Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. A physical plant may be controlled by configurable controller, which may further comprise a low level controller associated with a higher level controller such as an Engine Control Unit (ECU). The ECU uses modeling to calculate an estimated operating value of a first parameter in the physical plant, and also uses a sensor to measure an operating value of the first parameter. The measured and modeled values are compared to determine the state of health (SOH) of the physical plant or a component thereof. The SOH may be stored, transmitted, or used to modify one or more control values used by the low level controller.

Abstract: New and/or alternative approaches to engine performance control that can account for the need to robustly monitor performance and/or operation of the physical plant and actuators thereof, while avoiding or limiting performance degradation. Model predictive control (MPC) or other control configuration such as proportional-integral-derivative control may be used to control the system by identifying a performance optimized control solution. In some examples, a modification to the performance optimized solution analysis is made to weight control solutions in favor of robust monitoring conditions. In other examples, the performance optimized solution is post-processed and modified to favor robust monitoring conditions.

Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. In one example, a control algorithm is enhanced by inclusion of terms related to optimized performance and terms related to physical plant health. In another example, a performance optimized control solution is determined, a maximum allowed deviation is defined, and a final solution for physical plant control is determined taking into account health factors to minimize health impacts within the maximum allowed deviation from optimized performance, using for example a two-stage analysis. Another example uses a two level system with a low level controller and a supervisory controller, in which the supervisory controller observes health impacts of ongoing operations managed by the low level controller, and modifies one or more parameters used by the low level controller.

Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. In one example, a control algorithm is enhanced by inclusion of terms related to optimized performance and terms related to physical plant health. In another example, a performance optimized control solution is determined, a maximum allowed deviation is defined, and a final solution for physical plant control is determined taking into account health factors to minimize health impacts within the maximum allowed deviation from optimized performance, using for example a two-stage analysis. Another example uses a two level system with a low level controller and a supervisory controller, in which the supervisory controller observes health impacts of ongoing operations managed by the low level controller, and modifies one or more parameters used by the low level controller.

Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. A physical plant may be controlled by configurable controller, which may further comprise a low level controller associated with a higher level controller such as an Engine Control Unit (ECU). The ECU uses modeling to calculate an estimated operating value of a first parameter in the physical plant, and also uses a sensor to measure an operating value of the first parameter. The measured and modeled values are compared to determine the state of health (SOH) of the physical plant or a component thereof. The SOH may be stored, transmitted, or used to modify one or more control values used by the low level controller.

Abstract: Methods and systems that monitor an actuator state of wear. One or more observations are made as to one or more extremum positions of the actuator to determine a reference extremum position when the actuator is not worn. As the actuator becomes worn, the difference between a present extremum position and the reference is used to monitor actuator wear. Actuator wear may be observed to identify or predict a need for maintenance or replacement, and/or may be used in determining health impacts of control system solutions.

Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. A physical plant may be controlled by configurable controller, which may further comprise a low level controller associated with a higher level controller such as an Engine Control Unit (ECU). The ECU uses modeling to calculate an estimated operating value of a first parameter in the physical plant, and also uses a sensor to measure an operating value of the first parameter. The measured and modeled values are compared to determine the state of health (SOH) of the physical plant or a component thereof. The SOH may be stored, transmitted, or used to modify one or more control values used by the low level controller.

Abstract: Methods and systems that monitor an actuator state of wear. One or more observations are made as to one or more extremum positions of the actuator to determine a reference extremum position when the actuator is not worn. As the actuator becomes worn, the difference between a present extremum position and the reference is used to monitor actuator wear. Actuator wear may be observed to identify or predict a need for maintenance or replacement, and/or may be used in determining health impacts of control system solutions.

Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. In one example, a control algorithm is enhanced by inclusion of terms related to optimized performance and terms related to physical plant health. In another example, a performance optimized control solution is determined, a maximum allowed deviation is defined, and a final solution for physical plant control is determined taking into account health factors to minimize health impacts within the maximum allowed deviation from optimized performance, using for example a two-stage analysis. Another example uses a two level system with a low level controller and a supervisory controller, in which the supervisory controller observes health impacts of ongoing operations managed by the low level controller, and modifies one or more parameters used by the low level controller.

Abstract: New and/or alternative approaches to physical plant performance control that can account for the health of the physical plant. A physical plant may be controlled by configurable controller, which may further comprise a low level controller associated with a higher level controller such as an Engine Control Unit (ECU). The ECU uses modeling to calculate an estimated operating value of a first parameter in the physical plant, and also uses a sensor to measure an operating value of the first parameter. The measured and modeled values are compared to determine the state of health (SOH) of the physical plant or a component thereof. The SOH may be stored, transmitted, or used to modify one or more control values used by the low level controller.

Abstract: New and/or alternative approaches to engine performance control that can account for the need to robustly monitor performance and/or operation of the physical plant and actuators thereof, while avoiding or limiting performance degradation. Model predictive control (MPC) or other control configuration such as proportional-integral-derivative control may be used to control the system by identifying a performance optimized control solution. In some examples, a modification to the performance optimized solution analysis is made to weight control solutions in favor of robust monitoring conditions. In other examples, the performance optimized solution is post-processed and modified to favor robust monitoring conditions.