Author: claimsbot

What is claimed is:

1. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a time-invariant linear filter generating an error signal for feedback from an error signal generated using an output of the adaptive filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter using an error signal fed back from the time-invariant linear filter.
2. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a first time-invariant linear filter to which an output signal of the adaptive filter is inputted;
a second time-invariant linear filter generating an error signal for feedback from an error signal of an output of the first linear filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter using an error signal fed back from the second linear filter.
3. The digital filter according to claim 2, wherein
said second linear filter has filter coefficients obtained by inverting an order of filter coefficients of the first linear filter.
4. The digital filter according to claim 2, further comprising
a third linear filter generating a signal having a characteristic different from a characteristic of the first linear filter, from the output signal of said adaptive filter.
5. The digital filter according to claim 4, further comprising
a decision circuit detecting a phase error using an output signal of said third linear filter and generating a signal for timing recovery.
6. A digital filter, comprising
an adaptive filter having adaptively variable coefficients;
a decision circuit performing a linear operation using an output signal of the adaptive filter and generating an error signal of an obtained signal;
a time-invariant linear filter generating an error signal for feedback from the error signal generated by the decision circuit; and
a learning circuit adaptively learning the coefficients of the adaptive filter using an error signal fed back from the linear filter.
7. A digital filter, comprising
an adaptive filter having adaptively variable coefficients;
a decision circuit estimating a signal series of an input signal from an output signal of the adaptive filter by one of a maximum likelihood decision and a maximum a posteriori probability decision and generating an error signal; and
a learning circuit learning the coefficients of the adaptive filter using an error signal fed back from the decision circuit in such a way that an expected difference between a sum of squares of an output error signal series for a correct signal series and a sum of squares of an output error signal series in a case of a decision error increases.
8. The digital filter according to claim 7, further comprising
a linear filter having an impulse response corresponding to a self correlation function of an output error signal of said adaptive filter generated when the said decision circuit makes a decision error of a specific pattern and generating an error signal for feedback from the error signal generated by said decision circuit, wherein
said learning circuit learns the coefficients of said adaptive filter using the error signal generated by the linear filter.
9. The digital filter according to claim 8, wherein
the specific pattern is an error pattern in which an error is most easily committed and is determined by an input signal and an ideal output signal of said adaptive filter.
10. The digital filter according to claim 8, wherein
the specific pattern is a single bit error pattern.
11. The digital filter according to claim 8, wherein
the error signal is fed back to said learning circuit from the linear filter only if a signal series after a decision causes the specific pattern.
12. The digital filter according to claim 7, wherein
said learning circuit learns the coefficients of said adaptive filter in such a way that a weighted average of the expected difference between the sums of squares of an error for a plurality of error patterns increases.
13. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a first linear filter to which an output signal of the adaptive filter is inputted;
a decision circuit estimating a signal series of an input signal from an output signal of the first linear filter by one of a maximum likelihood decision and a maximum a posteriori probability decision and generating an error signal;
a second linear filter having an impulse response corresponding to a self correlation function of an output error signal of the adaptive filter generated when the decision circuit makes a decision error of a specific pattern and to which the error signal generated by the decision circuit is inputted;
a third linear filter generating an error signal for feedback from an output signal of the second linear filter; and
a learning circuit learning the coefficients of the adaptive filter using an error signal fed back from the third linear filter in such a way that an expected difference between a sum of squares of an output error signal series for a correct signal series and a sum of squares of an output error signal series in a case of a decision error increases.
14. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a first linear filter to which an output signal of the adaptive filter is inputted;
a decision circuit estimating a signal series of an input signal from an output signal of the first linear filter by one of a maximum likelihood decision and a maximum a posteriori probability decision and generating an error signal;
a second linear filter to which the error signal generated by the decision circuit is inputted;
a third linear filter having an impulse response corresponding to a self correlation function of an output error signal of the adaptive filter generated when the decision circuit makes a decision error of a specific pattern and generating an error signal for feedback from an output signal of the second linear filter;
a learning circuit learning the coefficients of the adaptive filter using an error signal fed back from the third linear filter in such a way that an expected difference between a sum of squares of an output error signal series for a correct signal series and a sum of squares of an output error signal series in a case of a decision error increases.
15. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a first linear filter to which an output signal of the adaptive filter is inputted;
a decision circuit estimating a signal series of an input signal from an output signal of the first linear filter by one of a maximum likelihood decision and a maximum a posteriori probability decision and generating an error signal;
a second linear filter having a transfer characteristic expressed by a product of a filter characteristic obtained by inverting an order of filter coefficients of the first linear filter and an impulse response corresponding to a self correlation function of an output error signal of the adaptive filter generated when the decision circuit commits a decision error of a specific pattern, and generating an error signal for feedback from the error signal generated by the decision circuit;
a learning circuit learning the coefficients of the adaptive filter using an error signal fed back from the second linear filter in such a way that an expected difference between a sum of squares of an output error signal series for a correct signal series and a sum of squares of an output error signal series in a case of a decision error increases.
16. A digital filter, comprising
an adaptive filter having adaptively variable coefficients;
an interpolation filter interpolating an output signal of the adaptive filter and generating a signal in a prescribed timing;
an inverse interpolation filter having filter coefficients obtained by inverting an order of one of interpolation coefficients corresponding to an output of the interpolation filter and approximate values of the interpolation coefficients, and generating an error signal in timing before interpolation by inversely interpolating an error signal of the output of the interpolation filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter using an error signal fed back from the inverse interpolation filter.
17. The digital filter according to claim 16, wherein
said inverse interpolation filter has filter coefficients obtained by inverting an order of a plurality of coefficients of a large absolute value of the interpolation coefficients.
18. The digital filter according to claim 16, wherein
said inverse interpolation filter has filter coefficients obtained by inverting an order of two coefficients of a large absolute value of the interpolation coefficients.
19. The digital filter according to claim 16, wherein
said inverse interpolation filter has filter coefficients obtained by inverting an order of coefficients obtained by linearly approximating two coefficients of a large absolute value of the interpolation coefficients with respect to interpolation phase.
20. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
an interpolation filter interpolating an output signal of the adaptive filter and generating a signal in a prescribed timing;
a first linear filter to which an output signal of the interpolation filter is inputted;
a second linear filter to which an error signal of an output of the first linear filter is inputted;
an inverse interpolation filter having filter coefficients obtained by inverting an order of one of interpolation coefficients corresponding to an output of the interpolation filter and approximate values of the interpolation coefficients, and generating an error signal in timing before interpolation by inversely interpolating an output signal of the second linear filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter using an error signal fed back from the inverse interpolation filter.
21. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
an interpolation filter interpolating an output signal of the adaptive filter and generating a signal in a prescribed timing;
a decision circuit performing a linear operation using an output signal of the interpolation filter and generating an error signal of an obtained signal;
a linear filter to which the error signal generated by the decision circuit is inputted;
an inverse interpolation filter having filter coefficients obtained by inverting an order of one of interpolation coefficients corresponding to an output of the interpolation filter and approximate values of the interpolation coefficients, and generating an error signal in timing before interpolation by inversely interpolating an output signal of the linear filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter using an error signal fed back from the inverse interpolation filter.
22. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a decision circuit generating an error signal of an output of the adaptive filter;
a linear filter generating an effective input signal from an input signal of the adaptive filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter by correlating the effective input signal from the linear filter to an error signal fed back from the decision circuit.
23. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a decision circuit performing a linear operation using an output signal of the adaptive filter and generating an error signal of an obtained signal;
a linear filter generating an effective input signal from an input signal of the adaptive filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter by correlating the effective input signal from the linear filter to an error signal fed back from the decision circuit.
24. The digital filter according to claim 23, wherein
said linear filter has one of a characteristic equivalent to a remaining part obtained by eliminating a transfer characteristic of the adaptive filter from a transfer characteristic of a route between the input signal of the adaptive filter and the signal obtained by the linear operation, and a characteristic obtained by approximating the remaining part.
25. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a first linear filter to which an output signal of the adaptive filter is inputted;
a decision circuit performing a linear operation using an output signal of the adaptive filter and generating an error signal of an obtained signal;
a second linear filter generating an effective input signal from an input signal of the adaptive filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter by correlating the effective input signal from the second linear filter to an error signal fed back from the decision circuit.
26. A digital filter, comprising:
an adaptive filter having adaptively variable coefficients;
a decision circuit performing a linear operation using an output signal of the adaptive filter and generating an error signal of an obtained signal;
a first linear filter generating an error signal for feedback from the error signal generated by the decision circuit;
a second linear filter generating an effective input signal from an input signal of the adaptive filter; and
a learning circuit adaptively learning the coefficients of the adaptive filter by correlating the effective input signal from the second linear filter to an error signal fed back from the first linear filter.
