Comparative study of adaptive and inherently sensorless observers for variable-speed induction-motor drives

State observers are key components of modern ac drives. The paper presents a comparative analysis of two state observers for induction-motor (IM) drives: the speed-adaptive observer and the inherently sensorless observer. The adaptive observer employs the time-variable full-order motor model with the rotor speed as the adaptive quantity. Thus, the speed estimation accuracy significantly impacts on the flux observer. It is shown that the popular model reference adaptive system (MRAS) speed estimator displays reduced bandwidth, and does not deliver adequate performance for the flux estimation. The inherently sensorless observer employs a full-order dual reference-frame model in order to eliminate the speed adaptation. In this way, it becomes decoupled from the speed estimator and its performance is superior to that of its adaptive counterpart. Theoretical aspects and comparative simulation results are discussed for both observers. Comparative experimental results for both observers are presented. Very low-speed-operation (3 r/min) capability of the drive with the sensorless observer is demonstrated.     

A Hybrid-Type Variable-Structure Instantaneous Torque Control With a Robust Adaptive Torque Observer for a High-Performance Direct-Drive PMSM

This paper describes a novel instantaneous torque control scheme for a high-performance direct-drive permanent-magnet synchronous motor. The scheme consists of a robust adaptive instantaneous torque observer and a hybrid-type variable-structure instantaneous torque controller. First, to robustly obtain the instantaneous electromagnetic torque information, a robust adaptive torque observer is designed by considering all possible current model uncertainties. The observation gains and uncertainties prediction rules are derived in the sense of Lyapunov theory so that the stability of the proposed estimation scheme is fulfilled. Second, to ensure perfect tracking of the output torque and providing means in eliminating torque ripples, the frequency modes of the disturbances to be eliminated should be included in the stable closed-loop system. To achieve this objective, a hybrid-type variable-structure controller with internal model, for the flux harmonics and system uncertainties, is adopted. The hybrid controller shows better disturbance rejection without control chattering. Comparative evaluation results are presented to demonstrate the validity and effectiveness of the proposed instantaneous torque control scheme.     

Sensorless Control of Induction Machines by a New Neural Algorithm: The TLS EXIN Neuron

This paper proposes two speed observers for high-performance induction machine drives, both adopting an online adaptation law based on a new total least-squares (TLS) technique: the TLS EXIN neuron. The first is a model reference adaptive system (MRAS) observer with a neural adaptive integrator in the reference model and a neural adaptive model trained online by the TLS EXIN neuron. This observer, presented in a previous article of the authors, has been improved here in two aspects: first, the neural adaptive integrator has been modified to make its learning factor vary according to the reference speed of the drive, second, a neural adaptive model based on the modified Euler integration has been proposed to solve the discretization instability problem in field-weakening. The second observer is a new full-order adaptive one based on the state equations of the induction machine, where the speed is estimated by means of a TLS EXIN adaptation technique. Both these observers have been provided with an inverter nonlinearity compensation algorithm and with techniques for the online estimation of the stator resistance of the machine. Moreover, a thorough theoretical stability analysis has been developed for them both, with particular reference to the field-weakening region behavior for the TLS MRAS observer and to the regenerating mode at low speeds for the TLS adaptive observer. Both speed observers have been verified in numerical simulation and experimentally on a test setup, and have also been compared experimentally with the BPN MRAS observer, the classic adaptive observer and with an open-loop estimator. Results show that both proposed observers outperform all other three observers in every working condition, with the TLS adaptive observer resulting in a better performance than the TLS MRAS observer     

Design of Luenberger state observers using fixed-structure H/sub /spl infin// optimization and its application to fault detection in lane-keeping control of automated vehicles

Lane-keeping control forms an integral part of fully automated intelligent vehicle highway systems (IVHS) and its reliable operation is critical to the operation of an automated highway. We present the design of a fault detection filter for the lane-keeping control systems onboard vehicles used by California-PATH, USA in its automated highways program. We use a Luenberger structure for the fault detection filters and tune the observer gains based on an H/sub /spl infin//-based cost. Such a choice of cost was motivated by the need to explicitly incorporate frequency-domain-based performance objectives. The linear matrix inequality (LMI)-based formulation of an H/sub /spl infin// optimization problem of Luenberger state observers does not allow for the augmentation with dynamic performance weightings in the optimization objective, since it makes the problem a nonconvex optimization problem. We present an algorithm to locally solve the problem of the design of Luenberger state observers using H/sub /spl infin// optimization by transforming the problem into an H/sub /spl infin// static output feedback controller problem. Experimental results demonstrate the efficacy of the tuning methodology by comparing the fault detection performance of filters that use H/sub /spl infin// Luenberger observers versus those that use Kalman filters. Implementation issues of the observers are also discussed.     

