Comparative analysis of passive algorithms in adaptive control

Representative passive adaptive algorithms have been developed with a wide variety of applications. However, to the best of our knowledge, the attempt to unify or to compare them has not been clearly established in literature. In this article, we provide a passive adaptive framework which encompasses all those algorithms including the recently developed proportional‐integral (PI) adaptive scheme. A comparative analysis among performances of the passive algorithms is carried out by means of simulations considering the problem of passivity‐based adaptive tracking control of a simple pendulum. In addition, passivity property for PI algorithm is rigorously shown in case of linear parametrization. Copyright © 2013 John Wiley & Sons, Ltd.     

Passification‐based adaptive control of linear systems: Robustness issues

Passivity is a widely used concept in control theory having led to many significant results. This paper concentrates on one characteristic of passivity, namely passification‐based adaptive control. This concept applies to multi‐input multi‐output systems for which exists a combination of outputs that renders the open‐loop system hyper‐minimum phase. Under such assumptions, the system may be passified by both high‐gain static output feedback and by a particular adaptive control algorithm. This last control law is modified here to guarantee its coefficients to be bounded. The contribution of this paper is to investigate its robustness with respect to parametric uncertainty. Time response characteristics are illustrated on examples including realistic situations with noisy output and saturated input. Theoretical results are formulated as linear matrix inequalities and can hence be readily solved with semi‐definite programming solvers. Copyright © 2007 John Wiley & Sons, Ltd.     

Adaptive filtering‐based multi‐innovation gradient algorithm for input nonlinear systems with autoregressive noise

In this paper, by means of the adaptive filtering technique and the multi‐innovation identification theory, an adaptive filtering‐based multi‐innovation stochastic gradient identification algorithm is derived for Hammerstein nonlinear systems with colored noise. The new adaptive filtering configuration consists of a noise whitening filter and a parameter estimator. The simulation results show that the proposed algorithm has higher parameter estimation accuracies and faster convergence rates than the multi‐innovation stochastic gradient algorithm for the same innovation length. As the innovation length increases, the filtering‐based multi‐innovation stochastic gradient algorithm gives smaller parameter estimation errors than the recursive least squares algorithm.     

Simulation error minimization identification based on multi‐stage prediction

Classical prediction error minimization (PEM) methods are widely used for model identification, but they are also known to provide satisfactory results only in specific identification conditions, e.g. disturbance model matching. If these conditions are not met, the obtained model may have quite different dynamical behavior compared with the original system, resulting in poor long range prediction or simulation performance, which is a critical factor for model analysis, simulation, model‐based control design. In the mentioned non‐ideal conditions a robust and reliable alternative is based on the minimization of the simulation error. Unfortunately, direct optimization of a simulation error minimization (SEM) criterion is an intrinsically complex and computationally intensive task. In this paper a low‐complexity approximate SEM approach is discussed, based on the iteration of multi‐step PEM methods. The soundness of the proposed approach is demonstrated by showing that, for sufficiently high prediction horizons, the k‐steps ahead (single‐ or multi‐step) PEM criteria converge to the SEM one. Identifiability issues and convergence properties of the algorithm are also discussed. Some examples are provided to illustrate the mentioned properties of the algorithm. Copyright © 2010 John Wiley & Sons, Ltd.     

Multi‐component instantaneous frequency estimation using locally adaptive directional time frequency distributions

This paper presents a locally adaptive time‐frequency (t,f) method for estimating the instantaneous frequency (IF) of multi‐component signals. A high‐resolution adaptive directional time‐frequency distribution (ADTFD) is defined by locally adapting the direction of its smoothing kernel at each (t,f) point based on the direction of the energy distribution in the (t,f) domain. The IF of signal components is then estimated from the ADTFD using an image processing algorithm. Using the mean square error between the original IF and estimated IF as a performance criterion, experimental results indicate that the ADTFD gives better IF estimation performance compared with other TFDs for a multi‐component signal. For example, for signal‐to‐noise ratio of 12dB, the IF estimate obtained using the ADTFD achieves a mean square error of ?42dB for a weak signal component, which is an improvement of ?12dB compared with other TFDs. Copyright © 2015 John Wiley & Sons, Ltd.     

Parallelization of the Scale‐Changing Technique in Grid Computing environment for the electronmagnetic simulation of multi‐scale structures

A parallel computing approach to run fast and full‐wave electromagnetic simulation of complex structures in Grid Computing environment is presented. In this study, we show how Grid Computing improves speed and/or reliability over that provided by a single computer, while typically being much more cost‐effective than single computers of comparable speed or reliability. An efficient monolithic (unique) formulation for the electromagnetic modelling of complex (multi‐scale) structures, i.e. structures that exhibit multiple metallic patterns whose sizes cover a large range of scales, is used here. This approach, named the Scale‐Changing Technique, is based on the cascade of multi‐modal Scale‐Changing Networks, each network modelling the electromagnetic coupling between two successive scale levels. These networks can be first computed separately, in an adaptive use of Grid Computing architecture nature, and then cascaded for the global electromagnetic simulation. Based on this technique, a fast computer algorithm was developed and tested in the Grid‐Computing environment. For illustration purposes, the electromagnetic analysis of multi‐scale structures, applied to phase‐shifter elements and an example of infinite passive reflectarray, was carried out. The obtained results have confirmed the effectiveness of such an approach compared with sequential computing. This approach shows very good computation performance while keeping the same accuracy. Besides, this method is very promising for optimizing circuit with multiple design parameters to handle and for the global electromagnetic simulation of multi‐scale and/or oer‐sized structures. Copyright © 2010 John Wiley & Sons, Ltd.     