27. The digital filter according to claim 26, wherein
a product of a transfer characteristic of the first linear filter and a transfer characteristic of the second linear filter is expressed by one of a remaining characteristic obtained by eliminating a transfer characteristic of the adaptive filter from a transfer characteristic of a route between the input signal of the adaptive filter and the signal obtained by the linear operation, and a characteristic obtained by approximating the remaining part.
28. A digital filter, comprising:
a fixed-coefficient filter having filter coefficients determined by a simulation that provides a digital filter model, which learns coefficients of an adaptive filter having adaptively variable coefficients by feeding back an error signal generated using an output of the adaptive filter through a time-invariant linear filter, with an input signal of a specific statistical property and conducts coefficient learning; and
a learning circuit estimating a signal series of an input signal from an output signal of the fixed-coefficient filter.
29. A digital filter, comprising:
an adaptive filter means having adaptively variable coefficients;
a time-invariant linear filter means for generating an error signal for feedback from an error signal generated using an output of the adaptive filter means; and
a learning circuit means for adaptively learning the coefficients of the adaptive filter means using an error signal fed back from the time-invariant linear filter means.
30. A digital filter, comprising
an adaptive filter means having adaptively variable coefficients;
an interpolation filter means for interpolating an output signal of the adaptive filter means and generating a signal in a prescribed timing;
an inverse interpolation filter means having filter coefficients obtained by inverting an order of one of interpolation coefficients corresponding to an output of the interpolation filter means and approximate values of the interpolation coefficients, and generating an error signal in timing before interpolation by inversely interpolating an error signal of the output of the interpolation filter means; and
a learning circuit means for adaptively learning the coefficients of the adaptive filter means using an error signal fed back from the inverse interpolation filter means.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

1. A method for controlling a hydraulic system adapted to perform at least one hydraulic work function in a working machine (1), wherein the hydraulic system performs the hydraulic control function in accordance with an operation signal (F) determined by a hydraulic system control unit (24), comprising the steps of:
the control unit (24) receiving an operator control input (a) associated to said work function, characterized in that
the control unit receiving a load input (L) indicative of a load associated to the work function,
the control unit determining the operation signal (F) in response to the operator control input (a) and the load input (L).
2. A method according to claim 1 wherein a relationship between the load input (L) and the operation signal (F) is determined so that an increased load input value (L) results in a reduced operation signal value (F).
3. A method according to claim 2 wherein the increased load input value (L) results in a reduced operation signal value (F) within a first control range of the operator control input (a), the first control range being smaller than the total operating range of the control input (a).
4. A method according to any of the claims 1-3 wherein a relationship between the load input (L) and the operation signal (F) is linear over the total operating range of the operator control input (a).
5. A method according to any of the claims 1-3 wherein a relationship between the load input (L) and the operation signal (F) is non-linear over the total operating range of the operator control input (a).
6. A method according to any of the claims 1-3 wherein a relationship between the load input (L) and the operation signal (F) is linear in at least a first interval of the load input value (L) and non-linear in a second interval of the load input value (L) for a particular value of the operator control input (a).
7. A method according to any of the preceding claims wherein a relationship between the load input (L) and the operation signal (F) in terms of gradient or slope is the same for different values of the operator control input (a).
8. A method according to any of the claims 1-6 wherein a relationship between the load input (L) and the operation signal (F) in terms of gradient or slope varies for different values of the operator control input (a).
9. Method according to any of the preceding claims wherein a relationship between the load input (L) and the operation signal (F) is defined in a control map in the hydraulic system control unit (24).
10. A method according to any of the preceding claims wherein the operator control input (a) corresponds to an angle of an operation lever.
11. A method according to any of the preceding claim wherein a relationship between the load input (L) and the operation signal (F) for a particular operator control input value (a) is dependent on an operating state of the working machine (1).
12. A method according to any of the preceding claims wherein the load input (L) is determined on the basis of a load indicating signal.
13. A method according to any of the preceding claims wherein the control unit (25) determines a load change in the work function during operation on the basis of repeated load inputs (L).
14. A method according to claim 13 wherein the control unit (24) changes the desired speed of the work function in response to the determined load change.
