Pitch angle control method and device and electronic equipment

Abstract

The invention provides a pitch angle control method and device and electronic equipment, and relates to the technical field of intelligent control, and the pitch angle control method comprises the steps: obtaining historical data, and training a prediction model according to the historical data; collecting data at the current moment, inputting the data at the current moment into the trained prediction model, and outputting prediction data; and determining a target function based on the prediction data, and controlling the pitch angle according to the target function. According to the method, the target function is constructed, and the variable quantity of the pitch angle is determined when the target function is minimum to control the pitch angle, so that the pitch angle controller achieves the purposes of smooth output, generator power stabilization and mechanical load reduction, and a better multi-target optimization control effect is achieved.

Description

Technical Field

[0001] The present application relates to the field of intelligent control technology, and in particular to a pitch angle control method, device and electronic equipment. Background Art

[0002] The ultimate goal of offshore wind turbine optimization control is multi-objective coordinated optimization, that is, to achieve the comprehensive optimization of increasing power generation, smoothing output power and reducing load. The existing control strategy cannot always take into account the two optimization objectives of maximum power point tracking performance and power smoothing in the speed change section, and the coordinated control effect is poor. Summary of the invention

[0003] Embodiments of the present application provide a pitch angle control method, device, and electronic device.

[0004] The first embodiment of the present application provides a pitch angle control method, including:

[0005] Acquire historical data, and train a prediction model based on the historical data;

[0006] Collecting data at the current moment, inputting the data at the current moment into the trained prediction model, and outputting prediction data;

[0007] An objective function is determined based on the prediction data, and the pitch angle is controlled according to the objective function.

[0008] In one embodiment of the present application, determining an objective function based on the predicted data, and controlling the pitch angle according to the objective function includes:

[0009] Construct an objective function according to the control objective;

[0010] When the objective function is minimum, determining the pitch angle change;

[0011] The pitch angle is controlled based on the pitch angle change amount.

[0012] In one embodiment of the present application, the parameter value includes one or more of generator speed, generator torque and pitch angle action acceleration, and the control target includes one or more of smooth output, stable generator speed and reduced mechanical load.

[0013] In one embodiment of the present application, the training of the prediction model based on the history includes:

[0014] For any sampling moment, determining the predicted data at said any sampling moment;

[0015] Obtaining actual output data at any sampling moment;

[0016] Determining a prediction error based on the actual output data and the predicted data;

[0017] The prediction model is corrected and trained according to the prediction error, and when the prediction error is minimum, a prediction model that has been trained is determined.

[0018] In one embodiment of the present application, determining an objective function based on the predicted data, and controlling the pitch angle according to the objective function includes:

[0019] Determining the generator speed, generator torque and pitch angle action acceleration according to the predicted data;

[0020] An objective function is constructed based on the generator speed, the generator torque and the pitch angle action acceleration.

[0021] In one embodiment of the present application, the method further includes:

[0022] A sampling period is preset, and in each sampling period, a control variable is obtained, and a first control variable is input into a prediction model to complete the prediction control of the sampling period.

[0023] In one embodiment of the present application, the method further includes:

[0024] A discretized state space equation is obtained, and the discretized state space equation is used as a prediction model.

[0025] The second aspect of the present application provides a pitch angle control device, including:

[0026] A first acquisition module acquires historical data and trains a prediction model based on the historical data;

[0027] An output module, used to collect data at the current moment, input the data at the current moment into the trained prediction model, and output the predicted data;

[0028] A control module is used to determine an objective function based on the predicted data and control the pitch angle according to the objective function.

[0029] In one embodiment of the present application, the control module includes:

[0030] Determining one or more parameter values ​​based on the predicted data;

[0031] constructing the objective function based on the one or more parameter values ​​and the control objective;

[0032] When the objective function is minimum, determining the pitch angle change;

[0033] The pitch angle is controlled based on the pitch angle change amount.

[0034] In one embodiment of the present application, the control objectives include at least one or more of: smooth output, stable generator speed, and reduced mechanical load.

[0035] In one embodiment of the present application, the first acquisition module includes:

[0036] For any sampling moment, determining the predicted data at said any sampling moment;

[0037] Obtaining actual output data at any sampling moment;

[0038] Determining a prediction error based on the actual output data and the predicted data;

[0039] The prediction model is corrected and trained according to the prediction error, and when the prediction error is minimum, a prediction model that has been trained is determined.