On driving non‐passive macromodels to instability

This paper illustrates a procedure for demonstrating and quantifying the importance of passivity in linear macromodels. This issue is critical whenever the macromodels are derived from tabulated port responses, either in time or frequency domain. We show an algorithmic procedure for the design of a passive termination network that will drive a given non‐passive macromodel to instability. Several termination structures characterized by various port couplings are investigated. Relaxed passivity conditions are also given, which guarantee the stability of the macromodel under specific reduced‐coupling loading conditions. Theoretical results are applied to a set of application test cases. Copyright © 2008 John Wiley & Sons, Ltd.     

Passive least-squares-type estimation algorithm for direct adaptive control

The standard least squares (LS) estimation algorithm is modified in such a way that it becomes passive. Therefore the scope of application of the LS algorithm is extended to those adaptive schemes whose convergence proof is based on passivity. The passive version of LS is presented in both continuous and discrete time.     

Positive‐real property of passive fractional circuits in W‐domain

Fractional circuits have attracted extensive attention of scholars and researchers for their superior performance and potential applications. Fractional circuits constitute a new challenge for the analysis and synthesis methods of traditional circuits theory. Passivity is the fundamental property of traditional circuits (integer order electric circuits). As is known to all, passivity is equivalent to positive realness in traditional linear circuits. However, this equivalence is broken down by introducing fractional elements into electrical networks in s‐domain. To address this issue, on the basis of s‐W transformation, we study the passive criteria of fractional circuits with rational order elements in this paper. Definitions of positive‐real (matrix) function in W‐domain are given, and the equivalence conditions of positive realness are derived. In addition, a conclusion is proposed in which the immittance (matrix) function of passive fractional circuits with rational order elements is positive real in W‐domain. The applications of passive criteria in circuit synthesis are shown.     

Control of induction motors: an adaptive passivity MIMO perspective

The design of two multiple‐input multiple‐output (MIMO) controllers for induction motors, based on adaptive passivity, is presented in this paper. The controller design method is based on concepts of equivalence passivity via adaptive feedback, previously developed by the authors. Robustness under variations of the motor‐load parameters is guaranteed and the knowledge of such a parameters is not needed in the design. Simple proportional controllers for the torque, rotor flux and stator current control loops are used, due to the control simplification introduced by the use of feedback passive equivalence. A principle called ‘Torque‐Flux Control Principle’ is used in this article introducing a considerable simplification in the resultant controller. Because of the employment of this principle, the control efforts are diminished and rotor flux estimation (or measurement) is avoided. Copyright © 2003 John Wiley & Sons, Ltd.     

Robust hybrid estimation and rejection of multi‐frequency signals

We consider the problem of output regulation for LTI systems in the presence of unknown exosystems. The knowledge about the multi‐frequency signals exosystem consists in the maximum number of frequencies and their maximal value. The control scheme relies on two main components: an estimation algorithm, to reconstruct the signal generated by the exosystem, and a controller, to enforce the output regulation property to the closed‐loop system. To tackle the first task, we propose a hybrid observer for the estimation of the (possibly piece‐wise continuous) number and values of the frequencies contained in the exogenous signal. The hybrid observer is particularly appealing for numerical implementations, and it is combined with a self‐tuning algorithm of the free parameters (gains), thus improving its performance even in case of noisy measurements. Semi‐global exponential convergence of the estimation error is provided. As far as the second task is concerned, a robust hybrid regulator is designed for practical rejection of the multi‐frequency disturbance signal acting on the plant. The result is achieved by exploiting the frequencies estimated by the hybrid observer. The effectiveness of the proposed control scheme is shown by means of numerical simulations. Copyright © 2016 John Wiley & Sons, Ltd.     

电压互感器的高频无源电路模型

提出了一种获得微观无源的PT高频模型方法,该方法首先利用矢量拟合获得Foster形式的网络函数稳定的表达式,然后利用起作用集方法求解带约束条件的二次规划获得满足无源的Foster形式的网络函数,最后综合获得微观无源的电路模型。根据无源修正前后网络函数的对比验证了本文所提方法的有效性。     

Passivity‐based control for stabilization,regulation and tracking purposes of a class of nonlinear systems

In this paper, a new passivity‐based control (PBC) scheme based on state feedback is proposed in order to solve tracking, regulation and stabilization problems for a class of multi‐input multi‐output (MIMO) nonlinear systems expressed in the normal form, with time‐invariant parameters and locally bounded reference weakly minimum phase. For the proposed control scheme two new different state feedbacks, one non‐adaptive for the case when the system parameters are assumed to be known and the other adaptive for the case of unknown parameters, are developed. For the adaptive case it is assumed that the unknown parameters appear linearly in the equations. Analysis of the transient behaviour of the proposed control schemes is presented through the simulation of two examples. Copyright © 2006 John Wiley & Sons, Ltd.     

