Techniques for ripple-type control of networked physical systems such as power systems, water systems, and others are provided. As one example, a device includes at least one processor configured to determine, for a first controllable device in a system, based on a measurement of an output parameter and a minimum output parameter value, an output violation value for the first device. The processor is further configured to determine, based on a present input value for the first device, the output violation value, and an assistance requisition value corresponding to a second device, a target input value for the first device. The processor is further configured to cause the first controllable device to modify operation based on the target input value and a maximum input value for the first controllable device.

A data processing device according to one aspect of the present invention includes a first definer configured to define a transfer function of a process which is a control target on the basis of an output value from the process and a manipulated variable of the process, an analyzer configured to analyze frequency characteristics of the output value from the process, a second definer configured to define a target sensitivity function on the basis of a sensitivity function, a first frequency band included in the frequency characteristics, and a predetermined attenuation factor, the sensitivity function being defined based on the transfer function of the process and at least one control parameter of a controller for controlling the process, and an adjuster configured to adjust the at least one control parameter to decrease a difference between the sensitivity function and the target sensitivity function.

A system and method enable an incineration facility to be controlled and diagnosed, and the life cycle thereof managed, using a heat exchange and design program and operation mode analysis of an operator of the facility. Operation efficiency is improved by comparing and analyzing (a) initial design values of the incineration facility, (b) measured actual valued obtained by measuring waste composition and heating values changed after construction of the facility and (c) operation values indicating actual operation adjustment values and operating result values operated by the operator and by analyzing the operator. The design values, measured actual values and operation values are compared and provided as data in graphs and tables.

The present invention relates to method for modifying process parameters based on optimum operation performance criteria for a metal working process, said method comprising the steps of inputting standard process parameters for at least one product to be machined and generating operational data based on the standard process parameters. Operational data is compared with optimized operation performance criteria and is presented to a decision-making entity. This entity may be allowed to modify the process parameters so as to improve operation of the metal working process.

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.

The invention comprises systems and methods for ramping setpoints on thermostats controlling HVAC systems. At least one thermostat is located inside a structure and is used to control an HVAC system in the structure. At least one remote processor is in communication with said thermostat and at least one database stores data reported by the thermostat. At least one processor compares the outside temperature at at least one location and at least one point in time to information reported to the remote processor from the thermostat. The remote processor ramps the setpoint on the thermostat so as to reduce the average spread between inside temperature and outside temperature in order to reduce energy consumption with affecting comfort. The remote processor takes into account the effect of weather conditions and occupant preferences in determining whether and when to ramp setpoints.

To perform reinforcement learning enabling to prevent complicated adjustment of coefficients of backlash compensation and backlash acceleration compensation. A machine learning apparatus includes a state information acquiring part for acquiring, from a servo control apparatus, state information including at least position deviation and a set of coefficients to be used by a backlash acceleration compensating part, by making the servo control apparatus execute a predetermined machining program, an action information output part for outputting action information including adjustment information on the set of coefficients included in the state information to the servo control apparatus, a reward output part for outputting a reward value in the reinforcement learning on the basis of the position deviation included in the state information, and a value function updating part for updating an action-value function on the basis of the reward value output by the reward output part, the state information and the action information.

A control apparatus includes: a control computing unit that generates an operation amount based on a control deviation, calculated by performing subtraction of a command value and a control amount, and a control gain; an adjustment-execution-command generating unit that generates an adjustment-execution command value indicating ON or OFF; a binary output unit that generates an adjustment-time addition value based on the control deviation and a hysteresis-width setting value; a standard-deviation estimating unit that calculates a low-frequency-component removed signal obtained by removing low-frequency components of the control amount or the control deviation and calculates a standard-deviation estimated value, which is an estimated value of a standard deviation; and a hysteresis-width computing unit that calculates a hysteresis-width computed value based on the standard-deviation estimated value and changes the hysteresis-width setting value of the binary output unit to the hysteresis-width computed value.

To configure a machine controller by an action execution tree, predefined action patterns are read in. A multiplicity of action execution trees for a machine to be controlled is also generated. For a respectively generated action execution tree, a performance for controlling the machine based on the respective action execution tree is determined. The predefined action patterns are also sought in the respective action execution tree. An action pattern found in the respective action execution tree is then replaced at least in part by a reference to the predefined action pattern. A tree size of the thus modified action execution tree is furthermore determined. Based on the generated action execution trees, a numerical optimization method is then used to determine an action execution tree that is optimized with regard to better performance and smaller tree size, and this is output in order to configure the machine controller.

A method and apparatus for providing secure, online centralized control over the selection of services and commodities to meet for example energy capacity for an electric generating plant, the method and apparatus providing screening and rejection of unqualified applicants, transparency exceeding governmental guidelines, options to aggregate offers, and facilitate automated, real time evaluation and ranking of energy producers.