Robustness of linear time‐varying systems with relaxed excitation

It is a well‐known fact that linear time‐varying systems with a persistently excited state matrix are exponentially converging and input‐to‐state stable with respect to additive perturbations. Recently, several relaxed conditions of persistent excitation have been presented, which ensure an asymptotic convergence rate in the system. In the present work, it is shown that these conditions are similar and that, under such a relaxed excitation, only nonuniform in time input‐to‐state stability and integral input‐to‐state stability properties can be obtained. The results are illustrated by simulations for a problem of estimation in the linear regression model.     

Composite learning adaptive backstepping control using neural networks with compact supports

The ability to learn is crucial for neural network (NN) control as it is able to enhance the overall stability and robustness of control systems. In this study, a composite learning control strategy is proposed for a class of strict‐feedback nonlinear systems with mismatched uncertainties, where raised‐cosine radial basis function NNs with compact supports are applied to approximate system uncertainties. Both online historical data and instantaneous data are utilized to update NN weights. Practical exponential stability of the closed‐loop system is established under a weak excitation condition termed interval excitation. The proposed approach ensures fast parameter convergence, implying an exact estimation of plant uncertainties, without the trajectory of NN inputs being recurrent and the time derivation of plant states. The raised‐cosine radial basis function NNs applied not only reduces computational cost but also facilitates the exact determination of a subregressor activated along any trajectory of NN inputs so that the interval excitation condition is verifiable. Numerical results have verified validity and superiority of the proposed approach.     

Power supply systems for rapid cycling synchrotron

JAEA and KEK are jointly constructing the high‐intensity proton accelerator project J‐PARC. Its main accelerator is a 3‐GeV rapid cycling synchrotron (RCS). Two types of resonant excitation systems, parallel and cascade, are introduced to excite DC biased 25‐Hz AC currents through its main magnets. The parallel excitation is adopted for the dipole magnet power supply system, and the cascade excitations are adopted for the seven family quadrupole magnets system. In this paper, the two systems are investigated and analyzed, and an explanation is given as to why the different types are adopted in each system. The authors believe that such hybrid exciting systems are most suitable for a high‐power RCS. © 2007 Wiley Periodicals, Inc. Electr Eng Jpn, 160(1): 49–60, 2007; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.20535     

Noncontact energy transfer system using immittance converter

Noncontact energy transfer systems are widely used in industrial material handling systems. This paper proposes a new noncontact energy transfer system using a tuned pickup coil and an immitance converter inductively coupled to a parallel transmission line excited by a high‐frequency constant‐current source. In a noncontact energy transfer system which supplies continuous energy to movers by electromagnetic induction, the efficiency is low owing to low excitation impedance because of the wide air gap of the magnetic core in the pickup coil. The excitation impedance can be increased by the resonance with a capacitor connected parallel to the pickup coil. The resonant pickup coil works as a high‐frequency constant‐current source for the load. We propose using an immittance converter to transform the high‐frequency constant‐current source into a high‐frequency constant‐voltage source. Then, the high‐frequency constant‐voltage source is rectified into a constant‐voltage dc source, and supplies power to an inverter for motor driving. In this paper, the configuration of this new noncontact energy transfer system and its characteristics are described. The experimental results and simulation waveforms are also described. © 2001 Scripta Technica, Electr Eng Jpn, 136(4): 58–64, 2001     

Rotor oscillation damping of a stepping motor by sliding mode control

Stepping motors are used mainly in OA and FA systems due to the merits of their digital driving behavior using switching devices. They are driven by closed‐loop control in systems where special performance such as prevention of out‐of‐synchronism or a high‐speed drive is required. It is well known that rotor oscillation is one of the principal problems in the switched drive of a stepping motor, and nowadays several methods for damping this oscillation have been suggested in which the switching sequence is changed in some manner. In such methods, the excitation time of the stator windings must be tuned appropriately, or the effect of damping is insufficient and oscillation may be even amplified in some circumstances. To resolve this problem, adaptive methods for tuning of the excitation time have been developed. However, they suffer the disadvantage that they require a tuning period for the excitation time to attain the optimal value at the beginning of control or when the machine parameters are varied by changing the driving condition. The authors have developed a new method for rotor oscillation damping of a stepping motor in a closed‐loop system. It is based on a sliding mode control technique and is designed to be robust to variation of rotor inertia which significantly affects the oscillatory characteristic. In this method, a lower‐order dynamical model, obtained by reaching a sliding mode where the angle‐torque characteristic of the motor is bound to a certain linear function, is made non‐oscillatory by pole assignment over a certain region of varying rotor inertia. Applying this method to an experimental system, rotor oscillation is damped excellently in the cases of single‐step and low‐speed multi‐step drive. On the other hand, it is shown deceleration is needed near the last step in the case of a high‐speed drive. © 1998 Scripta Technica, Electr Eng Jpn, 126(1): 42–51, 1999     