15. A hydraulic system control unit (24) being adapted to perform any of the method steps according to any of the claims 1-14.
16. A hydraulic system (17) comprising a hydraulic system control unit (24) according to claim 15.
17. A working machine (1) comprising a hydraulic system according to claim 16.

1. A shelf stable peroxycarboxylic acid composition comprising:
(a) about 0.005 wt-% to about 0.2 wt-% of a C1-C4 short chain peroxycarboxylic acid;
(b) about 1 wt-% to about 5 wt-% hydrogen peroxide;
(c) about 0.01 wt-% to about 0.3 wt-% of a protonated C6-C12 medium chain carboxylic acid;
(d) about 0.5 wt-% to about 3.5 wt-% of a protonated C1-C4 short chain carboxylic acid;
(e) about 0.01 wt-% to about 2 wt-% buffer;
(f) about 70 wt-% to about 99 wt-% water;
(g) about 0.01 wt-% to about 5 wt-% nonionic surfactant;
(h) about 0.01 to about 3 wt-% sequestrant comprising a phosphonic acid, phosphonate salt, or combinations of the same; and
(i) about 0.01 wt-% to about 0.25 wt-% triazole corrosion inhibitor;
wherein:
the composition is free of added mineral acid;
the pH of the composition is about 1 to about 4;
the ratio of hydrogen peroxide:peroxycarboxylic acid in the composition is about 30:1 to about 60:1;
the ratio of hydrogen peroxide:protonated carboxylic acid in the composition is about 1:1 to about 2:1; and
wherein the composition is stable such that greater than 85% of the initial concentration of peroxycarboxylic acid remains after 1 year of storage at room temperature.
2. The composition of claim 1, comprising: about 0.015 wt-% to about 0.15 wt-% C1-C4 short chain peroxycarboxylic acid; and about 1 wt-% to about 3 wt-% protonated C1-C4 short chain carboxylic acid.
3. The composition of claim 1, comprising: about 0.01 wt-% to about 0.25 wt-% protonated C6-C12 medium chain carboxylic acid.
4. The composition of claim 1, further comprising a hydrotrope.
5. The composition of claim 1, the buffer comprising phosphate salt, citrate salt, formate salt, malate salt, or acetate salt.
6. The composition of claim 1, the buffer being an acetate salt.
7. The composition of claim 1, comprising about 0.01 wt-% to about 0.2 wt-% of the triazole corrosion inhibitor.
8. The composition of claim 1, comprising about 0.04 wt-% to about 0.08 wt-% of the triazole corrosion inhibitor.
9. The composition of claim 8, wherein the corrosion inhibitor comprises benzotriazole.
10. The composition of claim 1, further comprising about 0.01 to about 1 wt-% masking agent, the masking agent being chemically stable the composition for at least about 6 months at room temperature.
11. A low corrosion peroxycarboxylic acid composition comprising:
(a) about 0.015 wt-% to about 0.15 wt-% of a C1-C4 short chain peroxycarboxylic acid;
(b) about 2 wt-% to about 4 wt-% hydrogen peroxide;
(c) about 0.01 wt-% to about 0.3 wt-% of a protonated C6-C12 medium chain carboxylic acid;
(d) about 0.5 wt-% to about 3.5 wt-% of a protonated C1-C4 short chain carboxylic acid;
(e) about 0.01 wt-% to about 2 wt-% buffer;
(f) about 70 wt-% to about 99 wt-% water;
(g) about 0.01 wt-% to about 0.25 wt-% corrosion inhibitor comprising a trazole;
(h) about 0.01 wt-% to about 4 wt-% nonionic surfactant;
(i) about 0.01 to about 3 wt-% sequestrant comprising a phosphonic acid, phosphonate salt, or combinations of the same;
wherein:
the ratio of hydrogen peroxide:peroxycarboxylic acid in the composition is about 30:1 to about 60:1; and the ratio of hydrogen peroxide:protonated carboxylic acid in the composition is about 1:1 to about 2:1;
the composition is free of added mineral acid;
the pH of the composition is about 1 to about 4; and
wherein the composition is stable such that greater than 85% of the initial concentration of peroxycarboxylic acid remains after 1 year of storage at room temperature.
12. The composition of claim 11, comprising about 0.01 wt-% to about 0.2 wt-% of the corrosion inhibitor.
13. The composition of claim 11, wherein the corrosion inhibitor comprises benzotriazole.
14. The composition of claim 11, wherein the buffer comprises a phosphate salt, citrate salt, formate salt, malate salt, or acetate salt.
