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The proposed approach takes advantage of the cascade structure of the system to design a hierarchical controller involving a High Level Controller devoted to position control and a Low Level Controller devoted to attitude stabilization.
The low level controller (LLC) implements the HLC's energy strategy by controlling the power flow between each subsystem in real time such that the energy balance is respected.
The low level controller (LLC) implements the HLC's energy strategy by controlling the power flow between each subsystem in real time such that the energy balance is respected. .
The low level controller is designed to optimally regulate torque at each wheel based on the control inputs of the high level controller, and distribute required torque between the wheels via actuation system.
The outputs of this algorithm are references in airspeed, flight path angle and bank angle, which are seek by the low level controller also presented in this paper.
The lower level is a conventional PID controller, and the higher level is a fuzzy controller acting over the parameters of the low level controller.
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Since most of the manufacturing systems are controlled by low level controllers (e.g., PLCs, CNCs) they store structure and control logic of the system to be modeled by a DES system.
A real-time trajectory smoother is combined with versatile low level controllers.
A hierarchical control system is designed where a high level controller (supervisor) is responsible for task decision, monitoring states of the vehicle, generating references for low level controllers, etc. and several low level controllers are responsible for attitude and altitude stabilization.
Because of complexity of the plants, several tokamaks adopt the so-called 'standard model' (SM) based on a three levels hierarchical control: (i) high level control (HLC)—the supervisor; (ii) medium level control (MLC)—I/O field equipments interface and concentration units and (iii) low level control (LLC)—the programmable logic controllers (PLC).
The low-level controller is designed using probabilistic robust control approaches.
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