Abstract: A building management system includes sensors configured to measure a plurality of monitored variables and fault detection and diagnosis (FDD) system configured to identify an operating state associated with the monitored variables. The FDD system includes a communications interface configured to receive samples of the monitored variables from the plurality of sensors. The FDD system includes a direction extractor configured to use locations, in a multidimensional modeling space, of a plurality of stored operating states to extract a direction from each of the stored operating states to each of the other stored operating states. The FDD system includes a fault diagnoser configured to use the extracted directions in a voting-based diagnosis to determine an operating state for each of the samples of the monitored variables.

Abstract: A control system for a plant includes a controller and a sensor. The controller is configured to estimate a response time of the plant and adjust a sampling rate based on the estimated response time. The response time is a parameter that characterizes a response of the plant to a disturbance. The sensor is configured to receive the adjusted sampling rate from the controller, collect samples of a measured variable from the plant at the adjusted sampling rate, and provide the samples of the measured variable to the controller.

Abstract: A control system for a plant includes a controller configured to detect a disturbance in the control system. In response to detecting the disturbance, the controller is configured to evaluate a signal affected by the disturbance to estimate a response time of a plant. The response time is a parameter that characterizes a response of the plant to the disturbance. The controller is configured to adjust an operating parameter used by the control system based on the estimated response time. The controller is configured to use the adjusted operating parameter to generate and provide an input to the plant.

Abstract: A method for adaptively and automatically adjusting a sampling rate in a feedback control system includes monitoring an error signal for a disturbance event, evaluating the error signal in response to the disturbance event to estimate a time constant of a control process, and determining a sampling rate for use in the feedback control system based on the estimated time constant. The error signal may be based on a difference between a setpoint and a feedback signal and the feedback signal may be received from the control process.

Abstract: A setpoint alarming system includes a feedback controller that monitors a process variable provided as a feedback signal from a plant and uses an error signal representing a difference between the process variable and a setpoint to generate a control signal for the plant. The plant uses the control signal to affect the process variable. The system includes a normalized index generator that uses the error signal to generate a normalized performance index for the plant. The system includes an expected value estimator that estimates a value of the normalized performance index expected to occur when a setpoint error of a predetermined magnitude has persisted for a predetermined duration. The system includes an alarm manager that compares the normalized performance index to the expected value and generates an alarm in response to the normalized performance index dropping below the expected value.

Abstract: A method for adaptively and automatically adjusting a sampling rate in a feedback control system includes monitoring an error signal for a disturbance event, evaluating the error signal in response to the disturbance event to estimate a time constant of a control process, and determining a sampling rate for use in the feedback control system based on the estimated time constant. The error signal may be based on a difference between a setpoint and a feedback signal and the feedback signal may be received from the control process.