Optimal frequency tracking method for phase‐shift PWM inverter

This paper proposes a new resonant frequency tracking control method for full‐bridge‐type high‐frequency inverters. Whereas the ordinary phase‐locked loop (PLL) based frequency control method uses a current sensor and a voltage sensor, the proposed technique can achieve the same purpose with a single current sensor. In high‐frequency power supply systems using a PLL, it is impossible to perform power control with an inverter. Therefore, an active converter must be used for power control, and the system grows larger. On the other hand, high‐frequency inverters using the proposed control system simultaneously enable power control and achieve the same resonant frequency tracking as a PLL, and thus high‐frequency power supply systems become extremely simple. This paper explains in detail the principle underlying the control method, and presents an example of a circuit to realize it. The theory is backed up by using a prototype high‐frequency power supply system which actually employs the proposed control system, thereby demonstrating its practical utility in industry. © 2012 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Adaptive fault tolerant control for a class of multi‐input multi‐output nonlinear systems with both sensor and actuator faults

Compared with the fault diagnosis, detection, and isolation literature, very few results are available to discuss control algorithms directly for multi‐input multi‐output nonlinear systems with both sensor and actuator faults in the fault tolerant control literature. In this work, we present a fault tolerant control algorithm to address the system output stabilization problem for a class of multi‐input multi‐output nonlinear systems with both parametric and nonparametric uncertainties, subject to sensor and actuator faults that can be both multiplicative and additive. All elements of the sensor measurements and actuator components can be faulty. Besides, the control input gain function is not fully known. Backstepping method is used in the analysis and control design. We show that under the proposed control scheme, uniformly ultimate boundedness of the system output is guaranteed, while all closed‐loop system signals stay bounded. In the cases where the sensor faults are only multiplicative, exponential convergence of the system state variables into small neighbourhoods around zero is guaranteed. An illustrative example on a robot manipulator model is presented in the end to further demonstrate the effectiveness of the proposed control scheme.     

Adaptive inverse control of unmodeled stable SISO and MIMO linear systems

Adaptive‐signal‐processing techniques have been employed with great success in such applications as: system identification, channel equalization, statistical prediction and noise/echo cancellation. From a mathematical point of view, there is little difference between these applications and the types of operations required by control systems to control a dynamical system. This paper presents an approach to control systems called adaptive inverse control in which adaptive‐signal‐processing techniques are used throughout. Adaptive inverse control comprises three simultaneous processes. The plant is automatically modeled using adaptive system identification techniques. The dynamic response of the system is adaptively controlled using the resulting model and methods related to channel equalization. Adaptive disturbance canceling is performed using methods similar to noise canceling. The method applies directly to stable single‐input single‐output (SISO) and multi‐input multi‐output (MIMO) plants, and does not require an a priori model of the system. If the plant is unstable, it must first be stabilized using conventional feedback. This implies that at least a rudimentary model need be made if the plant is unstable. Once the plant is stabilized, adaptive inverse control may be applied to the stabilized system. Copyright © 2002 John Wiley & Sons, Ltd.     

Digital implementation of biologically inspired Wilson model,population behavior,and learning

Spiking neurons, as a computational unit, are the main part in biological information processing systems. This paper presents a digital hardware implementation of a biological neuron on a field‐programmable gate array due to its high accuracy and high speed, especially for large‐scale simulations which is a key objective in the neuromorphic research field. Although this is a computationally expensive task, the use of more biological realistic system results in higher accuracy in mimicking biological behaviors of neural networks. Given that, the Wilson model is one of the most important biological neuron models that can be used in the architecture of spiking neural networks. To be closer to biological systems, a method is proposed to test the possibility of implementation of the Wilson neuron model on digital platforms. The results of the hardware implementation of the Wilson neuron and a spiking network on a field‐programmable gate array, capable of character recognition with supervised learning algorithm, are presented in this paper; moreover, population behavior of this model is simulated. In large‐scale implementation of 2000 Wilson neuron model, population capability, feasibility, and costs are investigated. This paper presents a method to the implementation of Wilson neurons on digital platforms, suggesting that the available system is an attainable platform for the implementation of large‐scale biologically plausible neural networks on field‐programmable gate array devices. Hardware synthesis, physical implementation on field‐programmable gate array, and theoretical analysis confirm that the proposed model has hardware so that makes it an appropriate model for the large‐scale digital implementation.     

