Patent Description:
Aircraft systems typically comprise many components, making up primary, secondary and even tertiary sets of components to ensure continuity of performance of the aircraft system if performance of one or more components is impaired.

<CIT> discusses a method for active brake selection comprising detecting an outbound taxiing event for an aircraft. The method also comprising determining whether an inboard or outboard brake has less wear than a respective inboard or outboard brake on a respective landing gear, and selecting an inboard or outboard brake to use during the outbound taxiing event.

<CIT> discusses an aircraft self-actuating brake method and system based on data sharing. The method includes obtaining runway data that the aircraft is to land on, obtaining aircraft state data relevant with aircraft to be landed, use the runway data and the aircraft state data to plan aircraft self-actuating brake scheme, and land the aircraft according to the aircraft self-actuating brake scheme.

<CIT> discusses a method that provides alert information, regarding an aircraft wheel braking system, to an operator of an aircraft during an aircraft landing. An input of a target deceleration rate for the landing aircraft is received prior to the aircraft having landed on a ground surface. At least one sensor electronically collects information relevant to a real-time deceleration rate of the aircraft after the aircraft has landed on the ground surface, and the real-time deceleration rate of the aircraft is calculated. The target deceleration rate is compared to the calculated deceleration rate to determine and effectiveness of the aircraft wheel braking system. A visual, audible, or tactile alert is optionally provided to the operator of the aircraft, and data from this system could also be used as an input for various other aircraft safety systems.

<CIT> discusses a method for monitoring wear of one or more aircraft parts, such as an aircraft brake, an aircraft tire, a standby system, and landing gear.

A first aspect of the present invention provides a controller according to claim <NUM>. A further aspect concerns an aircraft system according to claim <NUM> comprising a first set of components for performing a function of the aircraft system, a second, alternative, set of components for performing the function of the aircraft system, and a controller comprising a machine learning model, the controller being configured to: receive scenario data indicative of a scenario during which the function of the aircraft system is to be performed; where each of the first and second sets of components are operational, use the machine learning model to select between the first or the second set of components to perform the aircraft system function during the scenario based on the received scenario data; and control the selected set of components to perform the function during the scenario.

The controller is configured to, where each of the first and second sets of components are operational, select between the first and second sets to perform the aircraft system function during the scenario based on the received scenario data.

In particular, in known aircraft systems having first and second sets of components that perform the same aircraft system function, for example a primary set of components and a secondary or backup set of components, one of the first and second sets of components is used during normal operating conditions, with the other of the second and first sets of components being used only where the set of components used during normal operating scenarios is non-operational, for example due to a component fault. Conventional aircraft systems may thereby provide at least one level of redundancy to account for scenarios that are outside of normal operating conditions. However, it may be the case that performance of the set of components used in normal operating conditions is not tailored to the particular scenario in which the function of the aircraft system is to be performed. The present invention mitigates for this by selecting between the first or the second set of components to perform the aircraft system function during the scenario based on the received scenario data. This may allow for the function of the aircraft system to be performed in a manner that is tailored to a particular scenario, by using the most appropriate set of components based on the received scenario data.

Operational as discussed herein is taken to mean that a particular set of components can be operated to perform the desired function of the aircraft system, for example with a set of components being considered operational only where each component of that set is operational.

The scenario data may comprise component data indicative of a state of components in the first and second sets of components, for example a state of components in the first and second sets of components pre- the scenario in which the function of the aircraft system is to be performed. This may enable selection between the first and second sets of components to perform the aircraft system function to be based on the state of components within the first and second sets of components. The controller may be configured to receive component data indicative of a state of components in the first and second sets of components. The scenario data may comprise component data indicative of a state of each of the components in the first and second sets of components. This may enable the state of each component of the first and second sets of components to be taken into account when selecting which of the first and second sets of components is to be used to perform the function of the aircraft system.

The scenario data may comprise component data indicative of a future state of components in the first and second sets of components, for example a predicted state of components in the first and second sets of components post- the scenario in which the function of the aircraft system is to be performed. This may, for example, enable the controller to determine which of the first and second sets of components to use to perform the function to avoid negatively impacting upon the future state of components in the first and second sets of components.

The component data may be indicative of any of component service life, component wear, or component performance capability.

