Title of Invention	" A PROCEDURE FOR REGULATING A COMBUSTION PROCESS IN AN INSTALLATION"
Abstract	In a procedure for regulating a combustion process in an installation, in particular a power-generating plant, a waste incinerator or a cement plant, in which, while air is being supplied, material is converted by the combustion process, with at least one flame body 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 body, as well as other sensors, and are evaluated in a computer, whereupon any appropriate actions (a1) 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 according which actions (a1) are selected in order to approach states of the system in the installation at which the state variables (s(t)) deviate in a targeted manner, within predetermined limits, (s1, sh) from the optimal setpoint (s0)

Title of Invention

" A PROCEDURE FOR REGULATING A COMBUSTION PROCESS IN AN INSTALLATION"

Abstract

In a procedure for regulating a combustion process in an installation, in particular a power-generating plant, a waste incinerator or a cement plant, in which, while air is being supplied, material is converted by the combustion process, with at least one flame body 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 body, as well as other sensors, and are evaluated in a computer, whereupon any appropriate actions (a1) 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 according which actions (a1) are selected in order to approach states of the system in the installation at which the state variables (s(t)) deviate in a targeted manner, within predetermined limits, (s1, sh) from the optimal setpoint (s0)

Full Text	The invention relates to a procedure for regulating a combustion process with the features of the preamble of Claim 1. In a known procedure of this type, regulation is either carried out automatically to achieve certain setpoints of the state variables, by comparing the actual values with the setpoint values and if necessary by implementing actions, normally by making setting adjustments, or regulation is carried out to achieve stability of the combustion process, by implementing only a small number of actions. The present invention is based on the object of improving a procedure of the kind mentioned above. This object is achieved by a procedure with the features of Claim 1. Advantageous refinements are the subject matter of subclaims. Occasionally a changeover is made from setpoint control to disturbance control and, in accordance with the latter, actions are selected in order to approach system states in the installation at which the state variables deviate in a targeted manner within predetermined limits from the optimal setpoint, and as a result additional information is obtained that permits improved control. In particular, it is possible in this way to prevent the state of the system from remaining at a local minimum. Such actions would not be carried out either when regulating to achieve setpoints, where the aim is to reach a specific setpoint, nor - because they are aimed at achieving greater changes in state - would they be carried out when regulating for stability of the combustion process. Combinations of both types of control are possible in the form of compromises. The information can be obtained regularly and as comprehensively as possible in the course of ordinary disturbance control. In addition (or, if necessary, alternatively) certain areas of states can be more intensively tested using extraordinary disturbance control. 2 The invention can be used in various stationary, thermodynamic installations, in particular in power-generating plants, waste incinerators and cement plants. The invention is explained in greater detail below by means of an exemplary embodiment illustrated in the drawing, in which: Fig. 1 is a schematic representation of the time curve of a state variable s(t) up to a time t0 and the predictions for the further course of the curve, Fig. 2 is a schematic representation of the actual time curve of a state variable s(t) compared to the predictions made at time t0, Fig. 3 is a schematic representation of the time curve of a state variable s(t) with an action a1 at time t0, and Fig. 4 is a schematic view of an installation. An installation 1, for example a coal, oil or gas-fired power-generating plant, a waste incinerator or a cement plant, comprises a furnace 3, which should also be understood to mean a grate, at least one observation device 5, which can image the interior of the furnace 3 (or the grate), preferably other sensors 7, at least one adjusting device 9, and a computer 11, to which the observation device(s) 5, further sensors 7 and adjusting device(s) 9 are connected. Fuel, or another material to be converted, referred to here for short as material G, e.g. coal, oil, gas, waste material, lime, or similar, is supplied to the furnace 3 along with primary air (or primary oxygen) and secondary air (or secondary oxygen), referred to here for short as air L, this supply being regulated by the adjusting devices 9 which are controlled by the computer 11. A combustion process takes place in the furnace 3. The flame body F that is produced as a result (also any possible emissions from the walls of the furnace 3) is 3 constantly recorded by the observation devices 5. The observation devices 5 also comprise, in each case, in addition to an optical access passing through the wall of the furnace 3, e.g. a lance or device as disclosed in EP 1 621 813 Al (the disclosure content of which is explicitly included here), a camera or similar device that operates in the optical range or in adjacent ranges of electromagnetic radiation. Preference is given to a camera having high temporal, local and spectral resolution, such as the camera described, for example, in WO 02/070953 Al, the disclosure content of which is explicitly included here. The images of the flame body F (and of any possible emissions from the walls of the furnace 3) are evaluated in the computer 11, for example using an eigenvalue procedure as described in WO 2004/018940 Al, the disclosure content of which is explicitly included here. EP 1 524 470 Al, the disclosure content of which is also explicitly included here, describes a process by means of which a few characteristic values can be obtained from a spectrum. The data obtained from the images of the flame body F, as well as the data from the other sensors 7, which measure, for example, the supply of material G and of air L, concentrations of pollutants in the waste gases, or the concentration of free lime (FCAO), are treated as state