A globally convergent direct adaptive pole‐placement controller for nonminimum phase systems with relaxed excitation assumptions

In this paper, we propose the first solution to the long‐standing problem of designing a globally convergent direct adaptive pole‐placement controller for linear, time‐invariant discrete‐time systems with arbitrary zeros that does not rely on persistency of excitation assumptions. As is well known, the main difficulty of this design is that it involves the estimation of parameters that enter nonlinearly in the regression model. This problem can be overcome introducing an overparameterized representation of the system, which imposes very strict persistency of excitation conditions to prove the parameter convergence. The latter is avoided here using a new version of the dynamic regressor extension and mixing parameter estimator recently proposed in the literature. The main feature of this estimator is that it generates, out of an m‐dimensional vector regression, m scalar regression models. This property allows us to estimate only the controller parameters of interest for the adaptive implementation, whose convergence is ensured under assumptions that are strictly weaker than the classical persistency of excitation requirement. Simulation results that illustrate the performance of the proposed scheme are also presented.     

The innovation algorithms for multivariable state‐space models

This paper derives the input‐output representation of the dynamical system described by a linear multivariable state‐space model and the corresponding multivariate linear regressive model (ie, multivariate equation‐error model). A projection identification algorithm, a multivariate stochastic gradient identification algorithm, and a multi‐innovation stochastic gradient (MISG) identification algorithm are proposed for multivariate equation‐error systems by using the negative gradient search and the multi‐innovation identification theory. The convergence analysis of the MISG algorithm indicates that the parameter estimation errors converge to zero under the persistent excitation condition. Finally, a numerical example illustrates the effectiveness of the proposed algorithms.     

Composite learning fuzzy synchronization for incommensurate fractional‐order chaotic systems with time‐varying delays

This paper presents a composite learning fuzzy control to synchronize two different uncertain incommensurate fractional‐order time‐varying delayed chaotic systems with unknown external disturbances and mismatched parametric uncertainties via the Takagi‐Sugeno fuzzy method. An adaptive controller together with fractional‐order composite learning laws is designed based on both a parallel distributed compensation technology and a fractional Lyapunov criterion. The boundedness of all variables in the closed‐loop system and the Mittag‐Leffler stability of tracking error can be guaranteed. T‐S fuzzy systems are provided to tackle unknown nonlinear functions. The distinctive features of the proposed approach consist in the following: (1) a supervisory control law is designed to compensate the lumped disturbances; (2) both the prediction error and the tracking error are used to estimate the unknown fuzzy system parameters; (3) parameter convergence can be ensured by an interval excitation condition. Finally, the feasibility of the proposed control strategy is demonstrated throughout an illustrative example.     

Online self‐tuning mechanism for direct adaptive control of tall building

The simple adaptive control (SAC) method is known as a remarkable solution to reduce the negative influence of different uncertainties on active control of building structures during an earthquake. The design parameters of this direct adaptive control algorithm are determined after a large number of sensitivity analyses. Furthermore, the selected parameters will not necessarily lead a controller to the optimum performance of the structure. Herein, an innovative online self‐tuning method is firstly introduced to improve the SAC method and cancel out excessive sensitivity analysis. Accordingly, a fuzzy inference system is designed to select the appropriate SAC method, adjusting parameters online instead of using fixed parameters. To show the efficiency of the introduced method, a 20‐story steel building structure equipped with magnetorheological dampers in each story is considered as a benchmark control. The performance of the designed control system is evaluated in different condition of base excitation with and without uncertainty in the model of the proposed structure. The results from the numerical simulations show that the introduced method has better performance than the SAC method with fixed adjusting parameters. The predominance of the method becomes clearer when an input ground motion to the control system has completely different characteristics than the initial designed seismic excitation.     

