A new sliding mode position controller with adaptive load torqueestimator for an induction motor

A new sliding mode control algorithm with an adaptive load torque estimator is presented to control the position of the induction motor in this paper. First, the rotor flux is estimated with the simplified rotor flux observer in the rotor reference frame and the feedback linearization theory is used to decouple the rotor position and the rotor flux amplitude. Then, a new sliding mode position controller with an adaptive load torque estimator is designed to control the position of the induction motor such that the chattering effects associated with the classical sliding mode position controller can be eliminated. Stability analysis is carried out using the Lyapunov stability theorem. Experimental results are presented to confirm the characteristics of the proposed approach. The good position tracking and load regulating responses can be obtained by the proposed position controller     

Adaptive fuzzy sliding-mode control for induction servomotor systems

An adaptive fuzzy sliding-mode control design method is proposed for induction servomotor system control. The proposed adaptive fuzzy sliding-mode control system is comprised of a fuzzy controller and a compensation controller. The fuzzy controller is the main tracking controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the fuzzy controller. A tuning methodology is derived to tune the premise and consequence parts of the fuzzy rules. The online tuning algorithm is derived in the Lyapunov sense; thus, the stability of the control system can be guaranteed. Moreover, to relax the requirement for the uncertain bound in the compensation controller, an estimation mechanism is investigated to observe the uncertain bound, so that the chattering phenomena of the control efforts can be relaxed. To illustrate the effectiveness of the proposed design method, a comparison between a conventional fuzzy control and the proposed adaptive fuzzy sliding-mode control is made. Simulation and experimental results verify that the proposed adaptive fuzzy sliding-mode control design method can achieve favorable control performance with regard to parameter variations and external disturbances.     

Self-tuning control of induction motor drive using neural networkidentifier

This study presents a new self-tuning PI speed controller with load torque observer and feedforward compensation based on neural network identification for an induction motor. A two-layer neural estimator is also used to provide a real-time adaptive estimation of the unknown motor dynamics. The widely used projection algorithm is used as the learning algorithm for this network, to minimize the difference between the motor's actual response and that predicted by the neural estimator. The proposed neural estimator uses this learning to adjust PI speed controller with a load torque observer to generate the control signal online, thereby bringing the motor output to a desired reference trajectory. The theoretical analysis, simulation and experimental results demonstrate the proposed scheme's effectiveness     

Performance improvement of DTC for induction motor-fed by three-level inverter with an uncertainty observer using RBFN

A stable sensorless controller for DTC of induction motor fed by three-level inverter using the Radial Basis Function Network (RBFN) is presented in this paper. The torque ripple can be drastically reduced and low speed performance can be obtained in the DTC system for high performance induction motor drives. However, speed control performance is still influenced by the lumped uncertainties of the system such as parameter variations, external load disturbances, and unmodeled dynamics which make it difficult to obtain an exact mathematical model. In this paper, the lumped uncertainties are estimated on-line by the RBFN. Simulations as well as experimental results are shown to illustrate the performance of the proposed system.     

A microcomputer-based induction motor drive system using currentand torque control

This paper proposes an induction motor drive with current and torque control. The current control based on the current error with the current controller yields h_l signal. The torque control based on the torque error with the torque controller yields a h_l signal. According to the h_l signal, the h_l signal and the appropriate voltage vector is selected by using a look-up table to control the induction motor drive to obtain a rapid speed response. The torque controller, current controller, and d-q frame transform are constructed by the hardware which reduce the running time of the microcomputer to obtain a high performance drive. Computer simulations and experimental results demonstrate that the proposed method can obtain a high performance induction motor drive. Meanwhile, employing the advantages of the added zero voltage vector to reduce the inverter switching frequency greatly increasing the efficiency of the inverter     

A discrete adaptive induction position servo drive

A discrete adaptive induction position servo is designed and implemented. In the proposed servo system, the dynamic model of the indirect field-oriented induction motor is estimated from measurements using the stochastic approach. Based on this model, a PI speed controller and a P position controller are designed using pole-placement and root-locus techniques. In order to reduce the effects of machine and load parameter variations on the performance of the indirect field-oriented induction motor servo drive, an adaptive controller is augmented in which a reduced reference model, which defines the desired following control performance, is chosen and the adaptive control signal is synthesized. The proposed adaptive controller has the advantages of being easy to design and implement. Simulation and experimental results show that good following and regulating control performances are achieved. Moreover, the performances are rather insensitive to parameter variations     

Compositive adaptive position control of induction motors based onpassivity theory

A passivity-based composite adaptive position control scheme for an induction motor is proposed in this paper. First, the dynamics of the induction motor are proved to be state strictly passive, and a composite adaptation algorithm is proposed to control the position of the induction motor. Then, the global stability of the induction motor position control system is formally proved by the passivity theory. Experimental results are provided to show that the good position tracking can be obtained without any information of the rotor flux. The proposed approach is robust to the variations of motor mechanical parameters and external load disturbances     

A high-performance induction motor drive with on-line rotortime-constant estimation

