一类非线性系统故障诊断观测器设计

大多故障诊断算法集中在线性系统方面, 在非线性方面只考虑故障对状态起线性影响的那些系统. 本文根据系统的非线性本质特性, 提出了基于模型的一类非线性系统故障诊断观测器设计方法. 应用系统的(B;K; á)实现精确分解后的系统模型, 对它们的状态故障起非线性的影响. 采用干扰解耦技术,获得的残差对未知扰动有很好的鲁棒性. 在Lyapunov意义下, 验证了算法的稳定性. 仿真验证表明, 所提算法具有快速收敛性, 对一类非线性系统诊断效果较好.     

On-line implementation of a nonlinear distributed observer for a multizone furnace — comparative study with a nonlinear filter

The dynamic behavior of an experimental multizone electrical furnace is described by nonlinear partial differential equations. On this basis, a nonlinear distributed observer of the load temperature profiles is designed. The resulting observer equations are discretized by orthogonal collocation on finite elements and implemented on-line on a PC. The observer shows very good properties: easy tuning, robustness and small computer resources. Some experimental results and computer simulations are presented and discussed. Moreover, a comparison is performed between the observer and a distributed extended Kalman filter, including on-line performances and computational implementation aspects. It is shown that the observer requires less computational effort for similar performances.     

Eigenspectrum-based extended Luenberger observers for a class of distributed parameter systems

State estimation is an important problem in distributed parameter system especially with nonlinear dynamics in industrial process. An extended Luenberger observer based on the eigen-spectrum of the system operator is developed in this paper to handle this problem. The distributed parameter system is projected into a finite-dimensional subspace where a low-order ordinary differential equation describing the dominant dynamics of the system is derived. A Luenberger observer extended with a nonlinear part is developed based on that dominant dynamics. A sufficient condition is given in this paper for the convergence of the estimated error. Finally, by applying the developed design method to the temperature estimation of a catalytic rod, the achieved simulation results show the effectiveness of the proposed observer.     

Data-driven model reduction-based nonlinear MPC for large-scale distributed parameter systems

Model predictive control (MPC) has been effectively applied in process industries since the 1990s. Models in the form of closed equation sets are normally needed for MPC, but it is often difficult to obtain such formulations for large nonlinear systems. To extend nonlinear MPC (NMPC) application to nonlinear distributed parameter systems (DPS) with unknown dynamics, a data-driven model reduction-based approach is followed. The proper orthogonal decomposition (POD) method is first applied off-line to compute a set of basis functions. Then a series of artificial neural networks (ANNs) are trained to effectively compute POD time coefficients. NMPC, using sequential quadratic programming is then applied. The novelty of our methodology lies in the application of POD's highly efficient linear decomposition for the consequent conversion of any distributed multi-dimensional space-state model to a reduced 1-dimensional model, dependent only on time, which can be handled effectively as a black-box through ANNs. Hence we construct a paradigm, which allows the application of NMPC to complex nonlinear high-dimensional systems, even input/output systems, handled by black-box solvers, with significant computational efficiency. This paradigm combines elements of gain scheduling, NMPC, model reduction and ANN for effective control of nonlinear DPS. The stabilization/destabilization of a tubular reactor with recycle is used as an illustrative example to demonstrate the efficiency of our methodology. Case studies with inequality constraints are also presented.     

Adaptive fuzzy controller design with observer for a class of uncertain nonlinear MIMO systems

In this paper, an adaptive fuzzy control approach is proposed to stabilize a class of uncertain nonlinear MIMO systems with the unmeasured states and the external disturbances. The fuzzy logic systems are used to approximate the unknown functions. Because it does not required to assume that the system states are measurable, it needs to design an observer to estimate the system unmeasured states. The considered MIMO systems are more general, i.e. they consist of N subsystems and each subsystem is in the non‐affine form. The stability of the closed‐loop system is verified by using Lyapunov analysis method. Two simulation examples are utilized to verify the effectiveness of the proposed approach. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

From irreversible thermodynamics to a robust control theory for distributed process systems

In this paper we combine recent results that link passivity, as it is understood in system's theory, with concepts from irreversible thermodynamics to develop a robust control design methodology for distributed process systems. In this context, we show that passivity and stabilization of systems where non-dissipative phenomena are taking place is possible under very simple, finite dimensional control configurations. These include, boundary and high gain controllers, which combined with robust identification schemes should be able to provide efficient plant operation.     

