IEEE Transactions on Industrial Electronics · 2015 · 99 citations · 13 references
EngineeringElectrical EngineeringElectric MachinesMotor ControlPower ElectronicsBrushless Dc MachinesControl TheoryDirect Current MachinesElectric DrivesElectric Motor DrivesModel Predictive ControlBrushless Direct Current MachinesBrushless Direct Current Motor DrivesBrushless Direct Current MotorsCurrent ControlCurrent Control Of Motor DrivesMotor Drive ControlMotor Speed ControlSpeed Control Of Direct Current Machines
Model-based predictive control is a powerful control strategy to drive electrical machines. Conventional cascade proportional-integral (derivative) [PI(D)] controllers are often used to control speed, torque, and current. However, for low-inertia machines, achieving a high-performance and wide speed range is far beyond the application conditions for which these controllers are designed for. Using two cascaded PI(D) controllers for the speed/current control of a low-inertia machine, changes in the speed set point should be slowly applied in order to avoid stability problems. In this paper, a model predictive control algorithm that is able to control the speed of a low-inertia brushless direct-current machine with a high bandwidth and good disturbance rejection properties is proposed. The algorithm is implemented on a SPARTAN 3E 1600 field-programmable gate-array board, and experimental results verify the performance of the proposed algorithm.
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