基于龙伯格观测器的感应电机预设性能位置跟踪优化控制EI北大核心CSCD

考虑暂稳态约束、控制参数优化及参数摄动和负载扰动等对感应电机位置跟踪控制性能的影响,本文提出了一种基于龙伯格观测器的预设性能优化控制方法.首先,针对电机转子磁链在实际中不可测的问题,采用龙伯格观测器对其进行了快速准确的估计.其次,基于反步法完成感应电机位置预设性能控制器的设计,基于变增益指数趋近律完成感应电机磁链滑模控制器的设计,通过构造干扰观测器对电机系统中由参数摄动和负载扰动引起的不确定项进行观测,实现了对系统给定值准确的跟踪控制.再次,将遗传算法(GA)与改进的粒子群优化(IPSO)算法相结合,对所设计的控制器参数进行优化整定,进一步提高了系统的收敛速度和稳态精度.基于李雅普诺夫稳定性理论分析表:所设计的控制器能够保证位置跟踪误差一直处于预设边界内,且整个闭环系统是全局一致有界稳定的.最后,通过仿真和模拟实验对比分析验证了本文所提方法的有效性及在实际电机系统中应用的可行性.     

Trajectory tracking control of mobile robots without using longitudinal velocity measurements

We propose a new robust trajectory tracking control scheme for wheeled mobile robots without longitudinal velocity measurements. In the proposed controller, a velocity observer is used to estimate the longitudinal velocity of a wheeled mobile robot. A wheeled mobile robot model, including motor dynamics, is used to develop the controller. The developed controller has the following useful properties. (1) The developed controller does not require any accurate knowledge of the robot parameters or the motor parameters. Even if there are uncertainties in the robot dynamics, including the motor properties, it is certain that tracking errors ultimately become uniformly bounded in a closed-loop system using the developed controller. (2) It is shown theoretically that the ultimate norms of tracking errors can easily be reduced by setting only one design parameter.     

Adaptive control of flexible link manipulators using a pseudolink dynamic model

This paper presents a novel adaptive control scheme for a lightweight manipulator arm governed by electric motors. The controller design is based on the dynamic model of the arm in a quasi-static approximation which consists of the transports subsystem and the motor equations corrected for the elastic compliance of the plant. A passivity property of the flexible electromechanical system is established and an adaptive motor controller is developed which contains the rigid manipulator controller as a part. The motor controller updates all unknown rigid manipulator parameters as well as elastic parameters and ensures global asymptotic stability of the tracking errors with all signals in the system remaining bounded. Projecting of parameter estimates is used in the update law to avoid possible singularities when generating control input. Simulation results for a single-link elastic arm confirm the validity and demonstrate advantages of the proposed method.     

Feedback linearisation control of an induction machine augmented by single-hidden layer neural networks

We consider adaptive output feedback control methodology of highly uncertain nonlinear systems with both parametric uncertainties and unmodelled dynamics. The approach is also applicable to systems of unknown, but bounded dimension. However, the relative degree of the regulated output is assumed to be known. This new control strategy is proposed to address the tracking problem of an induction motor based on a modified field-oriented control method. The obtained controller is then augmented by an online neural network that serves as an approximator for the neglected dynamics and modelling errors. The network weight adaptation rule is derived from the Lyapunov stability analysis, that guarantees boundedness of all the error signals of the closed-loop system. Computer simulations of an output feedback controlled induction machine, augmented via single-hidden-layer neural networks, demonstrate the practical potential of the proposed control algorithm.     

方波型无刷直流电机的电压跟踪控制策略

针对方波型无刷直流电机控制系统的电压跟踪控制问题,利用非线性系统理论获得一种关于角速度的非线性降阶观测器,以及一种简单、易于应用的非线性位置反馈控制器.理论上,论证了在所设计的控制器作用下,该受控系统能实现全局一致毕竟有界.数值实验显示该控制器具有很好的普适性,以及此系统能快速跟踪额定电压范围内的参考电压,转矩脉动能被有效抑制.     

Adaptive output-feedback control of induction motors

In this paper, we design an adaptive controller for the induction motor which ensures global asymptotic rotor velocity tracking performance and global exponential rotor flux tracking. In addition, the controller compensates for parametric uncertainty associated with the mechanical subsystem and only requires rotor velocity measurements. Experimental results are provided to illustrate the performance of the controller.     