variables s(t) that describe (in a time-dependent manner) the state of the system in the installation 1 in general, and the state of the combustion process in particular, and are to be considered as a vector. A control loop is defined by the furnace 3 as a (controlled) system, the observation device(s) 5 and the other sensors 7, the computer 11 and the adjusting devices 9. It is also possible to provide a conventional control loop, with just a furnace 3, sensors 7, computer 11 and adjusting devices 9 and without the observation device(s ) 5, in which the control function takes account of only a few state variables st (i. e. it is low-dimensional) and is then optimized by including the observation device(s) 5. For example, the system in 4 installation 1 can be regulated to achieve certain setpoints or to achieve a stable process (i. e. smooth, quasi-stationary operation of the installation 1). In both cases, the state described by the actual values of the state variables s(t) is evaluated and, if necessary, suitable adjustment actions (setting actions), referred to for short as actions a1 , are selected which are to be carried out by the adjusting devices 9. In addition to supplying material G and air L, other activities performed by the adjusting devices 9, and possibly also the taking of a sample, may constitute an action a' within the meaning of the invention. Disturbances may also be treated as unintended actions a". Adjustable combinations of the two above-mentioned control situations are conceivable, which then represent compromises. The evaluation of the state and the selection of suitable actions a' may, for example, be accomplished by means of a procedure such as that described in WO 02/077527 Al, the disclosure content of which is explicitly included here. At least one neuronal network is implemented in the computer 11, this network storing as a process model the reactions of the system states to actions a1, i. e. the (non-linear) links between the values of the state variables s(t) at a time t = t0 and the actions a1 which are then taken, on the one hand, and the resulting values of the state variables s(t) at a later (i. e. later by a certain time interval) point in time t = tj (or ti, t2, t3...), on the other hand, i. e. at as many times t as possible in the past. In this sense, disturbances may also be included in the process model as (unintended) actions a1. An evaluation of the situation, designed as a type of simplified quality, that is independent of the process model, i. e. of the stored links, evaluates the values of the state variables s(t) at a certain point in time t with respect to predetermined optimization targets r', i. e. to determine how close the system state is to the optimal state at time t. By evaluating a state predicted - by means of the process model as a function of a specific action a1 - at a future point in time, it is possible to determine the suitability of the specific action a1 for approaching the optimization target r1. 5 Preferably three (or four) process models are stored (each in their own neuronal network) in the computer 11, each of which contains links learned for one short (t]-t0) time interval, for one (or two) medium (t2-t0) time intervals, and for one long (t2-t0) time interval. Correspondingly, it is thus possible to make short-term, medium-term and long-term predictions. Depending on the installation 1, said time intervals range from a few seconds to several hours. The state variables s(t) should and can usually vary within certain limits, i. e. within an interval, for example between a lower limit value S] and an upper limit value sh, around an optimal setpoint s0. The values Si, Sh and so can be time-dependent. The short-term, medium-term and long-term predictions serve to estimate the difference between s(t) and the optimal setpoint s0 (the optimization target r1 in the present case would be, for example, for s(t) - so to be equal to 0 or at least to become minimal) and also to determine whether these limits (limit values S\, Sh) have been adhered to, as well as to recognize the probable need for actions a1. The temporal development of a state variable s(t) up to time t = t0 as well as the short-term prediction for t = ti, the medium-term prediction for t = t2 and the long-term prediction for t = t3 are depicted in simplified form in Fig. 1. The actual development of s(t) compared to the predictions is then represented in Fig. 2; for better comparability no action a1 has been taken. In order to improve the accuracy, not only are the process models constantly updated by the actual developments of the state variables s(t) as a reaction to actions a1, but also a competition takes place between several process models regarding the quality of the predictions. For this purpose, alternative process models, for example with other topologies, are set up and trained in the background and their predictions compared with the currently used process models in order, if necessary, to replace the latter, in the manner as described, for example, in EP 1 396 770 Al, the disclosure content of which is explicitly included here. 6 According to the invention, it is possible to switch from normal control, i. e. so-called setpoint control, to disturbance control (and back again), the computer 11, in the latter case, sending out test signals so that - without regard for the optimization targets r1 - various actions a1 are taken in order, in a targeted manner, to approach in various directions initially adjacent states (i. e. adjacent to the respectively current state with regard to the state variables s(t) ) and preferably - by successively sequencing the approach - also to reach more distant states. However, in order not to impede, let alone disrupt, the operation of the installation 1, only states within the limits (limit values s\, Sh) of the state variables s(t) are selected as the target, i.e. only actions are selected in response to which the state variables s(t) will probably remain within their limits. The computer 11 starts "ordinary" disturbance control at regular intervals, e. g. approximately every seven days, but at the latest every four weeks, approaching as many states as possible, which are preferably distributed as uniformly as possible within the limits. If the same problems occur frequently during the control procedure, the computer 11 starts "extraordinary" disturbance control. Such problems exist, for example, when the state variables s(t) frequently tend towards a limit (limit values S\, sh), i. e. the mean value drifts and/or frequently