15. The composition of claim 11, wherein the buffer being an acetate salt.
16. The composition of claim 11, comprising: about 0.02 wt-% to about 0.12 wt-% C1-C4 short chain peroxycarboxylic acid; and about 1 wt-% to about 3 wt-% protonated C1-C4 short chain carboxylic acid.
17. The composition of claim 11, comprising: about 0.01 wt-% to about 0.25 wt-% protonated C6-C12 medium chain carboxylic acid.
18. The composition of claim 11, further comprising a hydrotrope.
19. The composition of claim 11, wherein the composition causes less than 200 mil per year corrosion of brass.
20. The composition of claim 11, further comprising about 0.01 to about 1 wt-% masking agent, the masking agent being chemically stable the composition for at least about 6 months at room temperature.
21. A method of reducing the population of bacterial endospores, comprising:
contacting bacterial endospores with a composition comprising:
(a) about 0.0005 wt-% to about 0.2 wt-% of a C1-C4 short chain peroxycarboxylic acid;
(b) about 1 wt-% to about 5 wt-% hydrogen peroxide;
(c) about 70 wt-% to about 99 wt-% water;
(d) about 0.01 wt-% to about 0.3 wt-% of a protonated C6-C12 medium chain carboxylic acid;
(e) about 0.5 wt-% to about 3.5 wt-% of a protonated C1-C4 short chain carboxylic acid;
(f) about 0.01 wt-% to about 2 wt-% buffer;
(f) about 0.01 wt-% to about 5 wt-% nonionic surfactant;
(h) about 0.01 to about 3 wt-% sequestrant comprising a phosphonic acid, phosphonate salt, or combinations of the same; and
(i) about 0.01 wt-% to about 0.25 wt-% benzotriazole corrosion inhibitor;
wherein: the composition is free of added mineral acid;
the pH of the composition is about 1 to about 4;
the ratio of hydrogen peroxide:peroxycarboxylic acid in the composition is about 30:1 to about 60:1;
the composition is stable such that greater than 85% of the initial concentration of peroxycarboxylic acid remains after 1 year of storage at room temperature; and
the ratio of hydrogen peroxide:protonated carboxylic acid in the composition is about 1:1 to about 2:1; and
achieving greater than 5 log reduction in the population of bacterial endospores in less than 1 hour under ambient conditions.

The claims below are in addition to those above.
All refrences to claim(s) which appear below refer to the numbering after this setence.

What is claimed is:

1. A processor unit for executing an event process in response to occurrence of a plurality of predetermined events, comprising:
a program for executing an event process in response to occurrence of said plurality of predetermined events, said processor unit,
wherein said program comprises:
a plurality of tasks each of which includes at least one event process which is executed in response to occurrence of one of said plurality of predetermined events;
an activation request program for requesting activation of a task which includes an event process corresponding to an event in response to occurrence of said event; and
a real time operating system for activating said task in response to the request for activation of said task,

wherein said activation request program stores identification information on said event process corresponding to said event in a storage area in response to occurrence of said event, if said task includes an event process other than said event process corresponding to said event,
wherein said task, which is activated by said real time operating system, obtains the identification information on said event process from said storage area if said task includes a plurality of event processes, and executes said event process corresponding to the obtained identification information, and
wherein at least one specific event is selected from said plurality of predetermined events, and an event process corresponding to said specific event is included in a dedicated task, which is created as one of said plurality of tasks for executing only one event process, so that said dedicated task identifies the event process corresponding to the specific event for execution without obtaining identification information from said storage area when said dedicated task is activated.
2. A processor unit as in claim 1,
wherein one of a plurality of priority levels is assigned to each of said plurality of tasks and said event process included therein, and a same priority level is assigned to a task and an event process included therein, and
wherein said real time operating system activates said task in response to the request for activation of said task if a priority level of said task is higher than a priority level of an active task.
3. A processor unit as in claim 1,
wherein a cyclic event which occurs in a cycle is selected as said specific event.
4. A processor unit as in claim 1,
wherein said processor unit executes an event process in response to the occurrence of one of said plurality of predetermined events for controlling a predetermined object, and
wherein a cyclic event which occurs in synchronous with a run cycle of said predetermined object is selected as said specific event.
