Model predictive control apparatus

• US 7,418,372 B2
• Filed: 05/13/2005
• Issued: 08/26/2008
• Est. Priority Date: 05/27/2004
• Status: Expired due to Fees

• Current Assignee: Nissan Motor Co., Ltd.
• Original Assignee: Nissan Motor Co., Ltd.
• Inventors: Nishira, Hikaru, Kawabe, Taketoshi
• Primary Examiner(s): FREJD, RUSSELL WARREN
• Application Number:
  US11/128,271
• Publication Number:
  US 20050267608A1
• Time in Patent Office: 1,201 Days
• Field of Search: 703/2, 703/8, 700 28- 31, 700/44, 706/21, 701/96, 701/117, 701/301
• US Class Current: 703/2
• CPC Class Codes: B60K 31/0008 including means for detecting potential obstacles in vehicle path
• CPC Class Codes: B60K 31/047 the memory being digital
• CPC Class Codes: B60W 2050/0031 Mathematical model of the vehicle
• CPC Class Codes: B60W 50/0097 Predicting future conditions

Abstract

A model predictive control apparatus includes an initial solution generation section, an abnormality handling section, and an objective function adjustment section. The abnormality handling section performs initial solution generation when it is determined that performed optimization is abnormal. The initial solution generation section generates an initial optimal value of a future time series control input in accordance with an initial objective function, without reference to a candidate value of the time series control input. The objective function adjustment section adjusts the current objective function so that the current objective function varies stepwise with time toward the normal objective function when it is determined that the current objective function is different from the normal objective function.

Claims

1. A model predictive control apparatus comprising:

a sensing section configured to measure a state of a physical system; and

a control unit connected electrically to the sensing section for receiving a sensing signal indicative of the measured system state, the control unit comprising;

a system behavior prediction section configured to perform the following;

predicting a future time series of the system state over a prediction horizon of time in accordance with the measured system state, and a future time series of a control input to the system over a control horizon of time;

an objective function reference section configured to perform the following;

providing a normal value of function definition data defining a normal objective function, the function definition data defining an objective function configured to provide a quantitative measure, in accordance with the time series system state, the time series control input, and a time series of a setpoint of the system state over the prediction horizon;

providing an initial value of the function definition data defining an initial objective function; and

providing a current value of the function definition data defining a current objective function;

an initial solution generation section configured to perform the following;

setting the current function definition data value to the initial function definition data value;

generating an initial optimal value of the time series control input in accordance with the initial function definition data value, without reference to a candidate value of the time series control input;

setting an optimal value of the time series control input to the initial optimal value of the time series control input; and

setting the next candidate value of the time series control input to the initial optimal value of the time series control input;

an optimization section configured to perform the following;

calculating an optimal value of a time series control input correction over the control horizon in accordance with the current function definition data value, and the candidate value of the time series control input, the control input correction being a differential between the control input and the candidate control input value;

setting the optimal value of the time series control input to a sum of the candidate value of the time series control input and the optimal value of the time series control input correction; and

setting the next candidate value of the time series control input;

an abnormality handling section configured to perform the following;

determining whether or not the performed optimization in the optimization section is abnormal; and

performing the initial solution generation when it is determined that the performed optimization is abnormal;

an objective function adjustment section configured to perform the following;

comparing the current function definition data value with the normal function definition data value; and

adjusting the current function definition data value so that the current objective function varies stepwise with time toward the normal objective function when it is determined that the current function definition data value is different from the normal function definition data value; and

an output section configured to perform the following;

determining an output value of the control input in accordance with the optimal value of the time series control input; and

outputting an output signal in accordance with the output value of the control input.

2. The model predictive control apparatus as claimed in claim 1, wherein the optimization section is configured to set the next candidate value of the time series control input to the optimal value of the time series control input.

