Abstract: A control system of a gas turbine engine is provided. The engine has a fuel flow metering valve which regulates a fuel flow to the engine, and one or more variable geometry components which are movable between different set points to vary an operating configuration of the engine. The control system has an engine fuel control sub-system which provides a fuel flow demand signal for controlling the fuel flow metering valve. The control system further has a variable geometry control sub-system which determines current set points to be adopted by the variable geometry components given the current engine operating condition in order to comply with one or more engine constraints. The control system further has an optimiser that receives the current set points and determines adjusted values of the set points which optimise, while complying with the engine constraints, an objective function modelling a performance characteristic of the engine, the objective function adapting to change in engine performance with time.

Abstract: A computer-implemented method of enabling optimisation of trajectory for a vehicle, the method comprising: determining a trajectory for the vehicle using: an algorithm; a vehicle model defining path constraints for the vehicle through space; a propulsion system model defining parameters of a propulsion system of the vehicle; an objective function defining one or more objectives; and controlling output of the determined trajectory.

Abstract: A computer-implemented method of enabling optimisation of derate for a propulsion system of a vehicle, the method comprising: determining a derate for the propulsion system of the vehicle using: an algorithm; a vehicle model defining path constraints for the vehicle through space; a propulsion system model defining parameters of the propulsion system; an objective function defining one or more objectives; and controlling output of the determined derate.

Abstract: A computer-implemented method of optimizing the performance of a reconfigurable power system is provided. The method comprises the steps of: receiving an operating profile for the power system; partitioning the operating profile into a plurality of sub-phases; performing a coarse optimisation routine of the power system over each sub-phase of the operating profile to derive a respective coarsely optimised configuration of the power system; performing a fine optimisation routine of each coarsely optimised configuration over its respective sub-phase of the operating profile to derive a respective finely optimised configuration for that sub-phase; and defining settings of the power system to implement the finely optimised configurations thereon.

Abstract: An electronics enclosure for use in a gas turbine engine. The electronics enclosure including: a housing; one or more electronic devices, located within the housing, for use in controlling or monitoring the gas turbine engine; and a thermoelectric cooler configured, based upon a determination of an operational state of the gas turbine engine, to change between an active cooling mode, whereby the thermoelectric cooler is provided with power and thereby operated to cool the inside of the housing, and a passive mode, in which the thermoelectric cooler is not operated.

Abstract: A control system of a gas turbine engine is provided. The engine has a fuel flow metering valve which regulates a fuel flow to the engine, and one or more variable geometry components which are movable between different set points to vary an operating configuration of the engine. The control system has an engine fuel control sub-system which provides a fuel flow demand signal for controlling the fuel flow metering valve. The control system further has a variable geometry control sub-system which determines current set points to be adopted by the variable geometry components given the current engine operating condition in order to comply with one or more engine constraints. The control system further has an optimiser that receives the current set points and determines adjusted values of the set points which optimise, while complying with the engine constraints, an objective function modelling a performance characteristic of the engine, the objective function adapting to change in engine performance with time.

Abstract: A computer-implemented method of optimizing the performance of a reconfigurable power system is provided. The method comprises the steps of: receiving an operating profile for the power system; partitioning the operating profile into a plurality of sub-phases; performing a coarse optimisation routine of the power system over each sub-phase of the operating profile to derive a respective coarsely optimised configuration of the power system; performing a fine optimisation routine of each coarsely optimised configuration over its respective sub-phase of the operating profile to derive a respective finely optimised configuration for that sub-phase; and defining settings of the power system to implement the finely optimised configurations thereon.

Abstract: There are disclosed corresponding methods, systems, controllers (26) and software for machine (10) sensor network management. Upon receiving from a node a request to join an existing network of machine sensors (25), sound waves are emitted in the vicinity of the machine (10). The emitted sound waves are sensed by the node and a corresponding signal output is generated by the node. The signal output from the node is compared with the emitted sound waves and/or a further signal output from one or more machine sensor (25) in the existing network. The node request to join the existing network is authenticated or rejected based on the comparison.

Abstract: A method of optimising the performance of a machine that comprises an element, comprises the steps of: (a) receiving operational data, the operational data being representative of an operational state of the machine; (b) transmitting an adjustment signal to the element to change the operational state of the element from a first state to a second state, the predetermined second state being dependent on the operational state of the machine; (c) generating an optimising action by processing the operational data, a history of previous operational states of the machine, a history of previous adjustment signals, and a sequence of previously applied optimising actions; and (d) applying the optimising action to the machine to optimise the performance of the machine.