actions a1 are needed to compensate for deviations, and/or other inconsistencies occur in the regulation to achieve setpoints (optimization targets r1) and a stable process. In the case of extraordinary disturbance control, it is possible in particular to approach states which are matched to the triggering problems; for example, depending on the solution strategy, the states are selected either oriented towards the problems or in the exactly opposite direction. In the drawings, for example, a case is depicted where s(t) fluctuates constantly above the optimal setpoint s0 (Fig. 2) and tends towards the upper limit value sh also in the predictions (Fig. 1), especially the long-term prediction of the time interval t3-t0. In the case of setpoint control, at t= t0 or t = t\|, an action a1 would 7 be selected that brings s(t) closer to the optimal setpoint s0. In the case of disturbance control, on the other hand, for example, another action a1 is also selected that brings s(t) to the lower limit value Sj. This is represented by an action a1 at time t = t0 in Fig. 3. 8 9 WE CLAIM: 1. A procedure for regulating a combustion process in an installation (1), in particular in a power-generating plant, a waste incinerator or a cement plant, in which, with air (L) being supplied, material (G) is converted by means of the combustion process with at least one flame body (F) being formed, wherein the state variables (s(t)) which describe the state of the system in the installation (1) are determined by using at least one observation device (5) that images the flame body (F) and also by using other sensors (7) and are evaluated in a computer (11), whereupon, if necessary, suitable actions (a1) are selected in order to control adjustment devices (9) for at least the supply of material (G) and/or air (L), and wherein setpoint control is carried out to achieve setpoints (s0) of the state variables (s(t)) and/or stability of the combustion process, characterized in that occasionally a changeover is made from setpoint control to disturbance control and, according to the latter, actions (a1) are selected in order to approach states in the system in the installation (1) at which the state variables (s(t)) deviate in a targeted manner within predetermined limits (st, Sh).from the optimal setpoint (s0) 2. A procedure according to Claim 1, characterized in that in the case of disturbance control, for each current state, states being adjacent with respect to the state variables s(t), are approached. 3. A procedure according to any of the preceding claims, characterized in that a changeover is regularly made from setpoint control to ordinary disturbance control and back again. 4. A procedure according to Claim 3, characterized in that in the case of ordinary disturbance control, as far as possible uniformly distributed states are approached within the predetermined limits (sj, Sh). 10 5. A procedure according to any of the preceding claims, characterized in that when the same problems frequently occur in the control process, in particular a frequent tendency of the state variables (s(t)) to tend towards a limit (s1, sh), and/or when there is a frequent need for actions (a1) to compensate for tendentially the same deviations, and/or when other inconsistencies occur in the control processes aimed at achieving setpoints (s0) of the state variables (s(t)) and also a stable combustion process, a changeover is made from setpoint control to extraordinary disturbance control. 6. A procedure according to Claim 5, characterized in that in the case of extraordinary disturbance control, states are approached that are matched to the triggering problems. 7. A procedure according to any of the preceding claims, characterized in that several process models are used to evaluate the state variables (s(t)) and to select the actions (a1), in order to obtain short-term, medium-term and long-term predictions for the state variables (s(t)). 8. A control loop for implementing a procedure according to one of the preceding claims, in an installation (1), in particular in a power- generating plant, a waste incinerator or a cement plant, having a (controlled) system (3) for converting material (G) by means of the combustion process, with air (L) being supplied, and at least one flame body (F) being formed, and having at least one observation device (5) imaging the flame body (F) and having further sensors (7) to determine the state variables (s(t)) describing the state of the system in the installation (1), and having a computer (11) to evaluate the state variables (s(t)) and, if necessary, to select suitable actions (a1), and having adjusting devices (9) that can be controlled by the actions (a1) to 11 regulate at least the supply of material (G) and/or air (L), the computer (11) during setpoint control regulating the process to achieve setpoints (s0) of the state variables (s(t)) and/or stability of the combustion process, characterized in that the computer (11) changes occasionally from setpoint control to disturbance control and, according to the latter, selects actions (a1) in order to approach states of the system in the installation (1) at which the state variables (s(t)) deviate in a targeted manner, within predetermined limits (s1, Sh), from the optimal setpoint (So)- 12 9. A control loop according to Claim 8, characterized in that in the computer (11) there is implemented at least one neuronal network which in each case stores a process model for evaluating the state variables (s(t)) and selecting the actions (a1). 10. A control loop according to Claim 9, characterized in that the computer (11) contains several neuronal networks with process models for short- term, medium-term and long-term predictions of the state variables (s(t)), and/or with process models which compete with each other as regards the quality of the predictions. In a procedure for regulating a combustion process in an installation, in particular a power-generating plant, a waste incinerator or a cement plant, in which, while air is being supplied, material is converted by the combustion process, with at least one flame body 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 body, as well as other sensors, and are evaluated in a computer, whereupon any appropriate actions (a1) 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 according which actions (a1) are selected in order to approach states of the system in the installation at which the state variables (s(t)) deviate in a targeted manner, within predetermined limits, (s1, sh) from the optimal setpoint (s0)