Component service life may comprise any of a duration since component installation or manufacture, a number of previous component uses, and an estimated duration of remaining component lifespan. This may enable component service life to be taken into account when selecting which of the first and second sets of components to perform the function during a particular scenario. For example, a duration since component installation or manufacture, or a number of previous component uses, may be indicative of component wear based on a simulation of component wear during normal operating conditions. By selecting one of the first and second sets of components based on received component data indicative of a duration since component installation or manufacture, component wear may be taken into account when considering whether to perform the function of the aircraft system using the first or second sets of components. Similarly, by selecting one of the first and second sets of components based on received component data indicative of an estimated duration of remaining component lifespan, a lifespan of components may be prolonged by selecting a set of components that has a longer remaining component lifespan to perform the function.

The controller may be configured to compare any of a duration since component installation or manufacture, a number of previous component uses, and an estimated duration of remaining component lifespan, between corresponding components of the first and second sets of components, and to select between the first or the second set of components to perform the aircraft system function during the scenario based on the comparison. For example, where corresponding components in the first and second set of components have different durations since installation, the controller may be configured to select the set of components having the shortest time since installation to perform the aircraft system function.

By corresponding components is meant components within the first and second sets of components that contribute similar functionality to the overall function of the aircraft system.

The controller may be configured to derive an estimated remaining lifespan of the first and second sets of components, and to select between the first or the second set of components to perform the aircraft system function during the scenario based on the derived remaining lifespan.

Components that suffer excessive wear in normal operating conditions may require regular maintenance. By selecting one of the first and second sets of components based on received component data indicative of component wear, maintenance intervals may be increased. The controller may be configured to compare component wear between corresponding components of the first and second sets of components, and to select between the first or the second set of components to perform the aircraft system function during the scenario based on the comparison. For example, where corresponding components in the first and second sets of components have different levels of component wear, the controller may be configured to select the set of components having the lowest level of component wear to perform the aircraft system function. The controller may be configured to calculate an aggregate level of component wear for each of the first and second sets of components, and to select the set of components having the lowest aggregate level of component wear to perform the aircraft system function.

By selecting one of the first and second sets of components based on received component data indicative of component performance capability, one of the first and second sets of components may be chosen depending on a desired performance criteria for the aircraft system function in the particular scenario in which the function is to be performed. The controller may be configured to compare performance capability between corresponding components of the first and second sets of components, and to select between the first or the second set of components to perform the aircraft system function during the scenario based on the comparison. For example, where corresponding components in the first and second sets of components have different levels of performance capability, the controller may be configured to select the set of components having the higher or lower level of performance capability, as desired, to perform the aircraft system function. The controller may be configured to calculate an aggregate level of performance capability for each of the first and second sets of components, and to select the set of components having the higher or lower aggregate level of performance capability, as desired for the particular scenario, to perform the aircraft system function.

It will be appreciated that performance capability may be at least partly based on component wear and/or component service life, and that component wear may be at least partly based on component service life.

The scenario data may comprise data indicative of any of an aircraft condition, a runway condition, or ambient weather condition, during the scenario. Thus the controller may account for any of an aircraft condition, a runway condition, or ambient weather condition when selecting between the first and second sets of components to perform the aircraft system function during the scenario.

The aircraft system may comprise an aircraft braking system, for example a system for applying a braking force to a wheel of an aircraft. The function may comprise applying a braking force to a wheel of an aircraft.

The aircraft condition may be indicative of any of a weight of the aircraft, landing gear loading during take-off or landing, wheel loading during take-off or landing, aircraft engine thrust magnitude, aircraft engine thrust direction, a flight control surface configuration, tyre condition, tyre pressure, or tyre lifespan. Each of these factors may contribute to the braking force to be applied to a wheel of an aircraft, and by selecting between the first and second sets of components based on any of these factors, an appropriate set of components may be selected for the given factors.

The runway condition may be indicative of any of runway distance or a coefficient of friction of the runway. Runway distance and/or a coefficient of friction of a runway may influence a braking force required to be applied during landing of an aircraft. By selecting between the first and second sets of components based on any of runway distance and a coefficient of friction of the runway, an appropriate one of the first and second sets of components may be chosen to perform the function, for example to apply a braking force to a wheel of an aircraft.

The scenario data may be derived from a model of the aircraft system.

