A comparative performance analysis based on artificial intelligence techniques applied to three-phase induction motor drives

In this work, we introduced a new robust hybrid control to an induction motor (IM), based on the theory of fuzzy logic and variable structure with sliding-mode control (SMC). As the variations of both control system parameters and operating conditions occur, the conventional control methods may not be satisfied further. Fuzzy tuning schemes are employed to improve control performance and to reduce chattering in the sliding mode. The combination of these two theories has given high performance and fast dynamic response with no overshoot. As it is very robust, it is insensitive to process parameters variation and external disturbances

A new method to minimize the chattering phenomenon in sliding mode control based on intelligent control for induction motor drives

This paper presents new method toward the design of hybrid control with sliding-mode (SMC) plus fuzzy logic control (FLC) for induction motors. As the variations of both control system parameters and operating conditions occur, the conventional control methods may not be satisfied further. Sliding mode control is robust with respect to both induction motor parameter variations and external disturbances. By embedding a fuzzy logic control into the sliding mode control, the chattering (torque-ripple) problem with varying parameters, which are the main disadvantage in sliding-mode control, can be suppressed, Simulation results of the proposed control theme present good dynamic and steady-state performances as compared to the classical SMC from aspects for torque-ripple minimization, the quick dynamic torque response and robustness to disturbance and variation of parameters

A novel robust adaptive control algorithm and application to DTC-SVM of AC drives

In this paper a new robust adaptive control algorithm for AC machine is presented. The main feature of this algorithm is that minimum synthesis is required to implement the strategy. The MCS algorithm is a significant development of MRAC and is similary based on the hyper stability theory of Popov. The hyperstability theory guarantees the global asymptotic stability of the error vector (i.e. the difference between the reference model and system states). Finally, a new approach has been successfully implemented to DTC-SVM. Discussion on theoretical aspects, such as, selection of a reference model, stability analysis, gain adaptive and steady state error are included. Results of simulations are also presented

Performance Analysis of Field-Oriented Control and Direct Torque Control for Sensorless Induction Motor Drives

Abstract-This paper presents a contribution for detailed comparison between two sensorless control techniques for high performance induction motor drives: Field-oriented control (FOC) and direct torque control (DTC). The main characteristics of field-oriented control and direct torque control schemes are studied by simulation emphasizing their advantages and disadvantages. The performances of the two control schemes are evaluated in terms of torque and current ripples, and transient responses to load toque variation. We can nevertheless say that the two control schemes provide in their basic configuration, comparable performances regarding the torque control and parameter sensitivity. We can note a slight advance of DTC scheme compared to FOC scheme regarding the dynamic flux control performance and the implementation complexity. The choice of one or the other scheme will depend mainly on specific requirements of the application

A comparative performance analysis based on artificial intelligence techniques applied to three-phase induction motor drives

In this work, we introduced a new robust hybrid control to an induction motor (IM), based on the theory of fuzzy logic and variable structure with sliding-mode control (SMC). As the variations of both control system parameters and operating conditions occur, the conventional control methods may not be satisfied further. Fuzzy tuning schemes are employed to improve control performance and to reduce chattering in the sliding mode. The combination of these two theories has given high performance and fast dynamic response with no overshoot. As it is very robust, it is insensitive to process parameters variation and external disturbances

A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM)

In this paper, we are interested in the adaptive fuzzy control a technique has been studied and applied, namely adaptive fuzzy control based on theory of Lyapunov. The system based on the stability theory is used to approximate the gains Ke and kdce to ensure the stability of the control in real time .the simulations results obtained by using Matlab environment gives that the fuzzy adaptive control more robust, also it has superior dynamics performances. The results and test of robustness will be presented

A Fuzzy Adaptive Control of Doubly Fed Induction Machine (DFIM)

In this paper, we are interested in the adaptive fuzzy control a technique has been studied and applied, namely adaptive fuzzy control based on theory of Lyapunov. The system based on the stability theory is used to approximate the gains Ke and kdce to ensure the stability of the control in real time .the simulations results obtained by using Matlab environment gives that the fuzzy adaptive control more robust, also it has superior dynamics performances. The results and test of robustness will be presented