:
A) The time period over which the control actions are optimized
B) The future time period for predictions
C) The time period for observing system performance
D) The duration of the optimization problem
Answer: A) The time period over which the control actions are optimized
11. The term “receding horizon” in MPC means:
A) The optimization is performed repeatedly with the horizon moving forward in time
B) The horizon remains fixed throughout the control process
C) The system’s response is evaluated at a fixed time
D) The optimization is performed only once
Answer: A) The optimization is performed repeatedly with the horizon moving forward in time
12. In MPC, the “prediction model” can be:
A) Linear or nonlinear depending on the system’s dynamics
B) Only linear
C) Only nonlinear
D) Fixed and not dependent on the system’s dynamics
Answer: A) Linear or nonlinear depending on the system’s dynamics
13. “Reference Tracking” in MPC aims to:
A) Minimize the deviation of the system output from a desired reference
B) Design fixed controllers
C) Analyze the system’s stability
D) Implement PID control
Answer: A) Minimize the deviation of the system output from a desired reference
14. “Input Constraints” in MPC are:
A) Limits on the control inputs to the system
B) Limits on the system outputs
C) Limits on the state variables
D) Design parameters of the model
Answer: A) Limits on the control inputs to the system
15. “State Constraints” in MPC refer to:
A) Limits on the state variables of the system
B) Limits on the control inputs
C) Limits on the system outputs
D) Design parameters of the model
Answer: A) Limits on the state variables of the system
16. “Performance Index” in MPC is used to:
A) Evaluate the overall performance of the control strategy based on the cost function
B) Analyze system poles and zeros
C) Implement frequency response analysis
D) Design fixed controllers
Answer: A) Evaluate the overall performance of the control strategy based on the cost function
17. “Disturbance Rejection” in MPC involves:
A) Designing the controller to handle and mitigate the effects of external disturbances
B) Analyzing the system’s frequency response
C) Implementing state feedback
D) Designing fixed gain controllers
Answer: A) Designing the controller to handle and mitigate the effects of external disturbances
18. The “prediction horizon” is typically:
A) Longer than the control horizon
B) Shorter than the control horizon
C) Equal to the control horizon
D) Unrelated to the control horizon
Answer: A) Longer than the control horizon
19. “MPC with Robustness” involves:
A) Designing the controller to perform well despite model inaccuracies and uncertainties
B) Designing controllers for specific known conditions
C) Analyzing system stability
D) Implementing PID control
Answer: A) Designing the controller to perform well despite model inaccuracies and uncertainties
20. “Linear MPC” is used when:
A) The system can be accurately modeled with linear dynamics
B) The system exhibits strong nonlinear behavior
C) The model includes significant uncertainties
D) The control actions are not optimized
Answer: A) The system can be accurately modeled with linear dynamics
21. “Nonlinear MPC” is applied when:
A) The system’s dynamics are nonlinear and cannot be accurately represented by a linear model
B) The system is linear
C) The model is fixed and does not change
D) The control actions are not optimized
Answer: A) The system’s dynamics are nonlinear and cannot be accurately represented by a linear model
22. The “computational burden” in MPC refers to:
A) The amount of computational resources required to solve the optimization problem
B) The physical load on the system
C) The number of constraints
D) The accuracy of the model
Answer: A) The amount of computational resources required to solve the optimization problem
23. In “Explicit MPC,” the control law is:
A) Precomputed offline and implemented online based on the current state
B) Computed in real-time
C) Based on adaptive control
D) Implemented using frequency response
Answer: A) Precomputed offline and implemented online based on the current state
24. “Stochastic MPC” deals with:
A) Systems where uncertainty is modeled as stochastic processes
B) Fixed gain controllers
C) Linear time-invariant systems
D) Deterministic systems
Answer: A) Systems where uncertainty is modeled as stochastic processes
25. “Economic MPC” focuses on:
A) Optimizing the economic performance of the system by minimizing a cost function related to economic criteria
B) Designing fixed controllers
C) Analyzing frequency response
D) Implementing PID control
Answer: A) Optimizing the economic performance of the system by minimizing a cost function related to economic criteria
26. “MPC in Discrete-Time” involves:
A) Applying MPC to systems sampled at discrete intervals
B) Designing continuous-time controllers
C) Implementing fixed controllers
D) Analyzing frequency response
Answer: A) Applying MPC to systems sampled at discrete intervals
27. The “constraint handling” in MPC is essential for:
A) Ensuring that control inputs and state variables stay within physically feasible limits
B) Designing fixed gain controllers
C) Analyzing system stability
D) Implementing adaptive control
Answer: A) Ensuring that control inputs and state variables stay within physically feasible limits
28. “Multi-Objective MPC” involves:
A) Optimizing multiple performance criteria simultaneously
B) Designing single-objective controllers
C) Analyzing system stability
D) Implementing fixed gain controllers
Answer: A) Optimizing multiple performance criteria simultaneously
29. In “MPC with Constraints,” the optimization problem includes:
A) Constraints on control inputs, state variables, and outputs
B) Only constraints on state variables
C) Only constraints on control inputs
D) No constraints
Answer: A) Constraints on control inputs, state variables, and outputs
30. “Robust MPC” aims to:
A) Ensure that the control performance is maintained despite model uncertainties and external disturbances
B) Design controllers for specific known conditions
C) Analyze the system’s frequency response
D) Implement fixed gain controllers
Answer: A) Ensure that the control performance is maintained despite model uncertainties and external disturbances
31. “Adaptive MPC” adjusts:
A) The control model and parameters in real-time based on observed system behavior
B) The physical structure of the system
C) The input constraints
D) The system’s frequency response
Answer: A) The control model and parameters in real-time based on observed system behavior
32. The “terminal cost” in MPC refers to:
A) The cost function evaluated at the end of the prediction horizon
B) The initial cost of the system
C) The cost related to system outputs
D) The cost of control inputs
Answer: A) The cost function evaluated at the end of the prediction horizon
33. “MPC for Linear Time-Invariant (LTI) Systems” assumes:
A) The system dynamics do not change over time
B) The system dynamics vary with time
C) The system has nonlinear characteristics
D) The system exhibits chaotic behavior
Answer: A) The system dynamics do not change over time
34. “Output Constraints” in MPC are:
A) Limits imposed on the system outputs to ensure safe operation
B) Limits on control inputs
C) Limits on state variables
D) Design parameters of the model
Answer: A) Limits imposed on the system outputs to ensure safe operation
35. “Feasibility” in the context of MPC means:
A) The existence of a solution that satisfies all constraints and optimizes the cost function
B) Designing fixed controllers
C) Analyzing system poles and zeros
D) Implementing frequency response analysis
Answer: A) The existence of a solution that satisfies all constraints and optimizes the cost function