The aircraft system may comprise a sensor, and the scenario data may be derived from a reading taken by the sensor in use. This may enable the controller to select between the first and second sets of components based on real-time data. The sensor may, for example, monitor a performance capability of one or more components of the first and second sets of components. The aircraft system may comprise a plurality of sensors, for example a plurality of sensors configured to monitor a plurality of corresponding components of the first and second sets of components.

The aircraft system may comprise a memory, and the scenario data may be derived from simulation data stored in the memory.

The controller may be configured to receive the scenario data from an off-aircraft location. This may remove the need for the aircraft system to comprise a large memory.

The first and second sets of components may comprise mutually exclusive sets, for example such that none of the components in the first set of components are present in the second set of components, and vice versa.

According to the invention, the controller comprises a machine learning model to select between the first or the second set of components based on the received scenario data. For example, the machine learning model may receive the scenario data as an input, and determine which of the first and second sets of components to select as an output. A machine learning model may be able to adapt to a wide range of scenarios seen by the aircraft system in use. The machine learning model may comprise a neural network or the like.

The aircraft system may comprise a third, different, set of components for performing the function of the aircraft system, and controller is configured to, where the first, second and third sets of components are operational, select between the first, second and third sets of components to perform the aircraft system function during the scenario based on the received scenario data, and control the selected set of components to perform the function during the scenario. This may provide further flexibility in determining which components are to be used for a given scenario.

Where one of the first and second sets of components is non-operational, the controller may be configured to select the other of the second and first sets of components to perform the aircraft system function.

The present invention provides a controller for an aircraft system comprising a first set of components for performing a function of the aircraft system, and a second, alternative, set of components for performing the function of the aircraft system, the controller comprising a machine learning model and being configured to: receive scenario data indicative of a scenario during which the function of the aircraft system is to be performed; where each of the first and second sets of components are operational, use the machine learning model to select between the first or the second set of components to perform the aircraft system function during the scenario based on the received scenario data; and control the selected set of components to perform the function during the scenario.

A third aspect of the present invention provides an aircraft comprising an aircraft system according to the first aspect.

A fourth aspect of the present invention provides a method of performing a function of an aircraft system comprising a first set of components for performing the function and a second, alternative, set of components for performing the function, wherein the method comprises; receiving scenario data indicative of a scenario during which the function of the aircraft system is to be performed; where each of the first and second sets of components are operational, using a machine learning model to select between the first and second sets of components to perform the aircraft system function during the scenario based on the received scenario criteria; and controlling the selected set of components to perform the function during the scenario.

According to an example, the aircraft system is an aircraft braking system comprising a first set of components for performing a braking function, a second, alternative, set of components for performing the braking function, and a controller configured to: receive braking scenario data indicative of a braking scenario in which the braking function is to be performed; where each of the first and second sets of components are operational, select between the first and second sets of components to perform the braking function during the braking scenario based on the received braking scenario data; and control the selected set of components to perform the braking function during the braking scenario.

An aircraft system <NUM>, in the form of a hydraulic braking system <NUM>, according to the present invention, is illustrated schematically in <FIG>. The braking system <NUM> comprises a brake controller <NUM>, with the brake controller <NUM> including a neural network <NUM>.

The hydraulic braking system <NUM> shown in <FIG> comprises components which are operated in order to control brakes 102a, 102b. The brakes 102a and 102b can be operated either using a first power supply or a second, alternative, power supply. In this example, the first power supply is provided by a hydraulic pump <NUM>, and the second power supply is provided by a hydraulic accumulator <NUM>. In some examples, as in the example of <FIG>, the hydraulic pump <NUM> can be used to supply power to the hydraulic accumulator <NUM>, if needed, with a check valve preventing backflow from the accumulator <NUM> to the hydraulic pump <NUM>. A first selector valve <NUM> selects operation using the first power supply <NUM>. Collectively, the first power supply <NUM> and the first selector valve <NUM> may be thought of as a first set of components 110a for providing a braking function of the hydraulic braking system <NUM>. The first set of components 110a may also comprise other components including monitoring equipment (not shown). Operating the first selector valve <NUM> comprises providing an electrical signal to a coil which actuates the valve. The first selector valve <NUM> may comprise two such coils for redundancy purposes.