Sliding-mode MRAS speed estimators for sensorless vector control of induction Machine

This paper presents two novel sliding mode (SM) model reference adaptive system (MRAS) observers for speed estimation in a sensorless-vector-controlled induction-machine drive. Both methods use the flux estimated by the voltage model observer as the reference and construct SM flux observers that allow speed estimation. Stability and dynamics of the two proposed SM flux observers are discussed. The observers are compared with the classical MRAS observer. The proposed estimators seem very robust and easy to tune. Unlike the classical MRAS, the speed-estimation process is based on algebraic calculations that do not exhibit underdamped poles or zeros on the right-hand plane. Simulations and experimental results on a 1/4-hp three-phase induction machine confirm the validity of the approaches.     

Virtual sensor: application to vehicle sideslip angle and transversal forces

This paper compares four observers (virtual sensors) of vehicle sideslip angle and lateral forces. The first is linear and uses a linear vehicle model. The remaining observers use an extended nonlinear model. The three nonlinear observers are: extended Luenberger observer, extended Kalman filter and sliding-mode observer. Modeling, model simplification, and observers are described, and an observability analysis is performed for the entire vehicle trajectory. The paper also deals with three different sets of sensors to see the impact of observers results. Comparison is first done by simulation on a valid vehicle simulator, and then observers are used on experimental data. Our study shows that observers are more accurate than simple models as regards unmeasurable variables such as sideslip angle and transversal forces. It also shows that speed of center of gravity is not an indispensable variable here.     

MRAS Observers for Sensorless Control of Doubly-Fed Induction Generators

This paper addresses the analysis and performance of several model reference adaptive system (MRAS) observers for sensorless vector control of doubly-fed induction machines. Small signal models allow the formal analysis of the observers for a given dynamic. The performance of each MRAS observer is analyzed, considering grid-connected and stand-alone operation. The MRAS observers are implemented in a 3.5 kW experimental prototype composed of a doubly-fed induction generator and a wind turbine emulator. Experimental results validate the predictions of the small signal models and demonstrate the performance of the sensorless methods during both steady state and variable speed wind energy generation.     

Decentralized nonlinear adaptive control for multimachine power systems via high-gain perturbation observer

This paper presents two novel decentralized nonlinear adaptive controllers (DNAC) for large-scale interconnected power systems, via state-feedback and output-feedback strategies respectively. In the both controllers, system perturbation, which includes all subsystem nonlinearities and interactions between subsystems, is estimated by a high-gain observer and then involved the decentralized adaptive feedback linearizing control law. For the first DNAC, when all subsystem states are available, a second-order high-gain perturbation observer is designed to estimate the system perturbation, which leads to a decentralized nonlinear adaptive state-feedback controller. For the second, a decentralized nonlinear adaptive output-feedback controller is designed using a high-gain states and perturbation observer, when only one subsystem state is measured. The stability of the closed-loop controller/observer system is analyzed by the Lyapunov direct method. Both the controllers have been evaluated in a simulation study based on a three-machine power system. The results show that with a simple structure, both the controllers have robust performance of improving the transient stability and damping of multimode oscillations, under different power-system operation and fault conditions.     

Robust adaptive control of a three-axis motion Simulator with state observers

The development of a nonlinear robust adaptive tracking control system for a three-axis motion simulator is presented in this paper. The motion simulator is used to test and calibrate certain spacecraft instruments within a hardware-in-the-loop environment. Permanent magnet synchronous motor (PMSM) drives are used as simulator actuators. The control system is developed based on Lyapunov stability theory for which only rotor position and stator current signals are required. By using mechanical and electrical state observers, the measurement of acceleration and load torque which is usually required when motor dynamics are considered, is avoided. The control system can be made adaptable to constant unknown motor parameters and load inertia and robust to unknown but bounded fast varying disturbances. Simulation and experimental results are presented to verify the stability and efficacy of the proposed control system.     