[0040] In one embodiment of the present application, the control module includes:

[0041] Determining a predicted generator speed, a predicted generator torque, and a predicted pitch angle action acceleration according to the predicted data;

[0042] An objective function is constructed based on the predicted generator speed, the predicted generator torque and the predicted pitch angle action acceleration.

[0043] In one embodiment of the present application, the device further includes:

[0044] A sampling period is preset, and in each sampling period, a control variable is obtained, and a first control variable is input into a prediction model to complete the prediction control of the sampling period.

[0045] In one embodiment of the present application, the device further includes:

[0046] A discretized state space equation is obtained, and the discretized state space equation is used as a prediction model.

[0047] The third aspect embodiment of the present application proposes an electronic device, comprising: a processor; a memory for storing instructions executable by the processor; wherein the processor is configured to execute the instructions to implement the pitch angle control method proposed in the first aspect embodiment of the present application.

[0048] The fourth aspect embodiment of the present application proposes a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor of an electronic device, the electronic device can execute the method proposed in the first aspect embodiment of the present application.

[0049] The fifth aspect embodiment of the present application proposes a computer program product, including a computer program, which implements the method proposed in the first aspect embodiment of the present application when executed by a processor in a communication device.

[0050] The technical solution provided by the embodiments of the present application brings at least the following beneficial effects:

[0051] In an embodiment of the present application, the prediction data for each subsequent moment is acquired in advance through the prediction model, the pitch angle is controlled by the prediction data, and the objective function is used to continuously optimize and adjust in this process to obtain a more accurate pitch angle control value for pitch angle control, and the tracking performance of the maximum power point tracking and power smoothing and other optimization objectives can be taken into account in the speed change section to achieve better control purposes.

[0052] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0054] Figure 1 A schematic diagram of a flow chart of a pitch angle control method provided in an embodiment of the present application;

[0055] Figure 1A A structural diagram of a model predictive control system provided in an embodiment of the present application;

[0056] Figure 1B A structural block diagram of a predictive control algorithm provided in an embodiment of the present application;

[0057] Figure 1C A basic principle diagram of a model predictive control algorithm provided in an embodiment of the present application;

[0058] Figure 2 A schematic flow chart of another pitch angle control method provided in an embodiment of the present application;

[0059] Figure 3 A schematic diagram of the structure of a pitch angle control device provided in an embodiment of the present application;

[0060] Figure 4 A schematic diagram of the structure of an electronic device provided according to an embodiment of the present application;

[0061] Figure 5 It is a schematic diagram of the structure of another electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0062] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the embodiments of the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the embodiments of the present application as detailed in the appended claims.

[0063] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the embodiments of the present application. The singular forms of "a" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0064] It should be understood that, although the terms first, second, third, etc. may be used to describe various information in the embodiments of the present application, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the embodiments of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the words "if" and "if" as used herein may be interpreted as "at..." or "when..." or "in response to determination".

[0065] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0066] It should be noted that the pitch angle control method provided in any embodiment of the present application can be executed alone, or can be executed in combination with possible implementation methods in other embodiments, or can be executed in combination with any technical solution in the related technology.

[0067] The pitch angle control method, device and electronic device of the embodiments of the present application are described below with reference to the accompanying drawings.

[0068] Figure 1 A schematic diagram of a pitch angle control method provided in an embodiment of the present application. Figure 1 As shown, the method includes but is not limited to the following steps:

[0069] S101, obtaining historical data, and training a prediction model based on the historical data.

[0070] like Figure 1A As shown, it is a structural diagram of the model predictive control control system. The system nominal model calculates the performance indicators based on the estimated state, considering the optimization algorithm and system constraints, and then obtains the output sequence of the system.

[0071] It is understandable that the basic idea of ​​model predictive control is to use the past, present and future information of the controlled object to predict the behavior characteristics of the model in the future. The main structure of the predictive control algorithm is as follows: Figure 1B shown.

[0072] In some implementations, the model predictive control algorithm continuously calculates the objective function online and optimizes it to determine the optimal control quantity. Figure 1C As shown in Figure 1, rolling calculation is to calculate the system output at multiple subsequent moments in each sampling period and make it close to the reference trajectory to achieve the purpose of good prediction. In other words, the prediction model is trained based on the historical data of the controlled object.