Multi‐objective optimization power control for code division multiple access systems

In code division multiple access (CDMA) communication systems, the communication channel is usually corrupted with time‐varying interferences, which include channel fading, multiple access interference, round‐trip delay, and noise. Power control is an important issue for CDMA systems to achieve higher communication link quality and better system capacity under time‐varying interferences. In the previous studies, most of power control algorithms only considered the user's target signal‐to‐interference‐and‐noise‐ratio (SINR) to maintain quality of service. In this study, a multi‐objective optimization method is proposed for power control design in CDMA systems. With a shadow system and an h _∞ filter to compensate for the round‐trip delay, the proposed power control scheme can simply adjust transmission power to achieve the best compromise between several objectives, such as minimization of SINR deviation, minimization of power consumption, and minimization of the system outage. Several simulation results are given to confirm the performance of the proposed power control scheme. Copyright © 2013 John Wiley & Sons, Ltd.     

磁浮控制系统的传感器非线性校正方法研究

磁浮控制系统采用涡流传感器检测其运行状态.由于控制系统对精度和实时性有较高要求,涡流传感器输入输出特性的非线性和模型随环境的变化需要快速准确的补偿.为此,采用径向基函数网络建立涡流传感器逆模型,使加入逆模型后涡流传感器输入输出映射单位线性化.采用本文提出的简化自适应隐层结构和中心学习算法能够快速准确得到网络结构和参数.实际测量说明,该方法在精度和实时性方面满足要求,校正误差小于0.7%,能够补偿涡流传感器模型的变化.该方法能够用于精度和实时性要求高的其他传感器校正中.     

Active fault tolerant control systems by the semi‐Markov model approach

This paper investigates the active fault tolerant control problem via the H _∞ state feedback controller. Because of the limitations of Markov processes, we apply semi‐Markov process in the system modeling. Two random processes are involved in the system: the failure process and the fault detection process. Therefore, two corresponding semi‐Markov processes are integrated in the closed‐loop system model. This framework can generally accommodate different types of system faults, including the randomly happening sensor faults and actuator faults. A controller is designed to guarantee the closed‐loop system stability with a prescribed noise/disturbance attenuation level. The controller can be readily solved by using convex optimization techniques. A vertical take‐off and landing vehicle example with actuation faults is used to demonstrate the effectiveness of the proposed technique. Copyright © 2013 John Wiley & Sons, Ltd.     

Data‐driven model reference control with asymptotically guaranteed stability

This paper presents a data‐driven controller tuning method that includes a set of constraints for ensuring closed‐loop stability. The approach requires a single experiment and can also be applied to nonminimum‐phase and unstable systems. The tuning scheme generates an estimate of the closed‐loop output error that is used to minimize an approximation of the model reference control problem. The correlation approach is used to deal with the influence of measurement noise. For linearly parameterized controllers, this leads to a convex optimization problem. A sufficient condition for closed‐loop stability is introduced, which can be included in the optimization problem for control design. As the data length tends to infinity, closed‐loop stability is guaranteed. The quality of the estimated controller is analyzed for finite data length. The effectiveness of the proposed method is demonstrated in simulation as well as experimentally on a laboratory‐scale mechanical setup. Copyright © 2010 John Wiley & Sons, Ltd.     

A new position‐sensorless position control method for high‐speed spindle systems

This paper proposes a new position‐sensorless position control method for high‐speed spindle drive systems. Mechanical vulnerability of position sensors such as an encoder mounted on a spindle motor is becoming a serious problem as required speed increases. For high speeds above 1500 rad/s, sensorless drive is preferred. It is possible for current technologies to control spindle motor in speed control mode without the sensor, but not in position control mode without the sensor. In the example of high‐speed spindle systems of automatic machine tools, implements must be automatically attached to and removed from the spindle at standstill. Automation necessitates position control, for which current technologies require a sensor. The proposed method makes it possible to realize pure sensorless high‐speed spindle systems performing in both speed and a position control modes. The method can attain a position control performance with quick settling from speed control and a repetitive positioning precision of 0.006 rad, 0.4°, which is comparable to that achieved by current sensor‐based methods. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(3): 58–69, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10059     

基于EKF在线辨识的多堆燃料电池系统最大效率点跟踪控制方法

为保证多堆燃料电池系统(multi-stack fuel cell system,MFCS)在负载不断变化条件下仍能稳定运行在最大效率点,该文提出了一种基于扩展卡尔曼滤波(extended kalman filter,EKF)在线辨识算法的MFCS最大效率点跟踪控制的方法。该方法利用EKF的实时在线拟合能力,快速实现对MFCS效率/功率曲线的辨识,做到实时估计系统最大效率点功率,并通过功率分配方法实现各个电堆间出力的合理分配,来达到维持系统在最大效率点处稳定运行的目的。最后,在搭建的RT-LAB半实物硬件在环测试平台上,与扰动观测(perturb and observe,P&O)算法进行了对比分析。实验结果证明,该文所提方法能够快速的实时估计MFCS最大效率点功率并且实现跟踪控制,减小燃料电池功率变化率等退化参数,提高燃料电池的耐久性。     

