Abstract: A control system (1) for a complex process, particularly for controlling a combustion process in a power plant, a waste incinerator plant, or a cement plant, has a controlled system (14) and at least one controller (36), wherein the control system (1) is divided hierarchically into various levels (10, 20, 30, 40). The first level (10) represents the complex, real process to be controlled and is implemented by the controlled system (14). The second level (20) represents an interface to the process and is implemented by a process control system. The third level (30) represents the control of the process and is implemented by the at least one active controller (36). The fourth level (40) represents a superordinate overview and is implemented by a principal controller (44).

Abstract: A control system (1) for a complex process, particularly for controlling a combustion process in a power plant, a waste incinerator plant, or a cement plant, has a controlled system (14) and at least one controller (36), wherein the control system (1) is divided hierarchically into various levels (10, 20, 30, 40). The first level (10) represents the complex, real process to be controlled and is implemented by the controlled system (14). The second level (20) represents an interface to the process and is implemented by a process control system. The third level (30) represents the control of the process and is implemented by the at least one active controller (36). The fourth level (40) represents a superordinate overview and is implemented by a principal controller (44).

Abstract: In a control loop for regulating a combustion process in a plant (e.g., a power-generating plant, a waste incineration plant or a cement works) having a controlled system for converting material by way of the combustion process while supplying air, with at least one flame body being formed, and having at least one observation device for imaging the flame body, other sensors for determining the input data, at least one adjustment device that can be controlled by output data for supplying at least material and/or air, and a computer for evaluating the input data in relation to target values and for determining the output data by using a current process model, the computer has a feature extraction module that extracts features from the input data using an information measure. The features are informative for the target values, and are for use in an alternative process model.

Abstract: In a procedure for regulating a combustion process in an installation while air is being supplied, material is converted by the combustion process, with at least one flame being formed, and the state variables (s(t)) describing the state of the system in the installation are determined using at least one observation device that images the flame, as well as other sensors, and are evaluated in a computer, whereupon any appropriate actions (ai) that may be needed are selected in order to control adjusting devices for the supply of material and/or air, wherein during setpoint regulation to achieve setpoints (s0) of the state variables and/or stability of the combustion process a changeover is occasionally made from setpoint control to disturbance control.

Abstract: Material (G) is converted by a combustion process in a plant (1) while air (L) is supplied. The state of the system in the plant (1) is described by state variables (x, y) and is regulated at least by one control loop (3, 5, 7, 9). Groups of states (Z) are defined for at least one pair of correlated state variables (x, y), with the groups being comparable as regards changes (dx/dt, dy/dt) of the correlated state variables (x, y). Each group of comparable states (Z) is characterized, as regards their transition functions, by parameters (Kp, Tn, Tv) of a standard controller. In the event of changes in the state of the system in the plant (1), the closest groups of comparable states (Z) are selected, and their transition functions, characterized by the parameters (Kp, Tn, Tv), are used for the purposes of regulation the system.

Abstract: A neuronal network is trained using measurement data of state variables comprising measurement data from input channels and measurement data from at least one output channel. The neuronal network is tested using measurement data from the input channels and measurement data from the output channel, and a first standard deviation is determined from the deviations of the predicted values for the output channel from the measurement data of the output channel. The measurement data of at least one input channel are replaced by a distribution. Values for the output channel are again calculated using the distribution or parts thereof and a second standard deviation of the calculated values for the output channel is determined from the associated measurement data. In the case of an increase in the second standard deviation compared with the first standard deviation, the input channel is significant for the neuronal network.

Abstract: In a control loop for regulating a combustion process in a plant having a controlled system for converting material by way of the combustion, with at least one flame body being formed, the control loop having at least one observation device for imaging the flame body and further sensors to determine the state variables describing the state of the system in the plant, at least one regulator and/or a computer to evaluate the state variables and select suitable actions based on a process model, and adjustment devices for at least the supply of material and/or air that can be controlled by the actions, the process model provides specialized function approximators for various process dynamics, one of which function approximators is selected by a selector, and a regulator assigned to the selected function approximator is used to regulate the control loop.