Full Text

The invention relates to a procedure for regulating a combustion process with the features of the preamble of Claim 1.
In a known procedure of this type, regulation is either carried out automatically to achieve certain setpoints of the state variables, by comparing the actual values with the setpoint values and if necessary by implementing actions, normally by making setting adjustments, or regulation is carried out to achieve stability of the combustion process, by implementing only a small number of actions.
The present invention is based on the object of improving a procedure of the kind mentioned above. This object is achieved by a procedure with the features of Claim 1. Advantageous refinements are the subject matter of subclaims.
Occasionally a changeover is made from setpoint control to disturbance control and, in accordance with the latter, actions are selected in order to approach system states in the installation at which the state variables deviate in a targeted manner within predetermined limits from the optimal setpoint, and as a result additional information is obtained that permits improved control. In particular, it is possible in this way to prevent the state of the system from remaining at a local minimum. Such actions would not be carried out either when regulating to achieve setpoints, where the aim is to reach a specific setpoint, nor - because they are aimed at achieving greater changes in state - would they be carried out when regulating for stability of the combustion process. Combinations of both types of control are possible in the form of compromises.
The information can be obtained regularly and as comprehensively as possible in the course of ordinary disturbance control. In addition (or, if necessary, alternatively) certain areas of states can be more intensively tested using extraordinary disturbance control.
2

