Abstract:
A system for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.
Abstract:
A method for optimizing customer utility usage in a utility network of customer sites, each having one or more utility devices, where customer site information is communicated between each of the customer sites and an optimization server having software for optimizing customer utility usage over one or more networks, including private and public networks. A customer site model for each of the customer sites is generated based upon the customer site information, and the customer utility usage is optimized based upon the customer site information and the customer site model. The optimization server can be hosted by an external source or within the customer site. In addition, the optimization processing can be partitioned between the customer site and an external source.
Abstract:
A system and method for reducing device test time are disclosed herein. A method for reducing device test time includes applying a linear program solver to select a first set of tests for testing a device from a second set of tests for testing the device. The first set of tests is selected to reduce the time required to test the device while allowing no more than a predetermined number of devices tested to pass the first set of tests and fail the second set of tests.
Abstract:
A system and method of controlling a sensor to sense one target from a plurality of targets includes predicting states of the targets. A set of probability distributions is generated. Each probability distribution in the set represents a setting or settings of at least one control parameter of the sensor. An expected information gain value for each control parameter in the set is calculated. The information gain value represents an expected quality of a measurement of one of the targets taken by the sensor if controlled according to the control parameter, based on the predicted state of the target. Updating the set of probability distributions takes place to identify the sensor control parameters that maximise the expected information gain value. The sensor is then controlled in accordance with the maximising control parameters.
Abstract:
A lead-lag input filter is connected ahead of a positioner feedback loop having one or more valve accessories, such as a volume booster or a QEV, to overcome slow dynamics experienced by the accessories when receiving low amplitude change control or set point signals. A user interface is connected to the lead-lag input filter and enables an operator or other control personnel to view and change the operating characteristics of the lead-lag input filter to thereby provide the control loop with any of a number of desired response characteristics.
Abstract:
An integrated optimization and control technique performs process control and optimization using stochastic optimization similar to that used in biological immune systems during on-line operation of a process, the technique collects and stores indications of process control states. During steady-state operation, the technique optimizes process operation by developing sets of process control inputs from stored process control states using an objective function that defines an optimality criterion. Moreover, after one or more disturbance inputs experiences a significant change, the technique responds by comparing the changed disturbance inputs to the disturbance inputs of at least some of the stored process control states to determine the stored process control states that are closest to the new process operating condition. The technique then develops a new set of control inputs based on the control inputs associated with the stored process control states determined to be closest to the new process operating condition.
Abstract:
A method and system for combining a feedback control and a feedforward control in a linear MPC to minimize effect of model uncertainty. An externally computed feedforward signal, which is more accurate and reliable, can be utilized in association with the MPC. A steady state relation between system parameters can be determined in order to compute the feedforward signal for a set of actuators associated with a non-linear system. A feedback MPC controller can then be designed. A state observer can be configured as an unknown input observer to estimate the effect of the feedforward signal. A strategy for manipulating the constraints of the MPC feedback signal can be implemented. A resulting control action for the actuators can be provided as a sum of corresponding feedback and feedforward signal while ensuring the constraints satisfaction.
Abstract:
In a method of operating a material testing machine for testing a specimen, the machine has an electrically controllable actuator arranged to apply a force to the specimen. The method includes inputting a single adjustable parameter value, calculating all necessary feedback control gains therefrom, and subsequently conducting a test of the specimen.
Abstract:
The invention provides control systems and methodologies for controlling a process having one or more motorized pumps and associated motor drives, which provide for optimized process performance according to one or more performance criteria, such as efficiency, component life expectancy, safety, emissions, noise, vibration, operational cost, or the like. More particularly, the subject invention provides for employing machine diagnostic and/or prognostic information in connection with optimizing an overall business operation over a time horizon.
Abstract:
A flexible process optimizer for recording and analyzing various parameters to improve the efficiency of a production process. The flexible process optimizer acquires and conditions signals from a variety of transducers mounted on a production machine. Through qualitative and quantitative data analysis, specific aspects are of the production process which need improvement are identified. The qualitative evaluation looks at the presence, absence, or duration of certain features of the production cycle as revealed by the sensor data. The quantitative evaluation of data involves the computation of certain data attributes. By providing useful data acquisition and data analysis tools, necessary adjustments are made to the required parameters of the production process to provide improved efficiency. The results of the changes are immediately verifiable using the flexible process optimizer.