Nonlinear influence in the frequency domain: Alternating series

The nonlinear influence on system output spectrum is studied for a class of nonlinear systems which have Volterra series expansion. It is shown that under certain conditions the system output spectrum can be expressed in an alternating series with respect to some model parameters which define system nonlinearities. The magnitude of the system output spectrum can therefore be suppressed by exploiting the properties of alternating series. Sufficient (and necessary) conditions in which the output spectrum can be cast into an alternating series are studied. These results reveal a novel frequency-domain insight into the nonlinear influence on a system, and provide a new method for the analysis and design of nonlinear systems in the frequency domain. Examples are given to illustrate the results.     

Input-output stability of interconnected systems

New results for input-output stability of multiple input-multiple output systems, viewed as interconnected systems, are established. In the present approach, which can also be utilized in stabilization and compensation procedures, large-scale systems are analyzed in terms of their subsystems and interconnecting structure. The method advanced is applied to a specific example. The present results differ appreciably from earlier ones by Porter and Michel because they are applicable to a larger class of problems, they are simpler to apply when conicity conditions are used, and in addition to circle criteria, they also utilize Popov-type conditions. The present procedure differs significantly from existing methods concerned with the analysis of systems having several nonlinearities. Many of these earlier results (multidimensional Popov criteria) usually involve frequency dependent test matrices and graphical frequency domain interpretations are generally not possible. The present results require frequency independent test matrices and yield graphical frequency domain interpretations.     

The vibration transmissibility of a single degree of freedom oscillator with nonlinear fractional order damping

Motivated by the theoretical analysis of the effects of nonlinear viscous damping on vibration isolation using the output frequency response function approach, the output frequency response function approach is employed to investigate the effects of the nonlinear fractional order damping on vibration isolation based on Volterra series in the frequency domain. First, the recursive algorithm which is proposed by Billings et al. is extended to deal with the system with fractional order terms. Then, the analytical relationships are established among the force transmissibility, nonlinear characteristic coefficients and fractional order parameters for the single degree of freedom oscillator. Consequently, the effects of the nonlinear system parameters on the force transmissibility are discussed in detail. The theoretical analysis reveals that the force transmissibility of the oscillator is suppressed due to the existence of the fractional order damping, but presents different effects on suppressing the force transmissibility of the oscillator over the frequency region by varying the fractional order parameters. Moreover, the fractional order parameters, which affect the force transmissibility, the bandwidth of the frequency region and the resonance frequency, can be used as designing parameters for vibration isolation systems. At last, numerical studies are presented to illustrate the theoretical results.     

VIBRATION CONTROL OF A CLASS OF GENERALIZED GRADIENT SYSTEMS

The suppression of oscillations in a class of generalized gradient systems using nonlinear dynamic output feedback is investigated. A class of controllers is considered which, in addition to a linear dynamic component, possess several types of nondynamic nonlinearities. Frequency domain conditions on the transfer matrix of the controller's linear component are presented that ensure the convergence of all closed-loop solutions to an equilibrium point in state space, thus eliminating the occurrence of sustained oscillations. Practically important technical applications include a.o. the set point control of mechanical systems described by the Euler–Lagrange equations and their equivalent Hamiltonian formulation. The obtained results constitute a systems theoretical basis for a new method of nonlinear vibration controller design.     

A dynamic operability analysis approach for nonlinear processes

Current process operability indicators are mostly restricted to linear approximations of the process dynamics. Other operability analysis approaches that have the capability to include full nonlinear process models rely on mixed integer dynamic optimisation techniques which, in general, require large amount of computations. In this paper we propose a dynamic operability analysis approach for stable nonlinear processes that can be readily applied during process design and can be solved efficiently using a limited amount of computations. The process nonlinear dynamics are approximated by a series interconnection of static nonlinearities and linear dynamics, represented by the so-called Hammerstein–Wiener models. These type of models can often be obtained during process design where detailed steady-state nonlinear models are available, combined with some (usually limited) information on the process dynamics. Using an extended internal model control (IMC) framework, we investigate the interaction between the static nonlinearities and linear dynamics on the operability of the process. The framework extends the well-known equivalence between operability and invertibility of linear processes to nonlinear systems. In particular, by exploiting some results from the theory of passive systems we provide conditions that guarantee the existence of the inverse of the static nonlinearities. We show that the inverse can be attained inside a specific input/output region. This region imposes a constraint on the maximum magnitude of the signals that appear in the closed-loop and represents the effect of the static nonlinearities on the operability of the overall process. Dynamic operability is then quantified using a linear matrix inequality (LMI) optimisation approach that minimises a given performance criterion subject to the constraint imposed by the static nonlinearities.     

Asymptotic rejection of unmatched general periodic disturbances with nonlinear Lipschitz internal models

This article deals with asymptotic rejection of general periodic disturbances in a class of nonlinear systems by exploiting observer design with Lipschitz output nonlinearities for the internal model design. It is shown that a class of general periodic distances can be modelled as outputs of linear systems with nonlinear output functions. Based on this observation, a nonlinear observer design with output Lipschitz nonlinearities is investigated and integrated for the internal model design to estimate the phase and amplitude of the desired feedforward input for asymptotic disturbance rejection in a class of nonlinear systems with input-to-state stable zero dynamics. A number of problems on disturbance rejection can be formulated in the disturbance rejection form shown in this article to which the proposed nonlinear Lipschitz internal model can be applied. Two examples are included to demonstrate the proposed design strategies.     