[0073] Alternatively, the prediction model may be a conventional long short-term memory network or a state-space model of a discrete-time system.

[0074] In some implementations, the nominal model can be corrected online through error feedback. That is, during the training process of the prediction model, the prediction model is corrected online to improve the anti-interference ability of the prediction model.

[0075] S102, collecting data at the current moment, inputting the data at the current moment into the trained prediction model, and outputting predicted data.

[0076] At some time, data at the current moment is collected as input data, the input data is input into the trained prediction model, and the prediction data is output.

[0077] In some implementations, the predicted data may be data at the next moment after the current moment, or data at multiple moments after the current moment.

[0078] S103, determining an objective function based on the predicted data, and controlling the pitch angle according to the objective function.

[0079] Determine the prediction data, that is, determine the output at each moment in the future. According to the prediction data, the pitch angle can be compensated, that is, the pitch angle can be controlled.

[0080] It is understandable that the goal of pitch angle control is to smooth output, stabilize generator speed, and reduce mechanical load, etc. Therefore, a corresponding objective function can be constructed based on the goal of the pitch angle controller. When the objective function meets the preset conditions, the pitch angle control amount in the objective function is determined. The pitch angle is controlled by the pitch angle control amount at this time to achieve a more accurate control purpose.

[0081] In an embodiment of the present application, the prediction data for each subsequent moment is acquired in advance through the prediction model, the pitch angle is controlled by the prediction data, and the objective function is used to continuously optimize and adjust in this process to obtain a more accurate pitch angle control value for pitch angle control, and the tracking performance of the maximum power point tracking and power smoothing and other optimization objectives can be taken into account in the speed change section to achieve better control purposes.

[0082] Figure 2 A schematic diagram of another method for controlling a pitch angle provided in an embodiment of the present application. Figure 2 As shown, the method includes but is not limited to the following steps:

[0083] S201, obtaining historical data, and training a prediction model based on the historical data.

[0084] In some implementations, for any sampling moment, the prediction data at any sampling moment is determined; the actual output data at any sampling moment is obtained; the prediction error is determined based on the actual output data and the prediction data; the prediction model is corrected and trained based on the prediction error, and when the prediction error is minimized, the trained prediction model is determined to be complete.

[0085] Understandably, the prediction error is:

[0086]

[0087] Among them, e(k+1) is the prediction error at time k+1; is the predicted value at time k+1; y(k+1) is the actual value at time k+1.

[0088] Since y(k+1) cannot be obtained, the approximation at the current moment can be used instead:

[0089]

[0090] Introducing error feedback to obtain closed-loop prediction:

[0091]

[0092] Where h is the feedback coefficient.

[0093] In some implementations, a sampling period may be preset, and in each sampling period, a control variable is obtained, and the first control variable is input into the prediction model to complete the prediction control of the sampling period.

[0094] Optionally, a discretized state space equation may be obtained and used as a prediction model.

[0095] It can be understood that the expression of the discretized state space equation is:

[0096] x(k+1)=Ax(k)+Bu(k)

[0097] y(k)=Cx(k)

[0098] Among them, the system variables satisfy the constraints

[0099] In the embodiment of the present application, the implementation method of step S201 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0100] S202, collecting data at the current moment, inputting the data at the current moment into the trained prediction model, and outputting predicted data.

[0101] In the embodiment of the present application, the implementation method of step S202 can be implemented by any of the methods in the embodiments of the present disclosure, which is not limited here and will not be repeated.

[0102] S203: Determine one or more parameter values ​​according to the predicted data.

[0103] Optionally, the parameter values ​​may be a generator speed, a generator torque, and a pitch angle action acceleration; therefore, a predicted generator speed, a predicted generator torque, and a predicted pitch angle action acceleration may be determined based on the prediction data.

[0104] Above the rated wind speed, the generator power is the rated power, and the generator torque setting value is inversely proportional to the generator speed, which can be expressed as:

[0105]

[0106] in, Indicates rated power; ω g Indicates the generator speed; Indicates the generator torque reference value.

[0107] S204: construct an objective function based on one or more parameter values ​​and a control objective.