The hydraulic accumulator <NUM> is a pressurised container. When used to operate the brakes 102a and 102b, the pressure which is delivered to the rest of the braking system from the accumulator <NUM> is monitored and controlled to ensure the safe operation of the brakes 102a and 102b. A relief valve <NUM> controls the pressure of fluid released from the accumulator <NUM>, a pressure transducer <NUM> monitors the pressure from the hydraulic accumulator <NUM>, and a second selector valve <NUM> selects the hydraulic accumulator <NUM> as the power supply for operating the brakes 102a and 102b. Collectively the hydraulic accumulator <NUM>, the relief valve <NUM>, the pressure transducer <NUM>, and the second selector valve <NUM> may be thought of as a second set of components 110b for providing a braking function of the hydraulic braking system <NUM>.

After the operation of either the first selector valve <NUM> or the second selector valve <NUM>, power, in the form of pressurised fluid, is provided in a brake operation system 110c. A first servo valve <NUM> and a second servo valve <NUM> are used to control the supply of hydraulic fluid from the hydraulic pump <NUM> to the first 102a and second 102b brakes respectively. The first <NUM> and second <NUM> servo valves may be considered part of the first set of components 110a, although this is not illustrated by the dashed box in <FIG> for the sake of clarity. A third servo valve <NUM> and a fourth servo valve <NUM> are used to control the supply of hydraulic fluid provided by the accumulator <NUM> to the first 102a and second 102b brakes. The third <NUM> and fourth <NUM> servo valves may be considered part of the second set of components 110b, although this is not illustrated by the dashed box in <FIG> for the sake of clarity. The hydraulic braking system <NUM> comprises two pressure transducers <NUM> and <NUM> for monitoring the pressure of hydraulic fluid being provided to each of the brakes 102a and 102b.

Shuttle valves <NUM>, <NUM> are included between the first <NUM>, second <NUM>, third <NUM> and fourth <NUM> servo valves and the brakes 102a, 102b to ensure that the highest-pressure input is fed through to the brakes. The use of shuttle valves prevents the pressurised fluid from the accumulator <NUM> from being fed back into the primary power supply, and vice versa. In other words, these shuttle valves ensure that fluid delivered from the accumulator goes to the brakes and not backwards through the first <NUM> and second <NUM> servo valves.

Two tachometers <NUM> and <NUM> are used to monitor the speed of the wheels during braking to provide feedback in the braking control system. It will be appreciated that other components not shown may also be included and used in the hydraulic braking system <NUM>, such as further sensors, actuators, and the like. It is also to be understood that while specific examples of equipment have been described herein, other equipment may also be used. For example, a wheel speed sensor other than a tachometer may be used to monitor the speed of the wheels during braking. Similarly, other pressure sensors rather than pressure transducers may be used to monitor the pressure in the hydraulic braking system <NUM>.

As indicated above, either the first set of components 110a or the second set of components 110b can be utilised to provide a braking function of the hydraulic braking system <NUM>. In known aircraft systems, the first set of components 110a would be used under normal operating conditions, with the second set of components 110b only being used in the event that the first set of components 110a is considered non-operational, for example where one or more of the components of the first set of components 110a is considered non-operational. Whilst the hydraulic braking system <NUM> of the present invention provides such functionality, the hydraulic braking system <NUM> also enables selection between the first set of components 110a and the second set of components 110b where both sets of components 110a and 110b are considered operational, as will be described hereafter.

In particular, the applicant has found that during certain scenarios encountered by the hydraulic braking system <NUM> in use, it may be preferable to use the second set of components 110b even where the first set of components 110a is considered operational. The hydraulic braking system <NUM> therefore accounts for this by receiving so-called "scenario data" <NUM> at the brake controller <NUM>, with the brake controller <NUM>, and in particular the neural network <NUM>, utilising the scenario data <NUM> to select between the first 110a and second 110b sets of components to perform a braking function during a particular scenario. It will be appreciated that the scenario data <NUM> may be considered to be any data representative of an aspect of a scenario in which a braking function of the hydraulic braking system <NUM> is to be performed, and that examples of appropriate scenario data <NUM> will be described hereinafter.