Robust speed control of IM with torque feedforward control

The authors describe a digital signal processor-based (DSP-based) robust speed control for an induction motor (IM) with the load-torque observer and the torque feedforward control. In the proposed system, the load torque is estimated by the minimal-order state observer based on the torque component of a vector-controlled IM. Using the load-torque observer, a speed controller can be provided with a torque feedforward loop, thus realizing a robust speed control system. The control system is composed of a DSP-based controller, a voltage-fed pulsewidth modulated (PWM) transistor inverter and a 3.7 kW IM system. An eccentric load with an arm and a weight is coupled to the IM and it generates the sinusoidal gravitational fluctuating torque. Experimental results show robustness against disturbance torque and system parameter change     

基于龙贝格观测器的PMSM无位置传感器控制系统设计

针对基于低分辨率霍尔位置传感器的永磁同步电机系统在中高速时出现的估算精度低与响应速度慢等问题,在建立永磁同步电机数学模型的基础上,将龙贝格观测器与锁相环结构相结合,提出一种永磁同步电机无位置传感器控制算法。利用MATLAB/Simulink工具搭建控制系统仿真模型验证该控制系统的可行性,并通过搭建基于PAC5232的实物平台对比验证龙贝格观测器相对于霍尔位置传感器的优越性。实验结果表明,该无位置传感器控制系统有效地提高了系统的响应速度和估算精度,使其能够更好地跟踪转子速度以及转子位置信息。     

Reduced-order extended luenberger observer based sensorless vector control driven by matrix converter with nonlinearity compensation

This paper presents a new sensorless vector control system for high-performance induction motor drives fed by a matrix converter with nonlinearity compensation. The nonlinear voltage distortion that is caused by commutation delay and ON-state voltage drop in the switching devices is corrected by a new matrix converter model. A reduced-order extended Luenberger observer is employed to bring better response in the whole speed operation range, and a method to select the observer gain is presented. Experimental results are shown to illustrate the performance of the proposed system.     

A newly robust controller design for the position control ofpermanent-magnet synchronous motor

A robust controller which is designed by employing variable-structure control and linear-quadratic method is presented for a permanent-magnet synchronous motor (PMSM) position control system. It is to achieve accurate control performance in the presence of plant parameter variation and load disturbance. In addition, it possesses the design flexibility of the conventional state feedback control. It is applied to the position control of a PMSM. Simulation and experimental results show that the proposed approach gives a better position response and is robust to parameter variations and load disturbance     

Adaptive positioning control for a LPMSM drive based on adapted inverse model and robust disturbance observer

The adaptive robust positioning control for a linear permanent magnet synchronous motor drive based on adapted inverse model and robust disturbance observer is studied in this paper. First, a model following two-degrees-of-freedom controller consisting of a command feedforward controller (FFC) and a feedback controller (FBC) is developed. According to the estimated motor drive dynamic model and the given position tracking response, the inner speed controller is first designed. Then, the transfer function of FFC is found based on the inverse model of inner speed closed-loop and the chosen reference model. The practically unrealizable problem possessed by traditional feedforward control is avoided by the proposed FFC. As to the FBC, it is quantitatively designed using reduced plant model to meet the specified load force regulation control specifications. In dealing with the robust control, a disturbance observer based robust control scheme and a parameter identifier are developed. The key parameters in the robust control scheme are designed considering the effect of system dead-time. The identification mechanism is devised to obtain the parameter uncertainties from the observed disturbance signal. Then by online adapting the parameters set in the FFC according to the identified parameters, the nonideal disturbance observer based robust control can be corrected to yield very close model following position tracking control. Meanwhile, the regulation control performance is also further improved by the robust control. In the proposed identification scheme, the effect of a nonideal differentiator in the accuracy of identification results is taken into account, and the compromise between performance, stability, and control effort limit is also considered in the whole proposed control scheme.     