[0108] The main purpose of the pitch angle controller is to smooth the output, stabilize the generator speed and reduce the mechanical load. When the generator speed reaches the rated speed, the generator power is also stabilized at the rated power. Optionally, the generator speed fluctuation and the axial load of the rotating shaft can be used as evaluation indicators to construct an objective function, which is as follows:

[0109]

[0110] Among them, J represents the value of the objective function; Q1, Q2, and Q3 represent different weight coefficients respectively; Indicates rated speed; ω g (k+i) represents the speed at the k+ith moment, which is the predicted value output by the prediction model; T shaft (k+i) represents the generator torque at the k+ith moment, which is the predicted value output by the prediction model; Δβ(k+i) represents the pitch angle action acceleration at the k+ith moment, which is the predicted value output by the prediction model; N c Indicates the total number of sampling moments in the prediction time domain.

[0111] Optionally, the constraints in the objective function are specifically:

[0112]

[0113]

[0114] 0≤β(k+i)≤β max

[0115] β min ≤Δβ(k+i)≤Δβ max

[0116] It can be understood that the above constraints are respectively the wind rotor speed constraint, the generator electromagnetic torque amplitude constraint, the pitch angle amplitude constraint and the pitch angle motion acceleration constraint.

[0117] S205, when the objective function is minimum, determining the pitch angle change.

[0118] Since the main purpose of the pitch angle controller is to smooth the output, stabilize the generator speed and reduce the mechanical load, the pitch angle change is determined when the objective function is minimum, that is, the pitch angle action acceleration.

[0119] It can be understood that the smaller the difference between the current speed and the rated speed, the more stable the speed of the generator and the better the power smoothing effect. Correspondingly, the smaller the mechanical load, the smaller the output increment, which means that the less mechanical load and the smaller the output increment, the more stable the output. In other words, when the objective function is smaller, the pitch angle controller achieves the purpose of smoothing the output, stabilizing the generator power and reducing the mechanical load.

[0120] S206: Control the pitch angle based on the pitch angle change.

[0121] After determining the change in the pitch angle, the pitch angle is controlled and adjusted based on the change in the pitch angle to ensure a better control effect of the pitch angle.

[0122] In an embodiment of the present application, by constructing an objective function, the pitch angle change is determined to perform pitch angle control when the objective function is minimum, so that the pitch angle controller can achieve the purpose of smooth output, stable generator power and reduced mechanical load, thereby achieving a better multi-objective optimization control effect.

[0123] Figure 3 Schematic diagram of the structure of a pitch angle control device provided in an embodiment of the present application. Figure 3 As shown, the pitch angle control device 300 comprises:

[0124] The first acquisition module 301 acquires historical data and trains a prediction model based on the historical data;

[0125] Output module 302, used to collect data at the current moment, input the data at the current moment into the trained prediction model, and output the predicted data;

[0126] The control module 303 is used to determine the objective function based on the predicted data, and control the pitch angle according to the objective function.

[0127] In some implementations, the control module 303 includes:

[0128] determining one or more parameter values ​​based on the predicted data;

[0129] constructing the objective function based on one or more parameter values ​​and a control objective;

[0130] When the objective function is minimum, determine the pitch angle change;

[0131] The pitch angle is controlled based on the pitch angle change amount.

[0132] In some implementations, the parameter value includes one or more of generator speed, generator torque, and pitch angle action acceleration, and the control target includes one or more of smooth output, stable generator speed, and reduced mechanical load.

[0133] In some implementations, the first acquisition module 301 includes:

[0134] For any sampling moment, determine the predicted data at any sampling moment;

[0135] Get the actual output data at any sampling moment;

[0136] Determine the prediction error based on the actual output data and the predicted data;

[0137] The prediction model is corrected and trained according to the prediction error, and when the prediction error is minimized, the trained prediction model is determined to be complete.

[0138] In some implementations, the control module 303 includes:

[0139] Determine the predicted generator speed, predicted generator torque and predicted pitch angle action acceleration according to the predicted data;

[0140] The objective function is constructed based on the predicted generator speed, predicted generator torque and predicted pitch angle action acceleration.

[0141] In some implementations, the apparatus 300 further includes:

[0142] The sampling period is preset, and in each sampling period, the control quantity is obtained, and the first control quantity is input into the prediction model to complete the prediction control of the sampling period.

[0143] In some implementations, the apparatus 300 further includes:

[0144] The discretized state space equation is obtained and used as a prediction model.

[0145] In an embodiment of the present application, the prediction data for each subsequent moment is acquired in advance through the prediction model, the pitch angle is controlled by the prediction data, and the objective function is used to continuously optimize and adjust in this process to obtain a more accurate pitch angle control value for pitch angle control, and the tracking performance of the maximum power point tracking and power smoothing and other optimization objectives can be taken into account in the speed change section to achieve better control purposes.