Abstract: A control loop, which is for regulating a process in a plant having a controlled system, comprises: at least one measuring device for recording observation values of the controlled system, at least one adjustment device for acting on the controlled system in response to the adjustment device being controlled by way of action values, and a regulator. The regulator is operative to provide the action values. The regulator being operative to provide the action values comprises the regulator being adapted for: predicting, by way of a process model and at least one probability distribution of the observation values, a set of distributions of probable future states of the system; evaluating the set of distributions of probable future states of the system using target values and/or distributions of the target values; and selecting at least one probability distribution of action values.

Abstract: In a control loop for regulating a combustion process in a plant (e.g., a power-generating plant, a waste incineration plant or a cement works) having a controlled system for converting material by way of the combustion process while supplying air, with at least one flame body being formed, and having at least one observation device for imaging the flame body, other sensors for determining the input data, at least one adjustment device that can be controlled by output data for supplying at least material and/or air, and a computer for evaluating the input data in relation to target values and for determining the output data by using a current process model, the computer has a feature extraction module that extracts features from the input data using an information measure. The features are informative for the target values, and are for use in an alternative process model.

Abstract: Material (G) is converted by a combustion process in a plant (1) while air (L) is supplied. The state of the system in the plant (1) is described by state variables (x, y) and is regulated at least by one control loop (3, 5, 7, 9). Groups of states (Z) are defined for at least one pair of correlated state variables (x, y), with the groups being comparable as regards changes (dx/dt, dy/dt) of the correlated state variables (x, y). Each group of comparable states (Z) is characterized, as regards their transition functions, by parameters (Kp, Tn, Tv) of a standard controller. In the event of changes in the state of the system in the plant (1), the closest groups of comparable states (Z) are selected, and their transition functions, characterized by the parameters (Kp, Tn, Tv), are used for the purposes of regulation the system.

Abstract: In a procedure for regulating a combustion process in an installation while air is being supplied, material is converted by the combustion process, with at least one flame being formed, and the state variables (s(t)) describing the state of the system in the installation are determined using at least one observation device that images the flame, as well as other sensors, and are evaluated in a computer, whereupon any appropriate actions (ai) that may be needed are selected in order to control adjusting devices for the supply of material and/or air, wherein during setpoint regulation to achieve setpoints (so) of the state variables and/or stability of the combustion process a changeover is occasionally made from setpoint control to disturbance control.

Abstract: In a method for monitoring a thermodynamic process in an installation, in which image material (5) of the process is produced and the image material (5) is subjected to image evaluation, an eigen value problem approach is used, at least in large part, for automatic image evaluation.

Abstract: In a method for controlling a thermodynamic process, in particular a combustion process, in which the system status (st) is measured, compared with optimization targets (rj), and in which suitable setting actions (ai) are performed in the system for controlling it, a process model (PM) is determined that is independent of the optimization targets (rj) and which describes the effects of actions (at) on the system status (st), and in which a situational evaluation (SB) that is independent of the process model (PM) evaluates the system status (st) by means of quality functions (ut) with regard to the optimization targets (rj).

Abstract: In a method for monitoring a combustion process, in which, in a oven, a substance arranged in a bed of the oven is converted under the supply of heat by way of firing by a flame, data of the flame and/or the substance in the bed being recorded by way of at least one sensor, the input of heat into the bed is determined from the data recorded by the sensor and is used for quality determination.

Abstract: In a method for monitoring a combustion process, in which, in a oven, a substance arranged in a bed of the oven is converted under the supply of heat by way of firing by a flame, data of the flame and/or the substance in the bed being recorded by way of at least one sensor, the input of heat into the bed is determined from the data recorded by the sensor and is used for quality determination.

Abstract: In a method for controlling a thermodynamic process, in particular a combustion process, in which the system status (st) is measured, compared with optimization targets (rj), and in which suitable setting actions (ai) are performed in the system for controlling it, a process model (PM) is determined that is independent of the optimization targets (rj) and which describes the effects of actions (at) on the system status (st), and in which a situational evaluation (SB) that is independent of the process model (PM) evaluates the system status (st) by means of quality functions (ut) with regard to the optimization targets (rj).