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In this approach, the transient main fuel control law for acceleration and deceleration process is designed based on the main fuel flow on steady operating state.
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All the proposed fuel control laws were implemented using a stand-alone single-chip digital signal processor (DSP).
Pareto optimisation based multi-objective genetic algorithms are used to design the fuel distribution control laws of a staged combustor.
The proposed MPPT control system provides a simple and robust control law that can keep the fuel cell working at MPPs in real time.
A basis for designing an intelligent control law for formation maintenance and fuel balancing is presented by exploiting the properties of the natural relative motion.
The realization of the buck converter allows the behaviour of any fuel cells to be easily emulated since only the modification of the control law of the switch is necessary.
The main purpose is to design the optimal control law to ensure the soft landing of the lander with the least fuel consumption.
The control law of the system aims at achieving a trade-off between tracking and fuel consumption while guaranteeing specific constraints, related to physical limitations, safety/comfort issues, environment protection and energy saving.
The CNF control law consists of a linear feedback control law and a nonlinear feedback control law.
The learning control scheme comprises two types of control laws: a linear feedback law and a feed-forward control law.
The control law is evaluated through simulations.
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