The invention can be used in various stationary, thermodynamic installations, in particular in power-generating plants, waste incinerators and cement plants.
The invention is explained in greater detail below by means of an exemplary embodiment illustrated in the drawing, in which:
Fig. 1 is a schematic representation of the time curve of a state variable s(t) up to a time t0 and the predictions for the further course of the curve,
Fig. 2 is a schematic representation of the actual time curve of a state variable s(t) compared to the predictions made at time t0,
Fig. 3 is a schematic representation of the time curve of a state variable s(t) with an action a1 at time t0, and
Fig. 4 is a schematic view of an installation.
An installation 1, for example a coal, oil or gas-fired power-generating plant, a waste incinerator or a cement plant, comprises a furnace 3, which should also be understood to mean a grate, at least one observation device 5, which can image the interior of the furnace 3 (or the grate), preferably other sensors 7, at least one adjusting device 9, and a computer 11, to which the observation device(s) 5, further sensors 7 and adjusting device(s) 9 are connected.
Fuel, or another material to be converted, referred to here for short as material G, e.g. coal, oil, gas, waste material, lime, or similar, is supplied to the furnace 3 along with primary air (or primary oxygen) and secondary air (or secondary oxygen), referred to here for short as air L, this supply being regulated by the adjusting devices 9 which are controlled by the computer 11. A combustion process takes place in the furnace 3. The flame body F that is produced as a result (also any possible emissions from the walls of the furnace 3) is
3

constantly recorded by the observation devices 5. The observation devices 5 also comprise, in each case, in addition to an optical access passing through the wall of the furnace 3, e.g. a lance or device as disclosed in EP 1 621 813 Al (the disclosure content of which is explicitly included here), a camera or similar device that operates in the optical range or in adjacent ranges of electromagnetic radiation. Preference is given to a camera having high temporal, local and spectral resolution, such as the camera described, for example, in WO 02/070953 Al, the disclosure content of which is explicitly included here.
The images of the flame body F (and of any possible emissions from the walls of the furnace 3) are evaluated in the computer 11, for example using an eigenvalue procedure as described in WO 2004/018940 Al, the disclosure content of which is explicitly included here. EP 1 524 470 Al, the disclosure content of which is also explicitly included here, describes a process by means of which a few characteristic values can be obtained from a spectrum. The data obtained from the images of the flame body F, as well as the data from the other sensors 7, which measure, for example, the supply of material G and of air L, concentrations of pollutants in the waste gases, or the concentration of free lime (FCAO), are treated as state variables s(t) that describe (in a time-dependent manner) the state of the system in the installation 1 in general, and the state of the combustion process in particular, and are to be considered as a vector.
A control loop is defined by the furnace 3 as a (controlled) system, the observation device(s) 5 and the other sensors 7, the computer 11 and the adjusting devices 9. It is also possible to provide a conventional control loop, with just a furnace 3, sensors 7, computer 11 and adjusting devices 9 and without the observation device(s ) 5, in which the control function takes account of only a few state variables st (i. e. it is low-dimensional) and is then optimized by including the observation device(s) 5. For example, the system in
4

installation 1 can be regulated to achieve certain setpoints or to achieve a stable process (i. e. smooth, quasi-stationary operation of the installation 1). In both cases, the state described by the actual values of the state variables s(t) is evaluated and, if necessary, suitable adjustment actions (setting actions), referred to for short as actions a1 , are selected which are to be carried out by the adjusting devices 9. In addition to supplying material G and air L, other activities performed by the adjusting devices 9, and possibly also the taking of a sample, may constitute an action a' within the meaning of the invention. Disturbances may also be treated as unintended actions a". Adjustable combinations of the two above-mentioned control situations are conceivable, which then represent compromises.
The evaluation of the state and the selection of suitable actions a' may, for example, be accomplished by means of a procedure such as that described in WO 02/077527 Al, the disclosure content of which is explicitly included here. At least one neuronal network is implemented in the computer 11, this network storing as a process model the reactions of the system states to actions a1, i. e. the (non-linear) links between the values of the state variables s(t) at a time t = t0 and the actions a1 which are then taken, on the one hand, and the resulting values of the state variables s(t) at a later (i. e. later by a certain time interval) point in time t = tj (or ti, t2, t3...), on the other hand, i. e. at as many times t as possible in the past. In this sense, disturbances may also be included in the process model as (unintended) actions a1. An evaluation of the situation, designed as a type of simplified quality, that is independent of the process model, i. e. of the stored links, evaluates the values of the state variables s(t) at a certain point in time t with respect to predetermined optimization targets r', i. e. to determine how close the system state is to the optimal state at time t. By evaluating a state predicted - by means of the process model as a function of a specific action a1 - at a future point in time, it is possible to determine the suitability of the specific action a1 for approaching the optimization target r1.
5