A method <NUM> according to the present invention is illustrated schematically in <FIG>. The method <NUM> comprises receiving <NUM> scenario data indicative of a scenario during which the braking function of the hydraulic braking system <NUM> is to be performed. Where each of the first 110a and second 110b sets of components are operational, the method <NUM> comprises selecting <NUM> between the first 110a and second 110b sets to perform the braking function of the hydraulic braking system <NUM> during the scenario, with the selecting <NUM> based on the received scenario data <NUM>. The method <NUM> comprises controlling <NUM> the selected set of components to perform the braking function during the scenario. Also illustrated in <FIG>, although not essential to the method <NUM>, are the steps of determining <NUM> which of the first 110a and second 110b sets is non-operational, selecting <NUM> the operational set of components to perform the braking function, and controlling <NUM> the operational set of components to perform the braking function.

The hydraulic braking system <NUM> and the method <NUM> according to the present invention thereby select which of the first 110a and second 110b sets of components are utilised to perform a braking function in a scenario where each of the first 110a and second 110b sets of components are operational. This may allow for the braking function of the hydraulic braking system <NUM> to be performed in a manner that is tailored to a particular scenario, by using the most appropriate set 110a,110b of components based on the received scenario data <NUM>.

In some embodiments, the scenario data <NUM> includes component data indicative of a state of components in the first 110a and second 110b sets of components, for example indicative of a state of each of the components in the first 110a and second 110b sets of components. Such component data can be indicative of any of component service life, component wear, or component performance capability. For example, where the component data is indicative of an number of actuations that have been performed out of an anticipated maximum number of actuations, the controller <NUM> may select one of the first 110a and second 110b sets of components to perform the braking function of the hydraulic braking system <NUM> to use components that are not as close to their maximum number of actuations. Similarly, for example, where the component data is indicative of component wear, the controller <NUM> may select one of the first 110a and second 110b sets of components to perform the braking function of the hydraulic braking system <NUM> to minimise component wear on components of the other of the second 110b and first 110a sets of components.

Taking the hydraulic braking system <NUM> illustrated in <FIG> as an example, it may be the case that the hydraulic pump <NUM> has experienced more wear than the hydraulic accumulator <NUM>. In such an instance, the controller <NUM> may select to use the second set 110b of components to perform a braking function to avoid further wear on the hydraulic pump <NUM>. In some embodiments, it may be the case that relatively high component performance is required, for example to provide a high braking force. Where the hydraulic pump <NUM> has suffered more wear than the hydraulic accumulator <NUM>, the hydraulic accumulator <NUM> may be capable of higher braking performance than the hydraulic pump <NUM>, and so, given this knowledge, the controller <NUM>, and in particular the neural network <NUM>, may select the second set 110b of components to perform the braking function.

Similarly, where the first <NUM> and second <NUM> servo valves are worn, and cannot deliver as high a braking performance as the third <NUM> and fourth <NUM> servo valves, the controller <NUM>, and in particular the neural network <NUM>, may, given this knowledge, select the second set 110b of components to perform the braking function.

The component data indicative of a state of components in the first 110a and second 110b sets of components can be indicative of a state pre-, during, or post- the scenario in which the braking function is to occur. Thus the scenario data <NUM> may enable the controller <NUM> to consider the full impact of the scenario, and the braking function to be performed in the scenario, on the components of the first 110a and second 110b sets of components.

It will of course be appreciated that there is a link between service life, wear and performance capability. For example, longer service life can be said to result in increased wear, and increased wear can be said to result in reduced performance capability. It will thus also be appreciated that wear or performance capability can be directly measured, for example using one or more sensors, or that wear or performance capability can be inferred based on service life or other parameters, such as the number of flights or landing operations. In some embodiments, wear or performance capability is inferred given other parameters such as service life. In such embodiments, the scenario data <NUM> may be derived from simulation data stored in a memory (not shown) of the hydraulic braking system <NUM>.

In some embodiments, the scenario data <NUM> comprises data indicative of any of an aircraft condition, a runway condition, or ambient weather condition, during the scenario in which the braking function is to be performed. In such a manner the set of components selected by the controller <NUM> may be selected to provide performance appropriate for a given aircraft condition, runway condition, or ambient weather condition, for which the braking function is to be performed.

The aircraft condition may be indicative of any of a weight of the aircraft, landing gear loading during take-off or landing, wheel loading during take-off or landing, aircraft engine thrust magnitude, aircraft engine thrust direction, a flight control surface configuration, tyre condition, tyre pressure, or tyre lifespan. It will be appreciated by a person skilled in the art that each of the aforementioned "aircraft conditions" which occur during a particular scenario in which a braking function is to be performed may have an impact on a required braking function. For example, a heavier aircraft weight may require a larger braking force to be applied, and the controller <NUM>, upon receipt of scenario data <NUM> indicating an aircraft weight, may select between the first 110a and second 110b sets of components to provide the appropriate braking force.