Design of consensus and adaptive consensus filters for distributed parameter systems

This work establishes an abstract framework that considers the distributed filtering of spatially varying processes using a sensor network. It is assumed that the sensor network consists of groups of sensors, each of which provides a number of state measurements from sensing devices that are not necessarily identical and which only transmit their information to their own sensor group. A modification to the local spatially distributed filters provides the non-adaptive case of spatially distributed consensus filters which penalize the disagreement amongst themselves in a dynamic manner. A subsequent modification to this scheme incorporates the adaptation of the consensus gains in the disagreement terms of all local filters. Both the well-posedness of these two consensus spatially distributed filters and the convergence of the associated observation errors to zero in appropriate norms are presented. Their performance is demonstrated on three different examples of a diffusion partial differential equation with point measurements.     

基于观测器非线性不确定系统的自适应模糊控制

针对一类单输入单输出不确定非线性系统，提出一种稳定的自适应模糊控制方法，该方法不需要系统状态可测的条件，而是通过设计模糊状态观测器来估计系统的状态，证明了所提出的控制方法不但能使闭环系统稳定，而且输出误差可取得H∞跟踪控制性能，仿真结果进一步验证了该控制算法的实用性和有效性。     

Sufficient conditions for controllability of a class of distributed parameter systems

In the paper we present certain results on the question of controllability for (i) linear evolution equations (parabolic and hyperbolic) with distributed controls and (ii) a class of linear parabolic equations with boundary controls.     

A robust adaptive observer for a class of singular nonlinear uncertain systems

This paper proposes a robust adaptive observer for a class of singular nonlinear non-autonomous uncertain systems with unstructured unknown system and derivative matrices, and unknown bounded nonlinearities. Unlike many existing observers, no strong assumption such as Lipschitz condition is imposed on the recommended system. An augmented system is constructed, and the unknown bounds are calculated online using adaptive bounding technique. Considering the continuous nonlinear gain removes the chattering which may appear in practical applications such as analysis of electrical circuits and estimation of interaction force in beating heart robotic-assisted surgery. Moreover, a simple yet precise structure is attained which is easy to implement in many systems with significant uncertainties. The existence conditions of the standard form observer are obtained in terms of linear matrix inequality and the constrained generalised Sylvester's equations, and global stability is ensured. Finally, simulation results are obtained to evaluate the performance of the proposed estimator and demonstrate the effectiveness of the developed scheme.     

基于干扰观测器的一类不确定非线性系统鲁棒H∞控制

为了降低控制器对干扰的要求,基于干扰观测器提出一类多输入多输出不确定非线性系统的鲁棒H∞控制方法．将系统的内部不确定性和外部干扰组成复合干扰,设计基于小波神经网络的复合干扰观测器,并提出干扰观测器的参数调节方案使观测器能以高精度逼近复合干扰．同时在控制器中引入鲁棒控制项用来抑制观测器误差给系统带来的影响,所设计的控制器能使系统的跟踪误差小于一个给定的性能指标．最后给出一个仿真算例验证了本控制方案的有效性．     

Matrix inequality‐based observer design for a class of distributed transport‐reaction systems

The problem of designing a globally exponentially convergent observer for a class of (linear in transport and nonlinear in generation) semi‐linear parabolic distributed systems is addressed within a matrix inequality framework, yielding (i) sufficient convergence conditions with physical meaning and (ii) the weight of a Lyapunov functional as design degree of freedom. The proposed approach is illustrated and tested with a representative case example in chemical reaction engineering. Copyright © 2013 John Wiley & Sons, Ltd.     

Adaptive fuzzy observer backstepping control for a class of uncertain nonlinear systems with unknown time-delay

In this paper, a new adaptive fuzzy backstepping control approach is developed for a class of nonlinear systems with unknown time-delay and unmeasured states. Using fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the state observer and applying the backstepping technique, an adaptive fuzzy observer control approach is developed. The main features of the proposed adaptive fuzzy control approach not only guarantees that all the signals of the closed-loop system are semiglobally uniformly ultimately bounded, but also contain less adaptation parameters to be updated on-line. Finally, simulation results are provided to show the effectiveness of the proposed approach.     

Sliding mode control with disturbance observer for a class of nonlinear systems

This paper is concerned with the stabilization problem for a class of nonlinear systems with disturbance. The disturbance model is unknown and the first derivative of disturbance is bounded. Firstly, a general disturbance observer is proposed to estimate disturbance approximatively. Secondly, since the bound of the disturbance observer error is unknown, an adaptive sliding mode controller is designed to guarantee that the state of system asymptotically converges to zero and the unknown bound can be adjusted by an adaptive law. Finally, an example is given to illustrate the effectiveness of the proposed method.     