A high-performance induction motor (IM) speed drive with online adaptive rotor time-constant estimation and a proposed recursive least square (RLS) estimator is introduced in this paper. The estimation of the rotor time-constant is on the basis of the model reference adaptive system (MRAS) theory; and the rotor inertia constant, the damping constant and the disturbed load torque of the IM are estimated by the proposed RLS estimator, which is composed of an RLS estimator and a torque observer. Moreover, an integral proportional (IP) speed controller is designed online according to the estimated rotor parameters; and the observed disturbance torque is fed forward to increase the robustness of the induction motor speed drive     

An observer-based robust adaptive controller for permanent magnet synchronous motor drive with initial rotor angle uncertainty

An observer-based robust adaptive nonlinear position and speed tracking controller is developed for a permanent magnet synchronous motor with initial rotor angle uncertainty. The unknown initial rotor position is treated as a constant motor parameter in the development of the controller. An incremental encoder, which provides relative position variation of the rotor, is used along with stator current signals to achieve stable control. However, the controller does not require the knowledge of motor parameters and it only assumes friction, external disturbances, and model uncertainties are bounded. By using state observers, the measurement of acceleration and load torque, which is required usually in the nonlinear controller design with high tracking performance, is avoided. The stability of the control system and tracking convergence are guaranteed using Lyapunov theory. Finally, the stability and efficacy of the proposed drive system are verified by experimental results.     

A robust control method for a PV-supplied DC motor using universal learning networks

In this paper, a new robust control method and its application to a photovoltaic (PV) supplied, separately excited DC motor loaded with a constant torque is discussed. The robust controller is designed against the load torque changes by using the first and second ordered derivatives of the universal learning networks (ULNs). These derivatives are calculated using the forward propagation algorithm, which is considered as an extended version of real time recurrent learning (RTRL). In this application, two ULNs are used: The first is the ULN identifier trained offline to emulate the dynamic performance of the DC motor system. The second is the ULN controller, which is trained online not only to make the motor speed follow a selected reference signal, but also to make the overall system operate at the maximum power point of the PV source. To investigate the effectiveness of the proposed robust control method, the simulation is carried out at four different values of the robustness coefficient γ in two different stages: The training stage, in which the simulation is done for a constant load torque. And the control stage, in which the controller performance is obtained when the load torque is changed. The simulation results showed that the robustness of the control system is improved although the motor load torque at the control stage is different from that at the training stage.     

A fuzzy adapted field-oriented mechanism for induction motor drive

The detuning of an indirect field-oriented induction motor drive due to variation of rotor resistance may lead to low efficiency and poor transient response. To improve this, an induction motor drive with a fuzzy adapted field-oriented mechanism is proposed. During steady state conditions, an adapted slip angular speed signal is synthesized by a fuzzy controller and used to adjust the original estimate of slip angular speed signal such that minimum stator current is obtained. When the transient due to command or load torque change occurs, the fuzzy tuning mechanism is temporarily inhibited and the final value of the adapted signal is held. A discrete two-degree-of-freedom controller (2DOF) is designed to yield good speed command tracking and load regulating responses. The effectiveness of the proposed motor drive is demonstrated experimentally     

A rotor-flux-observer-based composite adaptive speed controller foran induction motor

A composite adaptive speed controller for an induction motor based on a rotor-flux-observer is proposed in this paper. The rotor flux is estimated with the simplified rotor-flux-observer on the rotor reference frame and the input-output linearization theory is used to decouple the motor speed and the rotor flux. Then, the composite adaptive algorithm is used as the speed controller of the induction motor drive. The resulting system is verified to be stable. Some experimental results are provided to demonstrate the effectiveness of the proposed adaptive controller. Good speed tracking and load regulating responses can be obtained by the proposed composite adaptive controller. Moreover, the system can be operated in a wide range of speed and is robust to parameter variations     

A linear maximum torque per ampere control for IPMSM drives over full-speed range

In this paper, a linear torque control strategy is first proposed for interior permanent magnet synchronous motor drives to fully utilize the reluctance torque and simplify the controller design. The proposed linear torque control strategy also extends the existing maximum torque per ampere control in the constant torque limit region up to the entire field-weakening region. It is found that in an intermediate speed region, called partial field-weakening region, the existing maximum torque per ampere control can still be applied under lighter load condition. In addition, the proposed control can also achieve the objective of minimum copper loss (i.e., maximum torque per ampere) for the entire speed range. Sound theoretical basis is given in the context. Moreover, an adaptive limiter is proposed for efficiently implementing the proposed control strategy over the entire speed range. Finally, a prototype is also constructed by using a fixed-point DSP TMS320F240 and some experimental results are given to verify the validity of the proposed control strategy.     