The runway condition may be indicative of any of runway distance or a coefficient of friction of the runway. It will be appreciated by a person skilled in the art that either of these "runway conditions" that occur in a particular scenario in which a braking function is to be performed may have an impact on a required braking function. For example, a relatively short runway may require a larger braking force to be applied, and the controller <NUM>, upon receipt of scenario data <NUM>, may select between the first 110a and second 110b sets of components to provide the appropriate braking force. In some embodiments, the runway condition is transmitted to the controller <NUM> of the hydraulic braking system <NUM> from an off-aircraft location. In some embodiments the runway condition is derived, at least in part, from data indicative of an ambient weather condition of an aircraft <NUM> in which the hydraulic braking system <NUM> is installed.

As another example, a relatively long, dry, runway may be indicated by the scenario data <NUM>, and the first 110a set of components may provide braking over a shorter distance on such a runway, but the controller <NUM> may nevertheless select the second set of components 110b to perform a required braking function based on other scenario data <NUM>, for example scenario data <NUM> indicating that one or more of the components of the first set of components 110a has suffered greater wear than the corresponding component of the second set of components 110b.

From the discussion above, it can be seen that the scenario data <NUM> can take a variety of forms. The neural network <NUM> of the controller <NUM> is a machine learning model, for example such as a recurrent or LSTM neural network, that has been trained to process the scenario data <NUM> to select between the first 110a and second 110b sets of components. A neural network typically includes a number of interconnected nodes, which may be referred to as artificial neurons, or neurons. The internal state of a neuron (sometimes referred to as an "activation" of the neuron) typically depends on an input received by the neuron. The output of the neuron then depends on the input, weight, bias, and the activation function. The output of some neurons is connected to the input of other neurons, forming a directed, weighted graph in which vertices (corresponding to neurons) or edges (corresponding to connections) of the graph are associated with weights, respectively. The neurons may be arranged in layers such that information may flow from a given neuron in one layer to one or more neurons in a successive layer of the neural network.

The neural network <NUM> of the controller <NUM> is trained based on a high-fidelity model of the hydraulic braking system <NUM>, which takes into consideration the mechanical and physical properties of the system <NUM> and its components, as well as inputs such as pressures, temperatures, flow rates etc. Using such a model, system level behaviours and effects for different scenarios that occur in use can be accounted for, and the controller <NUM> can utilise either of the first 110a or second 110b sets as determined to be appropriate for the given scenario. It will be appreciated that the exact form of the model on which the neural network <NUM> is trained will depend on the structure of the system in question, and that the structure of the model can be determined by a person skilled in the art, as appropriate.

Whilst illustrated above in the context of a particular hydraulic braking system <NUM>, it will be appreciated that the method <NUM> described herein may be applicable to other types of aircraft system having first and second sets of components for separately performing the function of the aircraft system in question. It will certainly be appreciated that the method <NUM> described herein is not limited to hydraulic braking systems, and that other types of braking system, for example electric braking systems, that make use of the present invention are also envisaged.

Embodiments in which more than two sets of components for performing the same aircraft function are present are also envisaged. In such embodiments, the controller <NUM> may, where all sets of components are operational, select between the sets of components to perform the function of the hydraulic braking system <NUM> based on the received scenario data <NUM>.

An aircraft <NUM> comprising the hydraulic braking system <NUM> is illustrated schematically in <FIG>.

Claim 1:
A controller (<NUM>) for an aircraft system (<NUM>) comprising a first set of components (110a) for performing a function of the aircraft system, and a second, alternative, set of components (100b) for performing the function of the aircraft system, the controller (<NUM>) comprising a machine learning model (<NUM>) and being configured to:
receive scenario data (<NUM>) indicative of a scenario during which the function of the aircraft system (<NUM>) is to be performed;
where each of the first and second sets of components (110a, 110b) are operational, use the machine learning model (<NUM>) to select between the first or the second set of components (110a, 110b) to perform the aircraft system function during the scenario based on the received scenario data (<NUM>); and
control the selected set of components to perform the function during the scenario.