5. A processor unit as in claim 1,
wherein an event, which is not eliminated from said plurality of predetermined events when a system in which said processor unit is incorporated is modified, is selected as said specific event.
6. A processor unit as in claim 1,
wherein an event, in response to which it is unnecessary that said activation request program passes data to a task which includes a corresponding event process, is selected as said specific event.
7. A processor unit as in claim 1,
wherein a shared task of a priority level is created for each of said plurality of priority levels, and said shared task includes at least one event process which is assigned a priority level same as a priority level of said shared task and is other than said specific event.
8. A processor unit as in claim 4,
wherein said predetermined object controlled by said processor unit is an engine of a vehicle.
9. A processor unit as in claim 8,
wherein the cyclic event selected as said specific event is an event which occurs in synchronous with an engine cycle.
10. A record medium which stores a program for executing an event process in response to occurrence of a plurality of predetermined events,
wherein said program comprises:
a plurality of tasks each of which includes at least one event process which is executed in response to occurrence of one of said plurality of predetermined events, wherein one of a plurality of priority levels is assigned to each of said plurality of tasks and said event process and a same priority level is assigned to a task and an event process included therein;
an activation request program for requesting activation of a task which includes an event process corresponding to an event in response to occurrence of the event; and
a real time operating system for activating said task in response to the request for activation of said task,

wherein said activation request program stores identification information on said event process corresponding to said event in a queue in response to occurrence of said event, if said task includes an event process other than said event process corresponding to said event,
wherein said task, which is activated by said real time operating system, obtains the identification information on said event process from said queue if said task includes a plurality of event processes, and executes said event process corresponding to the obtained identification information, and
wherein at least one specific event is selected from said plurality of predetermined events, and a event process corresponding to the specific event is included in a dedicated task, which is created as one of said plurality of tasks for executing only one event process, so that said dedicated task identifies the event process corresponding to the specific event for execution without obtaining identification information from said queue when said dedicated task is activated.
11. A system for executing event processes in response to occurrence of a plurality of predetermined events, comprising:
a central processor unit (CPU); and
memory means coupled to said CPU, said memory means including software means executed by said CPU,
wherein said software means comprises:
a plurality of tasks each of which includes at least one event process, wherein one of a plurality of priority levels is assigned to each of said plurality of tasks and said event process, and a same priority level is assigned to a task and an event process included therein;
an activation request program for requesting activation of a task which includes an event process corresponding to an event in response to occurrence of said event; and
a real time operating system for activating said task in response to the request for activation of said task if a priority level of said task is higher than a priority level of an active task,

wherein said activation request program stores identification information on said event process corresponding to said event in an area of said memory means in response to occurrence of said event, if said task includes an event process other than said event process corresponding to said event,
wherein said task, which is activated by said real time operating system, obtains the identification information on said event process from said area of said memory means if said task includes a plurality of event processes, and executes said event process corresponding to the obtained identification information, and
wherein at least one specific event is selected from said plurality of predetermined events, and an event process corresponding to said specific event is included in a dedicated task, which is created as one of said plurality of tasks for executing only one event process, so that said dedicated task identifies the event process corresponding to the specific event for execution without obtaining identification information from said area of said memory means when said dedicated task is activated.
12. A method for executing an event process in real time on a computer in response to one of a plurality of predetermined events, said method comprising the steps of:
creating a plurality of tasks and assigning one of a plurality of priority levels to each of said plurality of tasks;
creating a plurality of event processes corresponding to said plurality of predetermined events and assigning one of said plurality of priority levels to each of said plurality of event processes;
dividing said plurality of event processes into said plurality of tasks so that each of said plurality of event processes is included in a task of a priority level same as a priority level of the event process;
requesting activation of a task which includes an event process corresponding to an event in response to occurrence of said event;
storing an ID of said event process in a queue in response to occurrence of said event if said task in which said event process is included includes an event process other than said event process;
activating said task if a priority level of said task is higher than a priority level of an active task;
said task obtaining the ID of said event process from said queue and identifying said event process based on the obtained ID if said task is activated; and
said task executing said identified event process,
wherein at least one specific event is selected from said plurality of predetermined events, and an event process corresponding to said specific event is included in a dedicated task, which is created at said creating step as one of said plurality of tasks for executing only one event process, so that said dedicated task identifies the event process corresponding to said specific event for execution without obtaining an ID of the event process from said queue when said dedicated task is activated.