Real-Time Speed and Flux Adaptive Control of Induction Motors Using Unknown Time-Varying Rotor Resistance and Load Torque

In this paper, an algorithm for direct speed and flux adaptive control of induction motors using unknown time-varying rotor resistance and load torque is described and validated with experimental results. This method is based on the variable structure theories and is potentially useful for adjusting online the induction motor controller unknown parameters (load torque and rotor resistance). The presented nonlinear compensator provides voltage inputs on the basis of rotor speed and stator current measurements, and generates estimates for both the unknown parameters and the nonmeasurable state variables (rotor flux and derivatives of the stator current and voltage) that converge to the corresponding true values. Experiments show that the proposed method achieved very good tracking performance within a wide range of the operation of the induction motor (with online variation of the rotor resistance: up to (87%). This high tracking performance of the rotor resistance variation demonstrates that the proposed adaptive control is beneficial for motor efficiency. The proposed algorithm also presented high decoupling performance and very interesting robustness properties with respect to the variation of the stator resistance (up to 100%), measurement noise, modeling errors, discretization effects, and parameter uncertainties (e.g., inaccuracies on motor inductance values). The other interesting feature of the proposed method is that it is simple and easily implementable in real time. Comparative results have shown that the proposed adaptive control decouples speed and flux tracking while standard field-oriented control does not.      

A Trajectory Planning Approach for the Regulation of the Induction Motor

An output feedback passivity based controller is suitably combined with an off-line trajectory planning for the equilibrium to equilibrium regulation of the nonlinear induction motor. As obtained from computer simulations, the proposed dynamic feedback controller naturally sustains the presence of un-modelled constant load torque perturbations and it is robust with respect to discontinuous variations of the rotor resistance parameter.     

A new composite adaptive speed controller for induction motor basedon feedback linearization

A new adaptive control technique is proposed to control the speed of the induction motor in this paper. First, the rotor flux is estimated with the simplified rotor flux observer on the rotor reference frame and the feedback linearization theory is used to decouple the rotor speed and the flux amplitude. Then, a new composite adaptive control algorithm based on an integral cost function is designed to control the speed of the induction motor. The overall speed control system is verified to be stable and robust to the parameter variations and external disturbances. Experimental results are provided to demonstrate the effectiveness of the presented approach. The good speed tracking and load regulating responses can be obtained by the proposed controller     

High performance speed and position tracking of induction motorsusing multi-layer fuzzy control

An electric drive system is considered high performance when the rotor position or shaft speed can be made to follow a preselected track at all times. The design of tracking controllers for induction motors is difficult due to motor nonlinearities and unknown load dynamics. An extension to fuzzy control, multi-layer fuzzy control (MLFC), is proposed and applied to high performance tracking of induction motors. The MLFC has two layers. The first layer is the execution layer which is made up of small subcontrollers. The second layer is the supervisor layer which fuzzily combines the execution layer subcontrollers to achieve the system objectives. The design and the tuning of the controller is simpler because of the layered topology. The MLFC tracking controllers are tested in the laboratory and their effectiveness in tracking applications is verified. The ease of controller tuning is also demonstrated     

Control of a linear permanent magnet brushless DC motor via exactlinearization methods

The author develops a position controller for permanent magnet brushless DC motors (PMBDCMs) which systematically determines control laws for operation in both the transient and steady-state with consideration of reluctance force. The controller design is based on a differential geometric approach which assists the motor in overcoming its inherent deficiencies, such as effects of torque ripples and reluctance torque. This is achieved by transforming the nonlinear state equations into an exact linear model. Computer simulations of the resulting closed-loop system were performed to demonstrate the effectiveness of the proposed control laws. Simulation results of the control variables were injected into the actual nonlinear system in an experimental open-loop setup to validate the design procedure     

Closed loop torque SVM-DTC based on robust super twisting speed controller for induction motor drive with efficiency optimization

This paper presents a space vector modulation (SVM) based Direct Torque Control strategy (DTC) for induction motor (IM) in order to overcome the drawbacks of the classical DTC. SVM can reduce the high torque and flux ripples by preserving a fixed switching frequency. This technique is known by the closed loop torque SVM-DTC. Moreover, the control scheme performance is improved by inserting a second order sliding mode super twisting controller in the outer loop for speed regulation. This nonlinear technique ensures a good dynamic and high robustness against external disturbance. Furthermore, the IM energy optimization is treated in the second objective of this paper. A proposed model based loss minimization strategy is presented for efficiency optimization. This strategy chooses an optimal flux magnitude for each applied load torque. The proposed optimized SVM-DTC algorithm will be investigated by simulation and real time implementation using Matlab/Simulink with real time interface based on dSpace 1104 signal card.     

Speed and efficiency control of an induction motor withinput-output linearization

A combination of a composite adaptive speed controller and an explicit efficiency control algorithm is proposed to control the speed and power efficiency of the induction motor in this paper. First, the input-output linearization method is used to dynamically decouple the motor speed and rotor flux. Then, a composite adaptive control algorithm is designed to control the speed of the induction motor. At steady-state light-load condition, the magnetizing current command is adjusted on the basis of the product of magnetizing current command and torque current command such that the steady-state power loss is minimum. A PC-based experimental drive system has been implemented, and some experimental results are provided to demonstrate the effectiveness of the presented approach