3. The model predictive control apparatus as claimed in claim 1, wherein the adjusted current objective function is a weighted average of the initial objective function and the normal objective function, and wherein the objective function adjustment section is configured to perform the following when it is determined that the current function definition data value is different from the normal function definition data value:

adjusting the current function definition data value so that the weights for the initial objective function and the normal objective function in the adjusted current objective function vary stepwise with time, and so that the current objective function varies stepwise with time toward the normal objective function.

4. The model predictive control apparatus as claimed in claim 1, wherein the adjusted current objective function is a weighted average of the current objective function and the normal objective function so that the current objective function varies stepwise with time toward the normal objective function.

5. The model predictive control apparatus as claimed in claim 1, wherein the abnormality handling section is configured to adjust the current function definition data value so that a current value of a length of the prediction horizon decreases from a normal value of a length of the prediction horizon so that the optimization is held normal, when it is determined that the performed optimization is abnormal.

6. The model predictive control apparatus as claimed in claim 5, wherein objective function adjustment section is configured to adjust the current function definition data value so that the current value of the prediction horizon length varies stepwise with time toward the normal value of the prediction horizon length, when the current value of the prediction horizon length is different from the normal value of the prediction horizon length.

7. The model predictive control apparatus as claimed in claim 1, wherein the initial objective function is configured to take less calculation cost to generate the optimal value of the time series control input without reference to the candidate value of the time series control input than the normal objective function.

8. The model predictive control apparatus as claimed in claim 1, wherein the normal objective function is a weighted sum of a plurality of functions, and wherein the initial objective function is a weighted sum of part of the plurality of functions.

9. The model predictive control apparatus as claimed in claim 1, wherein the initial solution generation section is configured to perform the following:

providing an explicit function definition data value defining an explicit function to provide the optimal value of the time series control input in accordance with the initial objective function; and

calculating the optimal value of the time series control input in accordance with the explicit function definition data value when it is determined that the current function definition data value is identical to the initial function definition data value.

10. The model predictive control apparatus as claimed in claim 1, wherein the initial solution generation section is configured to perform the following:

providing a set of multiple optimal values of the time series control input with respect to multiple hypothetical values of the system state in accordance with the initial objective function; and

determining the optimal value of the time series control input in accordance with the provided set of multiple optimal values of the time series control input.

11. The model predictive control apparatus as claimed in claim 1, wherein the abnormality handling section is configured to determine that the performed optimization is abnormal when the optimal value of the time series control input correction includes a value of the control input correction whose magnitude is larger than a certain threshold value.

12. The model predictive control apparatus as claimed in claim 1, wherein the abnormality handling section is configured to determine that the performed optimization is abnormal when the optimal value of the time series control input includes a value of an element of the control input which is out of certain associated bounds.

13. The model predictive control apparatus as claimed in claim 1, wherein the optimization section is configured to calculate the optimal value of the future time series control input correction by iterative calculations the number of which is bounded by a certain upper bound;

and wherein the abnormality handling section is configured to perform the following;

determining a degree of error of the performed optimization; and

determining that the performed optimization is abnormal when the error degree is at or above a certain threshold level.

14. The model predictive control apparatus as claimed in claim 1, wherein the system behavior prediction section is configured to perform the following:

providing a time series of the measured system state; and

predicting the future time series system state in accordance with the time series measured system state, and the time series control input.

15. The model predictive control apparatus as claimed in claim 1, wherein the system state includes a position of a movable object and a velocity of the movable object, and wherein the control input includes a physical quantity to generate an acceleration of the movable object to change the position and velocity of the movable object.

16. A model predictive control apparatus for a host automotive vehicle, comprising:

a sensing section configured to detect a target vehicle present around the host vehicle, and to measure a state of a physical system including the host vehicle and the target vehicle; and

a control unit connected electrically to the sensing section for receiving a sensing signal indicative of the measured system state, the control unit comprising;

a system behavior prediction section configured to perform the following;

predicting a future time series of the system state over a prediction horizon of time in accordance with the measured system state, and a future time series of a control input to the host vehicle over a control horizon of time;

an objective function reference section configured to perform the following;