Preferably three (or four) process models are stored (each in their own neuronal network) in the computer 11, each of which contains links learned for one short (t]-t0) time interval, for one (or two) medium (t2-t0) time intervals, and for one long (t2-t0) time interval. Correspondingly, it is thus possible to make short-term, medium-term and long-term predictions. Depending on the installation 1, said time intervals range from a few seconds to several hours. The state variables s(t) should and can usually vary within certain limits, i. e. within an interval, for example between a lower limit value S] and an upper limit value sh, around an optimal setpoint s0. The values Si, Sh and so can be time-dependent. The short-term, medium-term and long-term predictions serve to estimate the difference between s(t) and the optimal setpoint s0 (the optimization target r1 in the present case would be, for example, for s(t) - so to be equal to 0 or at least to become minimal) and also to determine whether these limits (limit values S\, Sh) have been adhered to, as well as to recognize the probable need for actions a1. The temporal development of a state variable s(t) up to time t = t0 as well as the short-term prediction for t = ti, the medium-term prediction for t = t2 and the long-term prediction for t = t3 are depicted in simplified form in Fig. 1. The actual development of s(t) compared to the predictions is then represented in Fig. 2; for better comparability no action a1 has been taken.
In order to improve the accuracy, not only are the process models constantly updated by the actual developments of the state variables s(t) as a reaction to actions a1, but also a competition takes place between several process models regarding the quality of the predictions. For this purpose, alternative process models, for example with other topologies, are set up and trained in the background and their predictions compared with the currently used process models in order, if necessary, to replace the latter, in the manner as described, for example, in EP 1 396 770 Al, the disclosure content of which is explicitly included here.
6

According to the invention, it is possible to switch from normal control, i. e. so-called setpoint control, to disturbance control (and back again), the computer 11, in the latter case, sending out test signals so that - without regard for the optimization targets r1 - various actions a1 are taken in order, in a targeted manner, to approach in various directions initially adjacent states (i. e. adjacent to the respectively current state with regard to the state variables s(t) ) and preferably - by successively sequencing the approach - also to reach more distant states. However, in order not to impede, let alone disrupt, the operation of the installation 1, only states within the limits (limit values s\, Sh) of the state variables s(t) are selected as the target, i.e. only actions are selected in response to which the state variables s(t) will probably remain within their limits.
The computer 11 starts "ordinary" disturbance control at regular intervals, e. g. approximately every seven days, but at the latest every four weeks, approaching as many states as possible, which are preferably distributed as uniformly as possible within the limits. If the same problems occur frequently during the control procedure, the computer 11 starts "extraordinary" disturbance control. Such problems exist, for example, when the state variables s(t) frequently tend towards a limit (limit values S\, sh), i. e. the mean value drifts and/or frequently actions a1 are needed to compensate for deviations, and/or other inconsistencies occur in the regulation to achieve setpoints (optimization targets r1) and a stable process. In the case of extraordinary disturbance control, it is possible in particular to approach states which are matched to the triggering problems; for example, depending on the solution strategy, the states are selected either oriented towards the problems or in the exactly opposite direction.
In the drawings, for example, a case is depicted where s(t) fluctuates constantly above the optimal setpoint s0 (Fig. 2) and tends towards the upper limit value sh also in the predictions (Fig. 1), especially the long-term prediction of the time interval t3-t0. In the case of setpoint control, at t= t0 or t = t|, an action a1 would
7

be selected that brings s(t) closer to the optimal setpoint s0. In the case of disturbance control, on the other hand, for example, another action a1 is also selected that brings s(t) to the lower limit value Sj. This is represented by an action a1 at time t = t0 in Fig. 3.
8