Novel model reference adaptive control architecture using semi‐initial excitation‐based switched parameter estimator

This paper is a generalization of the recently developed techniques of initial excitation (IE)–based adaptive control with an introduction to the definition of semi‐initial excitation (semi‐IE), a still more relaxed notion than IE. Classical adaptive controllers typically ensure Lyapunov stability of the extended error dynamics (tracking error + parameter estimation error) and asymptotic tracking, while requiring a stringent condition of persistence of excitation (PE) for parameter convergence. Of late, the authors have proposed a new adaptive control architecture, which guarantees parameter convergence under the online‐verifiable IE condition leading to exponential stability of the extended error dynamics. In earlier works, it has been established that the IE condition is significantly milder than the classical PE condition. The current work further slackens the excitation condition by proposing the concept of semi‐IE. The proposed adaptive controller is proved to ensure convergence of the parameter estimation error to a lower‐dimensional manifold under the weaker semi‐IE condition, while the stronger condition of IE guarantees convergence of the parameter estimation error to zero. The designed algorithm is shown to improve transient response of tracking error sufficiently in contrast to conventional adaptive controllers.     

Cumulant‐based approach to FIR system identification

In this paper, a non‐recursive approach is developed for estimating the coefficients of a moving average (MA) model from only third‐order cumulant statistics of a finite realization of the observations of the output data. The signal observations may be noisy. The excitation signal is assumed to be zero mean, non‐Gaussian stationary sequence that is not observed. The noise is additive and may be coloured Gaussian or non‐Gaussian. This novel technique is based on forming a third‐order cumulant composite data matrix. The method presented here requires the solution of a system of linear equations, which can be achieved using least‐squares methods. The proposed approach is illustrated via computer simulations and is shown to be consistent. Copyright © 2003 John Wiley & Sons, Ltd.     

Parameter identification of linear time‐invariant systems using dynamic regressor extension and mixing

Dynamic regressor extension and mixing (DREM) is a new technique for parameter estimation that has proven instrumental in the solution of several open problems in system identification and adaptive control. A key property of the estimator is that, by generation of scalar regression models, it guarantees monotonicity of each element of the parameter error vector that is a much stronger property than monotonicity of the vector norm , as ensured with classical gradient or least‐squares estimators. On the other hand, the overall performance improvement of the estimator is strongly dependent on the suitable choice of certain operators that enter in the design. In this paper, we investigate the impact of these operators on the convergence properties of the estimator in the context of identification of linear single‐input single‐output time‐invariant systems with periodic excitation. The most important contribution is that the DREM (almost surely) converges under the same persistence of excitation (PE) conditions as the gradient estimator while providing improved transient performance. In particular, we give some guidelines how to select the DREM operators to ensure convergence under the same PE conditions as standard identification schemes.     

Current and voltage excitations for the eddy current model

We present a systematic study of how to take into account external excitation in the eddy current model. Emphasis is put on mathematically sound variational formulations and on lumped parameter excitation through prescribed currents and voltages. We distinguish between local excitation at known contacts, known generator current distributions and non‐local variants that rely on topological concepts. The latter case entails the violation of Faraday's law at so‐called cuts and prevents us from reconstructing a meaningful electric field. Copyright © 2004 John Wiley & Sons, Ltd.     

Open‐loop Stackelberg learning solution for hierarchical control problems

This work presents a novel framework based on adaptive learning techniques to solve the continuous‐time open‐loop Stackelberg games. The method yields real‐time approximations of the game value and convergence of the policies to the open‐loop Stackelberg‐equilibrium solution, while also guaranteeing asymptotic stability of the equilibrium point of the closed‐loop system. It is implemented as a separate actor/critic parametric network approximator structure for every player and involves simultaneous continuous‐time adaptation. To introduce and implement the hierarchical structure to the coupled optimization problem, we adjoin to the leader the controller dynamics of the follower. A persistence of excitation condition guarantees convergence of both critics to the actual game values that eventually solve the hierarchical optimization problem. A simulation example shows the efficacy of the proposed approach.     

Simple and accurate approaches to implement the complex trans‐conductance suited for time‐domain simulators for small‐signal and large‐signal table‐based models

This paper focuses on the implementation of table‐based models of high‐frequency transistors for time‐domain simulators at microwave and mm‐wave frequencies. In this frequency range, the channel is not capable of responding to the excitation instantaneously therefore, a delay‐time exists between the channel response and the channel excitation. This delay is represented by a complex trans‐conductance in terms of circuit elements. The high‐frequency models of transistors are required to have the implementation of complex trans‐conductance, where the complex part accounts mathematically for the delay‐time between the channel response and the channel excitation. This paper presents simple and accurate approaches to incorporate the complex trans‐conductance in both small‐signal and large‐signal table‐based models for time‐domain simulators (MOS‐AK International Meeting. Eindhoven, Netherlands, April 2008). Implementation approach for each model, small‐signal and large‐signal, is presented in separated sections. In the first step, the delay is realized by the introduction of an ideal transmission line between the channel excitation and the channel response. As transmission lines are not generally suitable for time‐domain simulations, a lumped element equivalent network is introduced in the second step. The latter approach is fully compatible with time‐domain simulators but frequency limitation, determined by the delay‐time value itself, is introduced. Then the implementation of the complex trans‐conductance in large‐signal model is introduced. In terms of large‐signal behavior, delay‐time is important to achieve a non‐quasi static model. Yet again there is limitation in terms of the frequency range that is determined by the delay value itself. The methodology is illustrated on the small‐signal and the large‐signal equivalent circuit of a Multi‐Fin MOSFET transistor. Simulations are carried out by Cadence Spectre and Agilent ADS simulators, and comparisons are carried out between the simulation results and the measurements. Copyright © 2010 John Wiley & Sons, Ltd.     