providing a normal value of function definition data defining a normal objective function, the function definition data defining an objective function configured to provide a quantitative measure, in accordance with the time series system state, the time series control input, and a time series of a setpoint of the system state over the prediction horizon;

providing an initial value of the function definition data defining an initial objective function; and

providing a current value of the function definition data defining a current objective function;

an initial solution generation section configured to perform the following;

setting the current function definition data value to the initial function definition data value;

generating an initial optimal value of the time series control input in accordance with the initial function definition data value, without reference to a candidate value of the time series control input;

setting an optimal value of the time series control input to the initial optimal value of the time series control input; and

setting the next candidate value of the time series control input to the initial optimal value of the time series control input;

an optimization section configured to perform the following;

calculating an optimal value of a time series control input correction over the control horizon in accordance with the current function definition data value, and the candidate value of the time series control input, the control input correction being a differential between the control input and the candidate control input value;

setting the optimal value of the time series control input to a sum of the candidate value of the time series control input and the optimal value of the time series control input correction; and

setting the next candidate value of the time series control input;

an abnormality handling section configured to perform the following;

determining whether or not the performed optimization in the optimization section is abnormal; and

performing the initial solution generation when it is determined that the performed optimization is abnormal;

an objective function adjustment section configured to perform the following;

comparing the current function definition data value with the normal function definition data value; and

adjusting the current function definition data value so that the current objective function varies stepwise with time toward the normal objective function when it is determined that the current function definition data value is different from the normal function definition data value; and

an output section configured to perform the following;

determining a recommended value of the control input in accordance with the optimal value of the time series control input; and

outputting an output signal in accordance with the recommended value of the control input.

17. The model predictive control apparatus as claimed in claim 16, wherein the abnormality handling section is configured to perform the following:

determining a degree of risk of contact between the host vehicle and the target vehicle in accordance with the system state; and

determining that the performed optimization is abnormal when the optimal predicted value of the time series system state includes an abnormal future value of the system state whose risk degree is at or above a certain threshold level.

18. The model predictive control apparatus as claimed in claim 17, wherein the abnormality handling section is configured to perform the following when the optimal predicted value of the time series system state includes the abnormal future value of the system state whose risk degree is at or above the threshold level:

determining a provisional desired normal future value of the system state at a future time at which the system state is predicted to be the abnormal future value;

reducing a current value of a length of the prediction horizon from a normal value of the prediction horizon length so that the future time is an end point of the prediction horizon; and

adjusting the initial function definition data value so that the optimal predicted value of the time series system state in accordance with the initial objective function includes the provisional desired normal future value of the system state at the future time.

19. The model predictive control apparatus as claimed in claim 17, wherein the abnormality handling section is configured to perform the following when the optimal predicted value of the future time series system state includes the abnormal future value of the system state in which the host vehicle is beyond the lane end point:

determining a provisional desired normal future value of the system state at a future time at which the system state is predicted to be the abnormal future value;

reducing a current value of a length of the prediction horizon from a normal value of the prediction horizon length so that the future time is an end point of the prediction horizon; and

adjusting the initial function definition data value so that the optimal predicted value of the time series system state in accordance with the initial objective function includes the provisional desired normal future value of the system state at the future time.

20. The model predictive control apparatus as claimed in claim 16, wherein the sensing section is configured to detect forward lane reduction of a road on which the host vehicle is traveling, and wherein the abnormality handling section is configured to perform the following:

identifying a lane end point when forward lane reduction of the road is detected; and

determining that the performed optimization is abnormal when the optimal predicted value of the future time series system state includes an abnormal future value of the system state in which the host vehicle is beyond the lane end point.

21. The model predictive control apparatus as claimed in claim 16, wherein the system behavior prediction section is configured to perform the following:

providing a time series of the measured system state; and

predicting a future time series state of the target vehicle as part of the future time series system state in accordance with the time series measured system state.

22. The model predictive control apparatus as claimed in claim 16, further comprising a control-command input device disposed in the host vehicle, and manually operable to input the setpoint of the system state.