Mixed norm regularized recursive total least squares for group sparse system identification

A mixed l_p,0‐regularized recursive total least squares (RTLS) algorithm is considered for group sparse system identification. Regularized recursive least squares (RLS) has been successfully applied to group sparse system identification; however, the estimation performance in regularized RLS‐based algorithms deteriorates when both input and output are contaminated by noise (the error‐in‐variables problem). We propose an l_p,0‐RTLS algorithm to handle group sparse system identification with errors‐in‐variables. The proposed algorithm is an RLS‐like solution that utilizes l_p,0‐regularization. The proposed algorithm provides excellent performance as well as reduces the required complexity by effective inversion matrix handling. Simulations demonstrate the superiority of the proposed l_p,0‐regularized RTLS for a group sparse system identification setting. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

An IMM algorithm with federated information mode‐matched filters for AGV

In this paper, a tracking algorithm for autonomous navigation of automated guided vehicles (AGVs) is presented. The developed navigation algorithm is an interacting multiple‐model (IMM) algorithm used to detect other AGVs using fused information from multiple sensors. In order to detect other AGVs, two kinematic models were derived: A constant‐velocity model for linear motion, and a constant‐speed turn model for curvilinear motion. In the constant‐speed turn model, a nonlinear information filter (IF) is used in place of the extended Kalman filter (KF). Being equivalent to the KF algebraically, the IF is extended to N‐sensor distributed dynamic systems. The model‐matched filter used in multi‐sensor environments takes the form of a federated nonlinear IF. In multi‐sensor environments, the information‐based filter is easier to decentralize, initialize, and fuse than a KF‐based filter. In this paper, the structural features and information‐sharing principle of the federated IF are discussed. The performance of the suggested algorithm using a Monte Carlo simulation is evaluated under the three navigation patterns. Copyright © 2006 John Wiley & Sons, Ltd.     

无源修正技术在互感器宽频等效模型建模中的应用

首先采用一台HP4395A型网络矢量分析仪对电压互感器进行了S参数的测量,计算了互感器的Y参数。通过矢量匹配拟合得到互感器Y参数的频域有理函数表达式,为了保证所建模型的无源性,对拟合参数进行了无源修正,并通过网络综合建立了互感器稳定的π型等效电路。最后采用Matlab/Simulink软件进行了仿真,仿真结果表明采用无源修正技术可以保证互感器宽频等效模型的稳定性和精确性。     

A novel magnet polarity identification method for initial position estimation for sensorless IPMSM drive

This paper proposes a novel magnet polarity identification method for initial position estimation during startup for interior permanent magnet synchronous machine (IPMSM) drives. The rotor's initial position estimation is based on magnetic saliency and employs high‐frequency (HF) components of the voltage and current that are excited by the multi space‐vector pulse‐width modulation (MSVPWM) pattern. However, there is a common trouble in the estimation methods based on the magnetic saliency: it is necessary to identify the magnet polarity in order to distinguish the north and south poles since the estimated position angle is a periodic function with π radians. In this paper, a novel inductance estimation method is presented and the magnet polarity is uniquely identified by the relationship between the estimated inductance and the magnetic saturation effect. Experimental results confirm the advantages of the proposed method: it is reliable, accurate, and convenient, and can be done in real time. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

MIMO multi‐periodic repetitive control system: universal adaptive control schemes

This paper presents a simple adaptive multi‐periodic repetitive control scheme when the MIMO LTI plant is not necessarily positive real (PR), however it is strictly minimum‐phase, the spectrum of high‐frequency gain matrix CB is symmetric and lies in the open right/left half complex plane(sign/spectrum definite). The non‐identifier‐based direct adaptive control technique, which does not need plant parameter information, is used to construct adaptive schemes and the system stability is analysed by Lyapunov second method. The extension to plant under certain non‐linear perturbations and an exponential stability scheme are also discussed. Finally, an adaptive proportional plus multi‐periodic repetitive control scheme is proposed. The theoretical findings are supported with simulations. Copyright © 2006 John Wiley & Sons, Ltd.     

Adaptive filters cascade applied to a frequency identification improvement problem

Problem of frequency identification performance improvement for a single‐tone sinusoidal signal is solved via construction of an adaptive filters cascade. The cascade consists of adaptive band‐pass filters tuned by estimates of the frequency provided by a given identification algorithm. Stability of the cascade is studied and boundedness of trajectories is proven with Lyapunov analysis under certain assumption on identification algorithm. Numerical simulations are given illustrating improved identification performance for different identification algorithms. Copyright © 2015 John Wiley & Sons, Ltd.