两电机变频系统的支持向量机广义逆内模解耦控制

针对两电机变频系统非线性强耦合的特点,提出基于支持向量机广义逆内模控制的方法。对工作在矢量控制方式下的两电机变频系统数学模型进行广义逆存在性分析,从而得出系统广义逆数学表达式。通过支持向量机来辨识原系统的广义逆系统,然后对复合后所得到的伪线性系统引入了内模控制。该方法结合了支持向量机在小样本上具有良好的非线性建模能力和泛化能力,以及内模控制器易于在线设计的优点,同时兼顾系统的鲁棒稳定性,从而可以有效提高系统的控制效果。仿真和实验结果表明,该方法具有良好的动静态解耦性能,对外界扰动亦有很强的鲁棒稳定性。     

A current sensorless drive system of a synchronous motor with a low‐resolution position sensor

High‐performance drive of synchronous motors such as a permanent magnet synchronous motor and a synchronous reluctance motor can be achieved by current vector control. In such drive systems, the armature current is controlled as a sinusoidal waveform based on rotor position information from a high‐resolution position sensor, and the current vector (d‐ and q‐axis currents) is suitably controlled by current feedback control. This paper proposes a current sensorless drive system with a low‐resolution position sensor in order to simplify the SM drive system. High‐performance current control is achieved in the proposed drive system, where the current sensors are eliminated and the simulated currents are used for current control. The low‐resolution position sensor is used instead of a conventional high‐resolution position sensor, and the higher position information is estimated. The steady‐state and transient characteristics are examined in several experiments with respect to the synchronous reluctance motor and the interior permanent magnet synchronous motor. It is confirmed that sinusoidal current drive, high‐performance current vector control, and speed control can be achieved by the proposed drive system. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 141(4): 34–43, 2002; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10072     

Integration of multiple model based fault detection and nonlinear model predictive fault‐tolerant control

In this paper, we present a new fault‐tolerant control system for a class of nonlinear systems with input constraints. Because of many important factors that stabilize a nonlinear model predictive controller, it can be used as a powerful controller in the event of fault occurrence. So, the reconfigurable controller is designed based on the quasi‐infinite model predictive control (QIMPC) approach as a fault‐tolerant approach. On the other hand, a fault detection and diagnosis (FDD) system is designed based on the multiple model method. The bank of extended Kalman filters (EKFs) is used to detect the predefined actuator fault and estimate the unknown parameters of a fault. When a fault is detected, the proposed FDD information is used to correct the model of the faulty system recursively and reconfigure the controller. Delay on FDD decision may lead to performance degradation or even instability for some systems. The timely proposed FDD approach will preserve stability. Moreover, a framework is presented to ensure stability when a fault occurs. The effectiveness of this method is demonstrated, in comparison with conventional nonlinear model predictive control, by two practical examples. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

反馈有源噪声控制的最近邻多频陷波器模型

反馈有源噪声控制系统结构简单,抗外界干扰能力强,但在对频率成分复杂的噪声控制时通常存在收敛速度慢、控制残差高等缺陷。本文针对工程中常见的离散线谱噪声反馈控制问题设计了一种最近邻-多频陷波器（NNR-MNF）反馈有源控制模型,使用最近邻回归器算法先验计算时域最优滤波器系数的近似解,在参数空间内从一个接近最优解的位置开始训练滤波器参数,使系统能够以一个较小的步长对复杂噪声进行控制,在快速收敛的同时避免系统发散问题。基于驱逐舰轮机噪声真实数据的计算机仿真实验结果表明,NNR-MNF算法相比传统控制方法其收敛时间减少了约70%。该结果说明使用基于机器学习的参数预训练方法能够有效提升噪声有源控制系统的收敛速度,为主动噪声控制问题提供了一种新的优化方案。     

A design of model reference adaptive control systems with unknown disturbances

Recently, a design of model matching and adaptive control systems under the presence of measurement noise employing a nonminimal order state observer was reported. But this method cannot be used for the case where the plant has deterministic disturbances. In this paper, we will show that the idea is also applicable to the case where the plant has both measurement noise and deterministic disturbances. For this purpose, we will employ a direct method of adaptive control where the controller parameters are estimated. © 2000 Scripta Technica, Electr Eng Jpn, 131(3): 51–57, 2000     

Fractional‐order multivariable composite model reference adaptive control

A novel multivariable composite model reference adaptive control scheme is developed for multivariable fractional‐order systems with arbitrary relative degree. Firstly, by introducing right gain matrix to substitute left gain matrix, the stringent symmetry assumption is no longer required. The design procedures of controller with certain and uncertain high‐frequency gain matrix are then provided, respectively. The (robust) stability of the resulting closed‐loop control system is investigated by indirect Lyapunov method. It is shown that the composite model reference adaptive control can achieve better performance on output tracking than that of model reference adaptive control. Finally, the effectiveness and applicability of the proposed control scheme are demonstrated in 3 numerical examples.     

