Control of Electrical Drives
Nonlinear feedback controllers and compensators: a state-dependent Riccati equation approach
Computational Optimization and Applications
A neural network for linear matrix inequality problems
IEEE Transactions on Neural Networks
Mathematical and Computer Modelling: An International Journal
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Field orientation or vector control is an advanced technique used for the development of high-performance permanent magnet synchronous motor (PMSM) drives. In this paper, a field-oriented adaptive nonlinear control for PMSM drives is presented for sensorless control of the speed and field of the motor, simultaneously. The proposed approach is based on a state-dependent Riccati equation (SDRE) control technique and its formulation utilizes a gradient-based neural-like system for online computation. The unknown parameters of the PMSM drive, that is, stator resistance and load torque, as well as the speed of the motor, are estimated using an extended Kalman filter (EKF) to eliminate the mechanical sensors. The resulting adaptive algorithm is simple and fast and is easily applicable to real-time control of PMSM drives. The efficacy of the proposed approach for sensorless control of PMSM drives is demonstrated through an illustrative simulation for the proof of concept.