[0146] Figure 4 The present invention is a block diagram of an electronic device according to an exemplary embodiment. Figure 4 The electronic device shown is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0147] like Figure 4As shown, the electronic device 400 includes a processor 401, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 402 or a program loaded from a memory 406 to a random access memory (RAM) 403. In the RAM 403, various programs and data required for the operation of the electronic device 400 are also stored. The processor 401, the ROM 402, and the RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0148] The following components are connected to the I / O interface 405: a memory 406 including a hard disk, etc.; and a communication part 407 including a network interface card such as a LAN (Local Area Network) card, a modem, etc., and the communication part 407 performs communication processing via a network such as the Internet; a drive 408 is also connected to the I / O interface 405 as needed.

[0149] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 407. When the computer program is executed by the processor 401, the above-mentioned functions defined in the method of the present application are executed.

[0150] In an exemplary embodiment, a storage medium including instructions is also provided, such as a memory including instructions, and the instructions can be executed by the processor 401 of the electronic device 400 to complete the above method. Optionally, the storage medium can be a non-transitory computer-readable storage medium, for example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0151] In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, apparatus, or device. In the present application, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0152] Figure 5 The present invention is a structural block diagram of an electronic device according to an exemplary embodiment. Figure 5 The electronic device shown is only an example and should not limit the functions and scope of use of the embodiments of the present application. Figure 5 As shown, the electronic device 500 includes a processor 501 and a memory 502. The memory 502 is used to store program codes, and the processor 501 is connected to the memory 502 to read the program codes from the memory 502 to implement the pitch angle control method in the above embodiment.

[0153] Optionally, the number of processors 501 may be one or more.

[0154] Optionally, the electronic device may further include an interface 503, and the number of the interface 503 may be multiple. The interface 503 may be connected to an application program and may receive data from an external device such as a sensor.

[0155] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention that follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed in this application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0156] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A pitch angle control method, characterized in that: include: Acquire historical data, and train a prediction model based on the historical data; Collecting data at the current moment, inputting the data at the current moment into the trained prediction model, and outputting prediction data; An objective function is determined based on the prediction data, and the pitch angle is controlled according to the objective function.

2. The method according to claim 1, characterized in that The determining of the objective function based on the predicted data and controlling the pitch angle according to the objective function comprises: Determining one or more parameter values ​​based on the predicted data; constructing the objective function based on the one or more parameter values ​​and the control objective; When the objective function is minimum, determining the pitch angle change; The pitch angle is controlled based on the pitch angle change amount.

3. The method according to claim 2, characterized in that The parameter value includes one or more of a generator speed, a generator torque, and a pitch angle action acceleration, and the control target includes one or more of smooth output, stable generator speed, and reduced mechanical load.

4. The method according to claim 1, characterized in that The method of training the prediction model according to the history includes: For any sampling moment, determining the predicted data at said any sampling moment; Obtaining actual output data at any sampling moment; Determining a prediction error based on the actual output data and the predicted data; The prediction model is corrected and trained according to the prediction error, and when the prediction error is minimum, a prediction model that has been trained is determined.

5. The method according to claim 3, characterized in that: The determining of the objective function based on the predicted data and controlling the pitch angle according to the objective function comprises: Determining a predicted generator speed, a predicted generator torque, and a predicted pitch angle action acceleration according to the predicted data; An objective function is constructed based on the predicted generator speed, the predicted generator torque and the predicted pitch angle action acceleration.

6. The method according to any one of claims 1 to 5, characterized in that: The method further comprises: A sampling period is preset, and in each sampling period, a control variable is obtained, and a first control variable is input into a prediction model to complete the prediction control of the sampling period.

7. The method according to claim 6, characterized in that The method further comprises: A discretized state space equation is obtained, and the discretized state space equation is used as a prediction model.

8. A pitch angle control device, characterized in that: include: A first acquisition module acquires historical data and trains a prediction model based on the historical data; An output module, used to collect data at the current moment, input the data at the current moment into the trained prediction model, and output the predicted data; A control module is used to determine an objective function based on the predicted data and control the pitch angle according to the objective function.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the method according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the method as claimed in any one of claims 1 to 7.

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