Output Feedback Stabilization of a Class of Uncertain Nonaffine Nonlinear Systems

In this paper, output feedback control is presented for a general class of uncertain nonaffine nonlinear systems, that does not rely on state estimation. Under the condition that only the system output is available for feedback, a dynamic linear filter is built to estimate unknown nonlinearities, and an output feedback controller is developed to stabilize the systems by utilizing the estimation to compensate for the unknown nonlinearities. One important feature of the proposed control is that the controller is developed under mild conditions with simple control algorithms, which is of great significance in engineering practice. Simulation results show the effectiveness of the control approach.     

A numerical technique to predict periodic and quasi-periodic response of nonlinear dynamic systems

A frequency domain based algorithm using Fourier approximation and Galerkin error minimization has been used to obtain the periodic orbits of large order nonlinear dynamic systems. The stability of these periodic response is determined through a bifurcation analysis using Floquet theory. This technique is applicable to dynamic systems having both analytic and nonanalytic nonlinearities. This technique is compared with numerical time integration and is found to be much faster in predicting the steady state periodic response.     

Analysis of periodically forced bioreactors using nonlinear transfer functions

Nonlinearity is an underlying property of process systems that allows for time-average performance enhancement with periodic forcing of external parameters. One can use the well-known π-criterion to obtain a sufficient condition for optimal periodic operation, but it is valid only for weakly nonlinear systems with infinitesimal forcing amplitudes. Among such process systems, bioreactors often exhibit highly nonlinear dynamics, thus posing difficulties for a systematic analysis of their periodic operation. It becomes desirable to understand how inherent nonlinearities would contribute to performance improvement if periodic forcing is applied to such processes. This paper explores how nonlinear characteristics affect periodic process operation in the context of bioreactor systems. By taking advantage of iterated integrals and shuffle algebra, an analytical solution of a nonlinear bioprocess is approximated with the functional expansion method. The resulting Laplace-Borel transform of the nonlinear system facilitates the expression of the solution in the frequency domain based on the nonlinear transfer function. The method enables the separation of the transient dynamics and the stationary periodic behavior, facilitating the analysis of periodic operations and leading to a generalizable platform. Specifically, the optimal periodic operation problem is solved by finding the proper forcing amplitude and frequency to maximize the offset. Compared with the π-criterion, our method is proven to be globally valid for any forcing frequency and amplitude, so long as the process is globally stable.     

Output feedback stabilization of time‐delay nonlinear systems with unknown continuous time‐varying output function and nonlinear growth rate

This article addresses the problem of global output feedback stabilization for a class of time‐varying delay nonlinear systems with polynomial growth rate. The systems under investigation possess two remarkable features: the output is perturbed by an unknown sensitivity function that is not differentiable but continuous, and the nonlinearities are bounded by a polynomial function of the output multiplied by unmeasurable state variables. The new full‐order observer is established by introducing a dynamic gain and filtering unknown nonlinearities and time‐varying delay. With the help of the transformation skill and the reasonable combination of several systems, this article proposes a linear output feedback controller with the dynamic gain and completes the performance analysis based on the construction of two integral Lyapunov functions. Finally, a simulation example is presented to demonstrate the effectiveness of control strategy.     

Linear output feedback with dynamic high gain for nonlinear systems

We propose a linear output feedback with dynamic high gain for global regulation of a class of nonlinear systems. The uncertain nonlinearities are assumed to be bounded by a polynomial function of the output multiplied by unmeasured states. The crucial point made in this paper is that a linear observer-based output feedback can globally regulate an equilibrium of strongly nonlinear systems, provided that a single high gain is appropriately tuned.     

Magnitude bounds of generalized frequency response functions for nonlinear Volterra systems described by NARX model

In order to reveal the relationship between system time domain model parameters and system frequency response functions, new magnitude bounds of frequency response functions for nonlinear Volterra systems described by NARX model are established. The magnitude bound of the nth-order generalized frequency response function (GFRF) can be expressed as a simple n-degree polynomial function of the magnitude of the first order GFRF, whose coefficients are functions of the model parameters and frequency variables. Thus the system output spectrum can also be bounded by a polynomial function of the magnitude of the first order GFRF. These results demonstrate explicitly the analytical relationship between model parameters and system frequency response functions, and provide a significant insight into the magnitude based analysis and synthesis of nonlinear systems in the frequency domain.     

Global nonlinear output regulation: Convergence-based controller design

In this paper we present output-feedback controllers solving the global output regulation problem for a class of nonlinear systems. The proposed controllers are based on the notion of convergent systems. The presented solution extends well-established results on the linear output regulation problem and the local nonlinear output regulation problem to the global case. For Lur’e systems, which are not necessarily in the output-feedback form, the proposed controllers can be found by solving the regulator equations and certain linear matrix inequalities. For systems in the output-feedback form with uncertain parameters and uncertain nonlinearities we provide a robust regulator that does not rely on the minimum phaseness assumption on the system, which is crucial in the previous regulator designs for output-feedback systems. The results are illustrated by examples.     

