Abstract: A method, apparatus and system for measuring a temperature can involve measuring a voltage with a resistance temperature detector using a variable excitation current, and deriving a process temperature from the voltage measured by the resistance temperature detector. The process temperature can be further derived by applying a plurality of values of the variable excitation current, measuring corresponding values of voltage, and estimating a resistance by applying a least square estimation. The process temperature can also be derived by applying a different value of the variable excitation current at every iteration, using a recursive least square estimation to measure a resistance, and using confidence intervals for instrument diagnostics.

Abstract: A method, apparatus and system for measuring a temperature can involve measuring a voltage with a resistance temperature detector using a variable excitation current, and deriving a process temperature from the voltage measured by the resistance temperature detector. The process temperature can be further derived by applying a plurality of values of the variable excitation current, measuring corresponding values of voltage, and estimating a resistance by applying a least square estimation. The process temperature can also be derived by applying a different value of the variable excitation current at every iteration, using a recursive least square estimation to measure a resistance, and using confidence intervals for instrument diagnostics.

Abstract: A system and method are disclosed for observing a change of mass inside a grinding unit as a part of a grinding process with a storing unit. The change of mass is derived from a mass balance for the grinding unit and a mass balance for the storing unit.

Abstract: A system and method are disclosed for observing a change of mass inside a grinding unit as a part of a grinding process with a storing unit. The change of mass is derived from a mass balance for the grinding unit and a mass balance for the storing unit.

Abstract: A control system for controlling an industrial process includes an indicator generator configured to determine at least one fuzzy logic based indicator from measured process variables. The control system also includes a state estimator configured to determine estimated physical process states based on the fuzzy indicator. For controlling the industrial process, the process controller is configured to calculate manipulated variables based on (i) defined set-points and (ii) a physical model of the process using the estimated physical process states. Combining a fuzzy logic indicator with a model based process controller provides robust indicators of the process states for controlling an industrial process in a real plant situation in which measured process variables may possibly contradict each other.

Abstract: In a method and computer program product for optimal operation of a power plant and a power plant optimising system an optimisation mode (1) minimises a cost function (J[u],J[P]) that comprises a deviation of lifetime of plant components (LTp(?)) from a desired nominal lifetime trajectory (LTn(?)). This is done by, at a given time, determining future values of input values (u(?),P(?)) such as control values (P(?)) or process values (u(?)) to the plant and simulating, in a simulation modulate (2), the behaviour of the plant up to a given future time. Corresponding lifetime values are determined in the simulation, and incorporated in an objective function. The optimisation module (1) minimises the cost function (J[u],J[P]) by varying the input values (u(?),P(?)). As a result, it is possible to operate the plant such that component lifetime (LTp(?)) follows the desired trajectory (LTn(?)).

Abstract: In a method and computer program product for optimizing power plant control values and a power plant optimizing system an optimization module (1) minimizes total plant operation costs while achieving predetermined required output values for produced power and process steam. This is done by, at a given time, determining future values of control values and simulating, in a simulation module (2), the behavior of the plant up to a given future time. Corresponding fuel costs and generated power are determined in the simulation, and incorporated in an objective function. The optimization module (1) minimizes the objective function by varying the control values. According to the invention, a rate of ageing of plant components is determined when simulating the future behavior of the plant, and the objective function to be minimized comprises said rate of ageing.

Abstract: For estimating a value of a vector of variables p in a mathematical model representing a physical process, where a state vector x of the model is estimated by a State Augmented Extended Kalman Filter (SAEKF), and where that the vector of variables p represents one or more properties of the process and is representable by a function of the state vector x, the following steps are executed:

Abstract: In a method and computer program product for optimal operation of a power plant and a power plant optimising system an optimisation module (1) minimises a cost function (J[u],J[P]) that comprises a deviation of lifetime of plant components (LTp(&tgr;)) from a desired nominal lifetime trajectory (LTn(&tgr;)). This is done by, at a given time, determining future values of input values (u(&tgr;),P(&tgr;)) such as control values (P(&tgr;)) or process values (u(&tgr;)) to the plant and simulating, in a simulation module (2), the behaviour of the plant up to a given future time. Corresponding lifetime values are determined in the simulation, and incorporated in an objective function. The optimisation module (1) minimises the cost function (J[u],J[P]) by varying the input values (u(&tgr;),P(&tgr;)). As a result, it is possible to operate the plant such that component lifetime (LTp(&tgr;)) follows the desired trajectory (LTn(&tgr;)).

Abstract: In a method and computer program product for optimizing power plant control values and a power plant optimizing system an optimization module (1) minimizes total plant operation costs while achieving predetermined required output values for produced power and process steam. This is done by, at a given time, determining future values of control values and simulating, in a simulation module (2), the behavior of the plant up to a given future time. Corresponding fuel costs and generated power are determined in the simulation, and incorporated in an objective function. The optimization module (1) minimizes the objective function by varying the control values. According to the invention, a rate of ageing of plant components is determined when simulating the future behavior of the plant, and the objective function to be minimized comprises said rate of ageing.