23. The model predictive control apparatus as claimed in claim 16, further comprising a wheel torque actuator configured to adjust a wheel torque of the host vehicle as part of the control input in accordance with the output signal.

24. The model predictive control apparatus as claimed in claim 16, further comprising a display disposed in the host vehicle, and configured to display information concerning the current recommended control input value in accordance with the output signal.

25. A model predictive control apparatus comprising:

sensing means for measuring a state of a physical system; and

control means for receiving a sensing signal indicative of the measured system state, the control means comprising;

system behavior prediction means for performing the following;

predicting a future time series of the system state over a prediction horizon of time in accordance with the measured system state, and a future time series of a control input to the system over a control horizon of time;

objective function reference means for performing the following;

providing a normal value of function definition data defining a normal objective function, the function definition data defining an objective function configured to provide a quantitative measure, in accordance with the time series system state, the time series control input, and a time series of a setpoint of the system state over the prediction horizon;

providing an initial value of the function definition data defining an initial objective function; and

providing a current value of the function definition data defining a current objective function;

initial solution generation means for performing the following;

setting the current function definition data value to the initial function definition data value;

generating an initial optimal value of the time series control input in accordance with the initial function definition data value, without reference to a candidate value of the time series control input;

setting an optimal value of the time series control input to the initial optimal value of the time series control input; and

setting the next candidate value of the time series control input to the initial optimal value of the time series control input;

optimization means for performing the following;

calculating an optimal value of a time series control input correction over the control horizon in accordance with the current function definition data value, and the candidate value of the time series control input, the control input correction being a differential between the control input and the candidate control input value;

setting the optimal value of the time series control input to a sum of the candidate value of the time series control input and the optimal value of the time series control input correction; and

setting the next candidate value of the time series control input;

abnormality handling means for performing the following;

determining whether or not the performed optimization in the optimization means is abnormal; and

performing the initial solution generation when it is determined that the performed optimization is abnormal;

objective function adjustment means for performing the following;

comparing the current function definition data value with the normal function definition data value; and

adjusting the current function definition data value so that the current objective function varies stepwise with time toward the normal objective function when it is determined that the current function definition data value is different from the normal function definition data value; and

output means for performing the following;

determining an output value of the control input in accordance with the optimal value of the time series control input; and

outputting an output signal in accordance with the output value of the control input.

26. A method of controlling a model predictive control apparatus including a sensing section configured to measure a state of a physical system, and a control unit connected electrically to the sensing section for receiving a sensing signal indicative of the measured system state, the method comprising:

predicting a future time series of the system state over a prediction horizon of time in accordance with the measured system state, and a future time series of a control input to the system over a control horizon of time;

providing a normal value of function definition data defining a normal objective function, the function definition data defining an objective function configured to provide a quantitative measure, in accordance with the time series system state, the time series control input, and a time series of a setpoint of the system state over the prediction horizon;

providing an initial value of the function definition data defining an initial objective function;

providing a current value of the function definition data defining a current objective function;

setting the current function definition data value to the initial function definition data value;

generating an initial optimal value of the time series control input in accordance with the initial function definition data value, without reference to a candidate value of the time series control input;

setting an optimal value of the time series control input to the initial optimal value of the time series control input;

setting the next candidate value of the time series control input to the initial optimal value of the time series control input;

calculating an optimal value of a time series control input correction over the control horizon in accordance with the current function definition data value, and the candidate value of the time series control input, the control input correction being a differential between the control input and the candidate control input value;

setting the optimal value of the time series control input to a sum of the candidate value of the time series control input and the optimal value of the time series control input correction;

setting the next candidate value of the time series control input;

determining whether or not the performed optimization is abnormal;

performing the initial optimal value generation when it is determined that the performed optimization is abnormal;

comparing the current function definition data value with the normal function definition data value;

adjusting the current function definition data value so that the current objective function varies stepwise with time toward the normal objective function when it is determined that the current function definition data value is different from the normal function definition data value;

determining an output value of the control input in accordance with the optimal value of the time series control input; and

outputting an output signal in accordance with the output value of the control input.