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Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power
Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power
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Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power
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Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power
Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power

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Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power
Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power
Journal Article

Experimental analysis of passivity‐based control theory for permanent magnet synchronous motor drive fed by grid power

2024
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Overview
Controlling the Permanent Magnet Synchronous Motor (PMSM) can be challenging due to the nonlinearity of its dynamics, which makes it difficult to design control strategies that are both robust and effective. To address this challenge, this paper presents a novel control strategy rooted in the concept of passivity that combines field‐oriented control (FOC). This strategy compels the PMSM to accurately follow velocity and electrical torque trajectories. The approach, known as passivity‐based control (PBC), entails reshaping the inherent system energy while introducing the necessary damping to attain the desired objectives. A crucial aspect involves identifying workless force terms within the process model. Despite their presence, these terms do not impact the energy balance and stability properties. As a result, eliminating these terms is unnecessary. This simplicity in control architecture not only preserves system stability but also bolsters overall robustness. The system's overall stability and the current tracking error's exponential convergence have both been demonstrated analytically. In order to maintain stability, the controller accounts for the nonlinearities of the plant and approximates the unstructured dynamics of the PMSM. The proposed control is designed using the dq model of the PMSM, which avoids the model's structure destruction due to singularities, since the dq model does not depend explicitly on the rotor angular position. Experimental results shown further, illustrate speed and position control with a desired pair calculated by a filter or a proportional‐integral (PI) controller for speed control and a proportional‐integral‐derivative (PID) controller for position control. Also the correlation between practical and theoretical results is given as well as the robustness test in relation to the uncertainties of the PMSM's inertia moment. The results demonstrates the effectiveness of the proposed strategy in controlling the PMSM under different operating conditions, highlighting its potential for industrial applications. The main advantage of this approach is that it does not cancel out the nonlinear features of the system, but rather compensates for them in a damped manner. This allows for a more effective and robust control strategy.