感应电机转矩跟踪无源控制及自适应观测器设计

针对感应电机高性能转矩跟踪控制和磁链难以直接测量问题,提出了基于无源性的转矩跟踪和自适应磁链观测器控制方案.首先基于感应电机的无源性特性设计了渐近稳定转矩跟踪控制器,重新配置了系统的平衡点,通过注入阻尼提高系统的收敛速度.然后通过将定子电流和转子磁链作为状态变量构建了自适应磁链观测器,简化了观测器结构,根据Lyapunov稳定性理论设计了自适应控制律,实现转子磁链、转速和定子电阻的在线估计.为减小转速估计误差对观测器的影响,给出了观测器增益矩阵的选择方法.仿真结果表明本文所提出的基于自适应观测器的无源控制方案能够有效提高感应电机的动静态性能.     

ON STABILITY AND PERFORMANCE OF INDUCTION MOTOR SPEED DRIVES WITH SLIDING MODE CURRENT CONTROL

A novel inner loop sliding mode current control scheme for induction motor speed drives is proposed in this paper. The controller design is based on the nonlinear mathematical model of an induction motor in a coordinate system oriented along the rotor flux. The parameters of the PI speed controller are taken into consideration in the inner loop sliding mode current control. Rigorous stability verification for the overall system is provided in this paper. The chattering in sliding mode control is attenuated using the reaching law design method. The experimental results show that the proposed approach exhibits robust tracking performance in the presence of motor parameter variations and load disturbances.     

Adaptive nonlinear control of induction motor

This work addresses the problem of controlling a rigid arm (one degree of freedom robot manipulator) directly driven by an induction motor. A Lyapunov-based adaptive nonlinear controller is designed. The developed controller compensates for parametric uncertainty associated with the resistance of the rotor windings and it is capable to track asymptotically a trajectory for an angular position keeping all the internal signals bounded and guarantees the asymptotical stability of the system. Simulations are presented to illustrate the performance of this controller.     

State feedback tracking control for indirect field-oriented induction motor using fuzzy approach

This paper deals with the synthesis of fuzzy controller applied to the induction motor with a guaranteed model reference tracking performance. First, the Takagi-Sugeno (T-S) fuzzy model is used to approximate the nonlinear system in the synchronous d-q frame rotating with field-oriented control strategy. Then, a fuzzy state feedback controller is designed to reduce the tracking error by minimizing the disturbance level. The proposed controller is based on a T-S reference model in which the desired trajectory has been specified. The inaccessible rotor flux is estimated by a T-S fuzzy observer. The developed approach for the controller design is based on the synthesis of an augmented fuzzy model which regroups the model of induction machine, fuzzy observer, and reference model. The gains of the observer and controller are obtained by solving a set of linear matrix inequalities (LMIs). Finally, simulation and experimental results are given to show the performance of the observer-based tracking controller.     

方波型无刷直流电机的跟踪控制及扰动衰减

针对含随机扰动的方波型无刷直流电机的电压跟踪,引入饱和向量值函数及自适应参数,设计一种简单的、含饱和项的自适应非线性控制器克服电压跟踪中出现的电压饱和现象及抑制随机扰动,使受控系统跟踪参考电压信号．从理论上论证受控系统在设计的控制器作用下是全局一致毕竟有界．数值实验显示该控制器能使受控系统实现扰动衰减,电压跟踪效果较好．     

A globally stable saturated desired compensation adaptive robust control for linear motor systems with comparative experiments

The recently proposed saturated adaptive robust controller is integrated with desired trajectory compensation to achieve global stability with much improved tracking performance. The algorithm is tested on a linear motor drive system which has limited control effort and is subject to parametric uncertainties, unmodeled nonlinearities, and external disturbances. Global stability is achieved by employing back-stepping design with bounded (virtual) control input in each step. A guaranteed transient performance and final tracking accuracy is achieved by incorporating the well-developed adaptive robust controller with effective parameter identifier. Signal noise that affects the adaptation function is alleviated by replacing the noisy velocity signal with the cleaner position feedback. Furthermore, asymptotic output tracking can be achieved when only parametric uncertainties are present.     