A nonlinear speed control for a PM synchronous motor using a simpledisturbance estimation technique

A nonlinear speed control for a permanent-magnet (PM) synchronous motor using a simple disturbance estimation technique is presented. By using a feedback linearization scheme, the nonlinear motor model can be linearized in the Brunovski canonical form, and the speed controller can be easily designed based on the linearized model. This technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. An adaptive linearization technique and a sliding-mode control technique have been reported. Although good performance can be obtained, the controller designs are quite complex. To overcome this drawback, the controller parameters are estimated by using a disturbance observer theory where the disturbance torque and flux linkage are estimated. Since only the two reduced-order observers are used for the parameter estimation, the observer designs are considerably simple and the computational load of the controller for parameter estimation is negligibly small. The nonlinear disturbances caused by the incomplete linearization can be effectively compensated by using this control scheme. Thus, a desired dynamic performance and a zero steady-state error can be obtained. The proposed control scheme is implemented on a PM synchronous motor using a digital signal processor (TMS320C31) and the effectiveness is verified through the comparative simulations and experiments     

Robust-adaptive-observer design based on /spl gamma/-positive real problem for sensorless induction-motor drives

This paper proposes a design of a robust-adaptive full-order observer based on the /spl gamma/-positive real problem for sensorless induction-motor drives. The adaptive full-order observer is known to become unstable in a major part of the regenerating-mode low-speed operation, and this prevents the sensorless vector controller from operating an induction motor successfully. In this paper, a design of the observer gain for both stable speed identification and robust flux phase estimation and an adaptive scheme for stator resistance identification are proposed. First, the error system of the adaptive full-order observer is reconsidered-requirements of this observer with a speed identifier are described, in which a simple robust observer gain design in the sense of H/sub /spl infin// optimization is not useful in reality. Next, in order to satisfy all the requirements of the robust adaptive observer, the design of the observer gain based on the /spl gamma/-positive real problem and the adaptive scheme for stator resistance are described. Finally, several experimental results show the feasibility and effectiveness of the proposed design.     

Identification/Observation Using an Extended Luenberger Observer

This paper introduces a theory of parameter identification using an extended Luenberger observer. State augmentation is used to represent the unknown parameters, and an extended observer/ identifier is utilized to provide both state reconstruction and parameter identification. Conditions for convergence are established, and conditions are defined for the observability of the augmented system.     

Decoupled stator-flux-oriented induction motor drive with fuzzyneural network uncertainty observer

A stator-flux-oriented induction motor drive using online rotor time-constant estimation with a robust speed controller is introduced in this paper. The estimation of the rotor time constant is made on the basis of the model reference adaptive system using an energy function. The estimated rotor time-constant is used in the current-decoupled controller, which is designed to decouple the torque and flux in the stator-flux-field-oriented control. Moreover, a robust speed controller, which is comprised of an integral-proportional speed controller and a fuzzy neural network uncertainty observer, is designed to increase the robustness of the speed control loop. The effectiveness of the proposed control scheme is demonstrated by simulation and experimental results     

Sliding-mode observer and improved integrator with DC-offset compensation for flux estimation in sensorless-controlled induction motors

Two flux observers for wide speed range direct torque control (DTC) of sensorless induction-motor drives are presented and compared. The first one is a full-order sliding-mode observer with proportional plus integral (PI) compensation, without rotor speed adaptation. The second one is based on a zero phase-delay-improved integrator of the voltage model, which uses only a PI flux amplitude control with stator-flux reference magnitude in the correction loop. In both cases, an estimated dc offset is built up and memorized by the PI integral component and this totally compensates for all dc offsets and drifts originated in the acquisition channels. Two feasible solutions for on-line stator-resistance identification are proposed. Simulation and experimental results prove the accuracy, robustness, and high-dynamic performance of both observers when employed in sensorless DTC drives. The effectiveness of state estimation is confirmed by a steady state and transient sensorless operation at very low speed with rated load torque and step-speed reversal.     

A Globally Stable, Load-Independent Pressure Observer for the Servo Control of Pneumatic Actuators

Pneumatic actuators are governed by nonlinear dynamics. Thus, robust precision motion control of pneumatic systems requires model-based control techniques such as sliding-mode and/or adaptive control. These controllers typically require full-state knowledge of the system, i.e., pressure, position, velocity, and acceleration. For measuring pressure states, pneumatic servo systems require two expensive pressure sensors per axis, and hence, it makes the system economically noncompetitive with most electromagnetic types of actuation. This paper presents the development of a Lyapunov-based pressure observer for pneumatically actuated systems. The pressure observer is energy-based and has the useful feature of not requiring a model for the load of the system, i.e., it is load-independent. This pressure observer is proven to be globally stable with the added feature of having a response bandwidth equal to that of the modeled pressure dynamics. A robust observer-based controller is developed to obtain a low-cost precision pneumatic servo system. Experimental results are presented that demonstrate and validate the effectiveness of the proposed observer.