Provided is a control system comprising a control apparatus including a learning processing unit for generating a control model by learning, the control model being for calculating control data for controlling a facility according to state data detected by at least one sensor for measuring a state of the facility, and a model transmission unit for transmitting the generated control model to a controller for controlling the facility; and a controller including a model receiving unit for receiving the learned control model from the control apparatus, a state receiving unit for receiving the state data from the at least one sensor, a calculation unit for calculating control data for controlling the facility according to the state data, which is a processing target, by using the control model received by the model receiving unit, and a control unit for controlling the facility by using the calculated control data.

Technology is disclosed for scheduling control data transmissions in a control system that operates independently of specific control structures. The method begins by receiving the current system state of a controlled electronic device. Using a model of the device, a nominal system state and corresponding control signal are estimated. An error signal is computed as the difference between the actual and nominal states. This error signal is used to adjust the nominal control signal via a feedback matrix. A previously transmitted control signal is retrieved, and an alignment metric is calculated by comparing the direction of the error signal with the change in control signals. The alignment metric is then evaluated against a condition derived from the magnitude of the error signal. If the condition is satisfied, the adjusted control signal is transmitted. This approach enables efficient and responsive control data scheduling, enhancing system performance while reducing unnecessary transmissions.

Technology is disclosed for scheduling control data transmissions in a control system that operates independently of specific control structures. The method begins by receiving the current system state of a controlled electronic device. Using a model of the device, a nominal system state and corresponding control signal are estimated. An error signal is computed as the difference between the actual and nominal states. This error signal is used to adjust the nominal control signal via a feedback matrix. A previously transmitted control signal is retrieved, and an alignment metric is calculated by comparing the direction of the error signal with the change in control signals. The alignment metric is then evaluated against a condition derived from the magnitude of the error signal. If the condition is satisfied, the adjusted control signal is transmitted. This approach enables efficient and responsive control data scheduling, enhancing system performance while reducing unnecessary transmissions.