Real Time Implementation of Fuzzy Gain Scheduling of PI Controller for Induction Motor Machine Control

In this work the control of an induction motor using fuzzy gain scheduling of PI controller (adaptive FLC-PI) is presented. Fuzzy rules are utilized on-line to determine the controller parameters based on tracking error and its first time derivative. Simulation and experimental results of the proposed scheme show good performances compared to the PI controller with fixed parameters.     

Partial state feedback control of induction motors with magnetic saturation: elimination of flux measurements

In this paper, we present a singularity-free, rotor position tracking controller for the full order, nonlinear dynamic model of the induction motor that includes the effects of magnetic saturation. Specifically, by utilizing the π-equivalent saturation model, we design an observer/controller strategy that achieves semi-global exponential rotor position tracking and only requires stator current, rotor velocity, and rotor position measurements. Simulation and experimental results are included to demonstrate the efficacy of the proposed algorithm.     

自适应有限拍感应电机电流控制器设计

基于有限拍方法设计了一种自适应矢量控制感应电机的电流控制器.通过差分消去电机模型中的反电动势,利用补偿电压进一步消除电流误差.针对电流控制器对电机参数变化敏感的问题,对电机参数进行在线辨识,保证控制器参数与电机的实际参数一致.仿真结果表明,定子电流在参数变化时能够实现对参考电流的快速跟踪,同时能获得良好的稳态性能.     

Induction motor servo drive using robust PID-like neuro-fuzzy controller

A robust PID-like neuro-fuzzy controller, which has an ability to compensate for parameter variation, is proposed and applied to the speed control of the indirect vector-controlled induction motor. The controller gains are adjusted on-line using the tuning algorithm based on an artificial neural network (ANN). And a variable learning rate algorithm is proposed to improve the tracking performance while keeping the robustness. Simulation and experimental results confirm that good dynamic performance and high robustness to parameter variation and disturbance can be achieved by means of the proposed controller.     

Passivity-based torque and flux tracking for induction motors with magnetic saturation

An observer-based, globally asymptotically stable torque and rotor flux magnitude tracking controller for induction motors under magnetic saturation is proposed. The controller is synthesized using the passivity-based techniques. The paper considers a magnetically saturated π-model of the motor without any simplifying assumptions. Motor fluxes are reconstructed by a closed-loop observer. Closed-loop stability of the overall scheme including the observer is demonstrated. Simulation results are given to illustrate the proposed scheme.     

Adaptive output feedback tracking control for a class of uncertain nonlinear systems using neural networks.

This correspondence addresses the problem of designing robust tracking control for a class of uncertain nonlinear MIMO second-order systems. An adaptive neural-network-based output feedback tracking controller is constructed such that all the states and signals involved are uniformly bounded and the tracking error is uniformly ultimately bounded. Only the output measurement is required for feedback. The implementation of the neural network basis functions depends only on the desired reference trajectory. Therefore, the intelligent adaptive output feedback controller developed here possesses the properties of computational simplicity and easy implementation. A simulation example of controlling mass-spring-damper mechanical systems is made to confirm the effectiveness and performance of the developed control scheme.     

Adaptive speed control for induction motors based on a semi-current-fed model

This paper presents a semi-current-fed concept and a virtual desired variable synthesis for induction motor control. First, the traditional ideal current-loop assumption is relaxed. The relaxed assumption, considering more practical situations, allows a bounded stator voltage and a finite absolute-integral of current tracking error. From this novel concept, a semi-current-fed model for induction motors is used for the design. Both unknown rotor resistance and torque load are considered along with immeasurable rotor flux. To cope with the problems, we use a virtual desired variable approach to synthesize the control law. In the absence of a flux sensor and not using a flux observer, the asymptotic speed tracking is ensured without needing the persistent excitation condition. However, if the controlled system is persistently excited, an optimal torque control is additionally achieved. In addition to the theoretical proof, experimental results show the expected tracking performance.     

Robust backstepping output tracking control for SISO uncertain nonlinear systems with unknown virtual control coefficients

The output tracking controller design problem is dealt with for a class of nonlinear strict-feedback form systems in the presence of nonlinear uncertainties, external disturbance, unmodelled dynamics and unknown time-varying virtual control coefficients. A new method based on signal compensation is proposed to design a linear time-invariant robust controller, which consists of a nominal controller and a robust compensator. It is shown that the closed-loop control system with a controller designed by the proposed method has robust asymptotical practical tracking property for any bounded initial conditions and robust tracking transient property if all initial states are zero.