Analysis and assessment of VSC excitation system for power system stability enhancement

The voltage source converter (VSC) excitation system is a novel excitation system based on pulse-width modulation (PWM) voltage source converter, which is proposed as improved alternatives to the conventional thyristor excitation systems. This paper aims to provide theoretical confirmation of power system stability enhancement by the VSC excitation system. The reactive current injected to generator terminals by the VSC excitation system can be controlled flexibly. Its capability of enhancing power system stability is investigated in this paper. The simplified model of VSC excitation system suitable for use in system stability studies is developed. An extended Philips–Heffron model of a single-machine infinite bus (SMIB) system with VSC excitation system is established and applied to analyze the damping torque contribution of the injected reactive current to the power system. This paper also gives a brief explanation on why the VSC excitation system can enhance the transient stability in light of equal area criterion. The results of calculations and simulations show that the injected reactive current of VSC excitation system contributes to system damping significantly and has a great effect on the transient stability. When compared with conventional thyristor excitation systems, the VSC excitation system can not only improve the small-signal performance of the power system, but also can improve the system transient stability limit.     

同步发电机光控无刷励磁系统的研究

基于普通无刷励磁系统存在的问题,提出了一种新型同步发电机无刷励磁控制系统一光控无刷励磁控制系统,它是在普通无刷励磁控制系统中用可控器件取代不可控的二极管整流,通过光电耦合形式实现对励磁电流的直接控制,并且利用Matlab／Simulink仿真软件,分别对普通无刷励磁系统和光控励磁系统进行了建模、分析和仿真,并对仿真结果进行了比较。结果表明：光控励磁系统对于提高同步发电机的响应速度,改善电力系统的暂态和稳态性能有明显效果。     

Numerical investigation of the main factor promoting chaotic power swing in a single‐machine,infinite‐bus power system model with the AVR

This paper presents numerical results on bifurcations and chaotic behavior in a fundamental power system model, a single‐machine infinite‐bus system model with generator excitation control by the first‐order lag AVR. The numerical analysis mainly focuses on revealing the parameter value region where the chaotic behavior is observed. It is shown that the partially linearized model, which is derived by linearizing all of the nonlinear elements except the AVR limiter, exhibits similar bifurcations and chaos. Several simulation results indicate that the mechanisms producing the chaotic behaviors and the bifurcations are the same both in the linearized model and in the original single‐machine infinite‐bus system model for parameter value variation which does not move the equilibrium point from the reference point used for the linearization. © 2002 Wiley Periodicals, Inc. Electr Eng Jpn, 142(2): 21–28, 2003; Published online in Wiley InterScience ( www.interscience.wiley.com ). DOI 10.1002/eej.10090     

大容量火电机组励磁系统的技术特点及发展趋势

本文介绍了大容量火电机组励磁系统的基本分类,对其中的静态励磁系统和无刷励磁系统的发展历史进行了全面分析,总结了国内外主要励磁厂商的主要产品的特点,并对励磁系统的发展趋势进行了展望。本文可供大容量火电机组励磁系统选型时参考。     

New solutions to the 2D adaptive visual servoing problem with relaxed excitation requirements

In this paper, we present three new globally convergent vision‐based position controllers for a planar manipulator in a fixed‐camera configuration, where the camera orientation and scale factor are considered unknown. This is a basic adaptive visual servoing problem whose solution was hampered by the nonlinear dependence of the system dynamics on the unknown parameters. Proposing a suitable reparameterization of the systems mathematical model, and exploiting some structural properties of it, we propose three different solutions to the problem. The first one is the certainty equivalent version of the known parameter controller and requires some excitation conditions to ensure global asymptotic convergence. A second version of the controller, which is now slightly more complicated and, possibly, needs to inject some high gain but requires significantly weaker excitation conditions, is given. Finally, we propose a slight modification to the second scheme to achieve the trajectory tracking in finite time. The efficacy of the three adaptive controllers is shown through realistic simulations.