一类时滞分布参数切换系统的鲁棒容错控制

研究一类时滞分布参数切换系统的容错控制问题.当执行器失效或部分失效时,建立了系统容错控制的数学模型.通过构造Lyapunov函数,运用Green公式和Poincare不等式,获得了容错控制器存在的充分条件,该条件用一组线性矩阵不等式表示,从而将分布参数切换系统的容错控制问题转化为一组线性矩阵不等式的可行解问题.最后通过数值算例,验证了该方法的有效性.     

Global tracking sliding mode control for a class of nonlinear systems via variable gain observer

A novel output‐feedback sliding mode control strategy is proposed for a class of single‐input single‐output (SISO) uncertain time‐varying nonlinear systems for which a norm state estimator can be implemented. Such a class encompasses minimum‐phase systems with nonlinearities affinely norm bounded by unmeasured states with growth rate depending nonlinearly on the measured system output and on the internal states related with the zero‐dynamics. The sliding surface is generated by using the state of a high gain observer (HGO) whereas a peaking free control amplitude is obtained via a norm observer. In contrast to the existing semi‐global sliding mode control solutions available in the literature for the class of plants considered here, the proposed scheme is free of peaking and achieves global tracking with respect to a small residual set. The key idea is to design a time‐varying HGO gain implementable from measurable signals. Copyright © 2010 John Wiley & Sons, Ltd.     

Adaptive open loop control for a class of distributed parameter systems

The real time implementation of closed loop control laws obtained by the minimization of a quadratic criterion with finite time intervals is a difficult problem, if we consider computing time and the eventual determination of the state variables. It would seem useful therefore to define, for complex systems such as distributed parameter systems, a control type which unites the advantages of open loop control, with its relative simplicity of implementation, and those of closed loop control, with its ability to reduce perturbations. It is for this reason that we use the principle of adaptive open loop control. In this paper, we describe the principles of such a method and results obtained from one example studied by numerical computation or hybrid simulation in real time.     

Adaptive fuzzy tracking control for a class of uncertain MIMO nonlinear systems using disturbance observer

In this paper,the adaptive fuzzy tracking control is proposed for a class of multi-input and multioutput(MIMO)nonlinear systems in the presence of system uncertainties,unknown non-symmetric input saturation and external disturbances.Fuzzy logic systems(FLS)are used to approximate the system uncertainty of MIMO nonlinear systems.Then,the compound disturbance containing the approximation error and the timevarying external disturbance that cannot be directly measured are estimated via a disturbance observer.By appropriately choosing the gain matrix,the disturbance observer can approximate the compound disturbance well and the estimate error converges to a compact set.This control strategy is further extended to develop adaptive fuzzy tracking control for MIMO nonlinear systems by coping with practical issues in engineering applications,in particular unknown non-symmetric input saturation and control singularity.Within this setting,the disturbance observer technique is combined with the FLS approximation technique to compensate for the efects of unknown input saturation and control singularity.Lyapunov approach based analysis shows that semi-global uniform boundedness of the closed-loop signals is guaranteed under the proposed tracking control techniques.Numerical simulation results are presented to illustrate the efectiveness of the proposed tracking control schemes.     

一类具有变时滞不确定分布参数系统的滑动模控制

研究一类不确定变时滞分布参数系统的滑动模控制问题．首先设计一种无记忆功能的变结构控制器;然后分析了在滑动模切换面上滑动模控制系统关于不确定量的不变性特征;最后给出了从任意初始位置出发的轨线到达滑动模态区的时间估计．研究表明,所设计的控制器结构简单．容易实现．     

High gain observer for a class of nonlinear systems with coupled structure and sampled output measurements: application to a quadrotor

This paper proposes a new high gain observer for a class of non-uniformly observable nonlinear systems with coupled structure driven by sampled outputs. The considered class of systems is particularly constituted by several subsystems where each subsystem is associated to a subset of the output variables. The observer design is carried out through two steps. First, a high-gain observer is proposed in the continuous-time output case under the assumption that an adequate persistent excitation condition is satisfied by each subsystem. Then, the proposed observer is redesigned to handle the case of sampled outputs leading thereby to a continuous-discrete time observer. The latter property is achieved thanks to the approach pursued along the convergence analysis. The effectiveness of the proposed observer is emphasised in a realistic simulation framework involving a mathematical model of a quadrotor which is diffeomorphic to the proposed class of considered systems.