The performances of the adjustable electric drive systems are directly related to the accurate knowledge of the parameters. It is well known that the resistances are temperature dependent and the inductances are function on the magnetising B-H curve of the ferromagnetic material and the saturation effect. In order to obtain a high performance electric drive system, an adaptive structure in direct form (the controller parameters are obtained on-line) is proposed in this paper. The adaptive mechanism of the parameters is obtained by adding two terms: the first one will support a gradient adjustment law (assuring the asymptotic performances) and the second one will comport an adjustment that includes a sigmoid function specific for variable structure control. The last component improves the transient and steady state response by eliminating the small oscillations of the closed loop response around the equilibrium state in order to obtain a zero tracking error. The adaptive mechanism assures the robustness to the external disturbances and to the unmodeled dynamics. Another issue presented in this paper is an original load torque method. The load torque estimator is based on the transversal current stator component and the measured rotor speed. This method presents certain advantages instead of using measured method, which requires a low pass filter: no additional hardware, and faster control response. Matlab/Simulink based simulation results will show the validity of the proposed solution.I.

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Due to the parametric and structural uncertainty of the DC drive system, an adaptive control method is necessary. Therefore, an original model reference adaptive control (MRAC) for DC drives is proposed in this paper. MRAC ensures on-line adjustment of the control parameters with DC machine parameter variation. The proposed adaptive control structure provides regulating advantages: asymptotic cancellation of the tracking error, fast and smooth evolution towards the origin of the phase plan due to a sliding mode switching k-sigmoid function. The reference model can be a real strictly positive function (the tracking error is also the identification error) as its order is relatively higher than one degree. For this reason, the synthesis of the adaptive control will use a different type of error called augmented or enhanced error. The DC machine with separate excitation is fed at a constant flux. This adaptive control law assures robustness to external perturbations and to unmodelled dynamics.

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The motor drives are the major consumers of the electrical energy. There are two main ways for energy saving: to use the advanced techniques of the optimal control and to adapt a solution to the existing drive systems in order to increase the energy efficiency. In order to find an answer to this challenge, in this paper a very cheap and efficient solution is proposed. The proposed electrical drive system is obtained in two steps: firstly, the optimal control based on the energetic criteria is used in order to obtain the optimal speed response; secondly, the optimal speed response is used as reference to the existing conventional drive system. The obtained efficient electric drive system combines the energetic performances of the optimal control with the features of the conventional drive control, the solution being applicable to the industrial drive systems. The optimal control solution is based on the integration of the matrix Riccati differential equation (MRDE) and it is computed on-line. The optimal control has three components: the state feedback, the forcing component to achieve the desired state and the compensating feed forward of the perturbation. It is tested by using numerical simulations on the specific cycle of an elevator drive system and implemented to an industrial drive system.