9

WE CLAIM:
1. A procedure for regulating a combustion process in an installation (1), in
particular in a power-generating plant, a waste incinerator or a cement
plant, in which, with air (L) being supplied, material (G) is converted by
means of the combustion process with at least one flame body (F) being
formed, wherein the state variables (s(t)) which describe the state of the
system in the installation (1) are determined by using at least one
observation device (5) that images the flame body (F) and also by using
other sensors (7) and are evaluated in a computer (11), whereupon, if
necessary, suitable actions (a1) are selected in order to control
adjustment devices (9) for at least the supply of material (G) and/or air
(L), and wherein setpoint control is carried out to achieve setpoints (s0)
of the state variables (s(t)) and/or stability of the combustion process,
characterized in that occasionally a changeover is made from setpoint
control to disturbance control and, according to the latter, actions (a1) are
selected in order to approach states in the system in the installation (1)
at which the state variables (s(t)) deviate in a targeted manner within
predetermined limits (st, Sh).from the optimal setpoint (s0)
2. A procedure according to Claim 1, characterized in that in the case of
disturbance control, for each current state, states being adjacent with
respect to the state variables s(t), are approached.
3. A procedure according to any of the preceding claims, characterized in
that a changeover is regularly made from setpoint control to ordinary
disturbance control and back again.
4. A procedure according to Claim 3, characterized in that in the case of
ordinary disturbance control, as far as possible uniformly distributed
states are approached within the predetermined limits (sj, Sh).
10

5. A procedure according to any of the preceding claims, characterized in
that when the same problems frequently occur in the control process, in
particular a frequent tendency of the state variables (s(t)) to tend towards
a limit (s1, sh), and/or when there is a frequent need for actions (a1) to
compensate for tendentially the same deviations, and/or when other
inconsistencies occur in the control processes aimed at achieving
setpoints (s0) of the state variables (s(t)) and also a stable combustion
process, a changeover is made from setpoint control to extraordinary
disturbance control.
6. A procedure according to Claim 5, characterized in that in the case of
extraordinary disturbance control, states are approached that are
matched to the triggering problems.
7. A procedure according to any of the preceding claims, characterized in
that several process models are used to evaluate the state variables (s(t))
and to select the actions (a1), in order to obtain short-term, medium-term
and long-term predictions for the state variables (s(t)).
8. A control loop for implementing a procedure according to one of the
preceding claims, in an installation (1), in particular in a power-
generating plant, a waste incinerator or a cement plant, having a
(controlled) system (3) for converting material (G) by means of the
combustion process, with air (L) being supplied, and at least one flame
body (F) being formed, and having at least one observation device (5)
imaging the flame body (F) and having further sensors (7) to determine
the state variables (s(t)) describing the state of the system in the
installation (1), and having a computer (11) to evaluate the state
variables (s(t)) and, if necessary, to select suitable actions (a1), and
having adjusting devices (9) that can be controlled by the actions (a1) to
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regulate at least the supply of material (G) and/or air (L), the computer (11) during setpoint control regulating the process to achieve setpoints (s0) of the state variables (s(t)) and/or stability of the combustion process, characterized in that the computer (11) changes occasionally from setpoint control to disturbance control and, according to the latter, selects actions (a1) in order to approach states of the system in the installation (1) at which the state variables (s(t)) deviate in a targeted manner, within predetermined limits (s1, Sh), from the optimal setpoint
(So)-
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9. A control loop according to Claim 8, characterized in that in the
computer (11) there is implemented at least one neuronal network which
in each case stores a process model for evaluating the state variables
(s(t)) and selecting the actions (a1).
10. A control loop according to Claim 9, characterized in that the computer
(11) contains several neuronal networks with process models for short-
term, medium-term and long-term predictions of the state variables
(s(t)), and/or with process models which compete with each other as
regards the quality of the predictions.

In a procedure for regulating a combustion process in an installation, in particular a power-generating plant, a waste incinerator or a cement plant, in which, while air is being supplied, material is converted by the combustion process, with at least one flame body 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 body, as well as other sensors, and are evaluated in a computer, whereupon any appropriate actions (a1) 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 according which actions (a1) are selected in order to approach states of the system in the installation at which the state variables (s(t)) deviate in a targeted manner, within predetermined limits, (s1, sh) from the optimal setpoint (s0)

" A PROCEDURE FOR REGULATING A COMBUSTION PROCESS IN AN INSTALLATION"

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