Inverse optimal adaptive control for non‐linear uncertain systems with exogenous disturbances

A Lyapunov‐based inverse optimal adaptive control‐system design problem for non‐linear uncertain systems with exogenous ℒ︁₂ disturbances is considered. Specifically, an inverse optimal adaptive non‐linear control framework is developed to explicitly characterize globally stabilizing disturbance rejection adaptive controllers that minimize a nonlinear‐nonquadratic performance functional for non‐linear cascade and block cascade systems with parametric uncertainty. It is shown that the adaptive Lyapunov function guaranteeing closed‐loop stability is a solution to the Hamilton–Jacobi–Isaacs equation for the controlled system and thus guarantees both optimality and robust stability. Additionally, the adaptive Lyapunov function is dissipative with respect to a weighted input–output energy supply rate guaranteeing closed‐loop disturbance rejection. For special integrand structures of the performance functionals considered, the proposed adaptive controllers additionally guarantee robustness to multiplicative input uncertainty. In the case of linear‐quadratic control it is shown that the operations of parameter estimation and controller design are coupled illustrating the breakdown of the certainty equivalence principle for the optimal adaptive control problem. Finally, the proposed framework is used to design adaptive controllers for jet engine compression systems with uncertain system dynamics. Copyright © 2000 John Wiley & Sons, Ltd.     

基于自抗扰控制器的两电机变频调速系统最小二乘支持向量机逆控制

针对多输入多输出(multiple input multiple output,MIMO)非线性强耦合的两电机变频调速系统,对其数学模型进行可逆性存在分析,进一步设计最小二乘支持向量机(least squares support vector machines,LSSVM)逆系统,串联于两电机系统之前,组成基于阶逆的伪线性复合系统,实现MIMO系统的线性化与解耦。在此基础上,采用自抗扰控制器(active disturbances rejection control,ADRC)抑制伪线性复合系统中非线性因素的作用,引入扩张状态观测器对不确定性的估计,使之参与LSSVM逆模型的构造。仿真和实验结果表明,新型控制策略可以有效减小负载扰动和LSSVM建模误差的影响,具有良好的解耦控制效果和鲁棒性。     

基于逆系统解耦的电磁轴承飞轮转子系统二自由度控制

针对电磁轴承高速飞轮转子系统的振动抑制问题,提出了一种基于逆系统解耦和改进型二自由度控制的方法。首先采用逆系统方法对电磁轴承飞轮转子系统进行解耦,将非线性、强耦合的电磁轴承飞轮转子系统解耦为四个彼此独立的子系统,再用改进型二自由度控制器对解耦后的子系统进行整定,使控制系统的设定值跟踪及外扰抑制特性能够分别调节,并通过速度观测器获取阻尼控制信号,增强系统的抗噪声能力。从理论上分析了所提出控制算法的稳定性、设定值跟踪性能及鲁棒性,并对其性能进行了仿真和实验验证。结果表明,该文提出的控制算法能够使飞轮转子稳定悬浮并有效抑制其振动,具有稳定性好、鲁棒性强、抗噪声能力强等优点。     

Performance assessment of switched control systems based on tensor space approach

Based on tensor space, a new performance assessment approach is proposed for switched control systems in this paper. Switched control system is widely existing in industrial processes, especially in safety‐important processes where the systems controlled may be switched by protection logic during accident. Clearly, bad performance of control and protection strategies will eventually drive the system to a dangerous condition. To treat this problem, one may set up a performance assessment procedure for the switched control systems using multiple model method, where performance is evaluated through assessment of every individual submodel of the switched system. Obviously, this approach ignores interaction nature between control algorithm and protection strategy. The proposed method can capture the interaction nature of control and protection systems. In the tensor space, the interacting relation of control and protection systems can be synthetically represented by adding the logical switching space. Specifically, the tensor space modeling representation for switched systems has been developed, which can actually model the high coupling interaction of control and protection systems. The data‐driven tensor space algorithm based on higher‐order singular value decomposition has also been developed to assess the performance of switched control systems. By using orthogonal projection in tensor space extended from the matrix space, prediction error approach has been employed to obtain the optimal prediction error variance being as the control performance benchmark for performance assessment. Finally, numerical simulation examples are presented to illustrate the rationality and effectiveness of tensor space approach by comparing with the multiple model approach. Copyright © 2015 John Wiley & Sons, Ltd.