The parametric characteristic of frequency response functions for nonlinear systems

The characteristic of the frequency response functions of nonlinear systems can be revealed and analyzed by analyzing of the parametric characteristics of these functions. To achieve these objectives, a new operator is defined, and several fundamental and important results about the parametric characteristics of the frequency response functions of nonlinear systems are developed. These theoretical results provide a significant and novel insight into the frequency domain characteristics of nonlinear systems and circumvent a large amount of complicated integral and symbolic calculations which have previously been required to perform nonlinear system frequency domain analysis. Several new results for the analysis and synthesis of nonlinear systems are also developed. Examples are included to illustrate potential applications of the new results.     

Non‐Parametric Identification Method of Volterra Kernels for Nonlinear Systems Excited by Multitone Signal

To solve the problem of Volterra frequency‐domain kernels (VFKs) of nonlinear systems, which can be difficult to identify, we propose a novel non‐parametric identification method based on multitone excitation. First, we have studied the output properties of VFKs of nonlinear systems excited by the multitone signal, and derived a formula for identifying VFKs. Second, to improve the efficiency of the non‐parametric identification method, we suggest an increase in the number of tones for multitone excitation to simultaneously identify multi‐point VFKs with one excitation. We also propose an algorithm for searching the frequency base of multitone excitation. Finally, we use the interpolation method to separate every order output of VFK and extract its output frequency components, then use the derived formula to calculate the VFKs. The theoretical analysis and simulation results indicate that the non‐parametric method has a high precision and convenience of operation, improving the conventional methods, which have the defects of being unable to precisely identify VFKs and identification results are limited to three‐order VFK.     

基于双增益方法的不确定非线性系统的输出反馈调节问题

研究一类具有多种不确定性的非线性系统的全局输出反馈调节问题.所研究系统的一个显著特点是非线性项被未知增长率和多项式形式的输出函数的乘积界定,难点是在输出受不确定参数摄动的情况下如何抑制非线性项.提出一种改进的双增益方法来设计输出反馈控制器,可以确保闭环系统所有信号全局一致有界并且原系统状态收敛到零.最后,采用质量弹簧机械系统的输出反馈镇定问题来说明控制策略的有效性.     

Global output feedback stabilisation of nonlinear systems with a unifying linear controller structure

We investigate the problem of global stabilisation by linear output feedback for a class of uncertain nonlinear systems with zero-dynamics. Compared with the previous works, new dilation-based assumptions are introduced that allow the system nonlinearities and its bounding functions to be coupled with all the states. The nonlinear systems of this paper can be considered as an extended form of some low triangular and feedforward systems. Dynamic gain scaling technique is applied to the controller design and stability analysis. It is proved that with a unifying linear controller structure and flexible adaptive laws for the observer gain, global stabilisation of the nonlinear systems can be achieved.     

Global robust output regulation for output feedback systems

The global robust output regulation problem for the class of nonlinear systems in output feedback form has been studied under the assumption that the solution of the regulator equations is polynomial. This assumption essentially requires these systems contain only polynomial nonlinearity and is due to the failure of finding a nonlinear internal model to account for more complex nonlinearities than polynomials. Recently, it was found that a nonlinear internal model can be constructed under some assumption much milder than the polynomial assumption. In this note, we will apply this type of internal model to solve the global robust output regulation problem for the class of nonlinear systems in output feedback form.     

Output frequency response function of nonlinear Volterra systems

An expression for the output frequency response function (OFRF), which defines the explicit analytical relationship between the output spectrum and the system parameters, is derived for nonlinear systems which can be described by a polynomial form differential equation model. An effective algorithm is developed to determine the OFRF directly from system simulation or experimental data. Simulation studies demonstrate the significance of the OFRF concept, and verify the effectiveness of the algorithm which evaluates the OFRF numerically. These new results provide an important basis for the analytical study and design of a wide class of nonlinear systems in the frequency domain.     

Identification and frequency domain analysis of non-stationary and nonlinear systems using time-varying NARMAX models

This paper introduces a new approach for nonlinear and non-stationary (time-varying) system identification based on time-varying nonlinear autoregressive moving average with exogenous variable (TV-NARMAX) models. The challenging model structure selection and parameter tracking problems are solved by combining a multiwavelet basis function expansion of the time-varying parameters with an orthogonal least squares algorithm. Numerical examples demonstrate that the proposed approach can track rapid time-varying effects in nonlinear systems more accurately than the standard recursive algorithms. Based on the identified time domain model, a new frequency domain analysis approach is introduced based on a time-varying generalised frequency response function (TV-GFRF) concept, which enables the analysis of nonlinear, non-stationary systems in the frequency domain. Features in the TV-GFRFs which depend on the TV-NARMAX model structure and time-varying parameters are investigated. It is shown that the high-dimensional frequency features can be visualised in a low-dimensional time–frequency space.