On the Observer Problem for Discrete-Time Control Systems

This paper studies the construction of observers for nonlinear time-varying discrete-time systems in a general context, where a certain function of the states must be estimated. Appropriate notions of robust complete observability are proposed, under which a constructive proof of existence of an observer is developed. Moreover, a "transitive observer property" is proven, according to which a state observer can be generated as the series connection of two observers. The analysis and the results are developed in general normed linear spaces, to cover both finite-dimensional and infinite-dimensional systems     

Polynomial Fuzzy Observer Designs: A Sum-of-Squares Approach

This paper presents a sum-of-squares (SOS) approach to polynomial fuzzy observer designs for three classes of polynomial fuzzy systems. The proposed SOS-based framework provides a number of innovations and improvements over the existing linear matrix inequality (LMI)-based approaches to Takagi-Sugeno (T-S) fuzzy controller and observer designs. First, we briefly summarize previous results with respect to a polynomial fuzzy system that is a more general representation of the well-known T-S fuzzy system. Next, we propose polynomial fuzzy observers to estimate states in three classes of polynomial fuzzy systems and derive SOS conditions to design polynomial fuzzy controllers and observers. A remarkable feature of the SOS design conditions for the first two classes (Classes I and II) is that they realize the so-called separation principle, i.e., the polynomial fuzzy controller and observer for each class can be separately designed without lack of guaranteeing the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. Although, for the last class (Class III), the separation principle does not hold, we propose an algorithm to design polynomial fuzzy controller and observer satisfying the stability of the overall control system in addition to converging state-estimation error (via the observer) to zero. All the design conditions in the proposed approach can be represented in terms of SOS and are symbolically and numerically solved via the recently developed SOSTOOLS and a semidefinite-program solver, respectively. To illustrate the validity and applicability of the proposed approach, three design examples are provided. The examples demonstrate the advantages of the SOS-based approaches for the existing LMI approaches to T-S fuzzy observer designs.     

Linear function observer for linear discrete-time systems

The problem of estimating the value of a linear function of the state deterministically is considered for a finite-dimensional linear time-invariant discrete-time system. A procedure is stated for constructing a minimum-time linear function observer, i.e., an observer which begins to produce the errorless estimate in minimum-time.     

Applying observer based FDI techniques to detect faults in dynamic and bounded stochastic distributions

This paper presents novel approach on applying the standard observer based fault detection technique to the change detection of the output probability density functions for dynamic stochastic systems. For such systems, the control inputs of the system appear as a set of variables in the probability density functions of the system output, and these variables affect the shape of the probability density function of the system output. Using the B-splines approximation theory, the measured probability density functions of the system output are represented by a set of weights which are functions of the control inputs to the system. This leads to a unique expression of the dynamic characteristics of the output probability density functions for the system. Using this expression, it has been shown that standard observer based fault detection technique can be used to detect any unexpected changes caused by the additive type of fault in the dynamic part of the system. In specific, two observers are constructed for the fault detection purposes, where the first observer is based on the linear weighted integration of the output probability density functions whilst the second observer uses the non-linear residual signal generated from the integration of the output probability density functions. In both cases, the convergence of the observers have been proved under certain conditions when there is no fault in the system. An applicability study to the detection of unexpected changes of particle size (i.e. flocculation size) in paper-making is included to demonstrate the use of the proposed algorithm and desired results have been obtained.     

Adaptive fault detection and isolation approach for actuator stuck faults in closed-loop systems

This paper addresses the fault detection and isolation (FDI) problem for linear time-invariant (LTI) systems under feedback control. Considered all the possible actuator stuck faults, the closed-loop systems are modeled via multiple models, i.e., fault-free model and faulty models. A fault detection observer and a bank of fault isolation observers are designed by using adaptive estimation techniques. The explicit fault detectability and isolability conditions are derived for determining the class of faults that are detectable and isolable. An F-18 aircraft model is employed to illustrate the effectiveness of the proposed FDI approach.     

A New Algorithm to Design Minimal Multi‐Functional Observers for Linear Systems

Designing minimum possible order (minimal) observers for multi‐input multi‐output (MIMO) linear systems have always been an interesting subject. In this paper, a new methodology to design minimal multi‐functional observers for linear time invariant (LTI) systems is proposed. The approach is applicable, and it also helps in regulating the convergence rate of the observed functions. It is assumed that the system is functional observable or functional detectable, which is less conservative than assuming the observability or detectability of the system. To satisfy the minimality of the observer, a recursive algorithm is provided that increases the order of the observer by appending the minimum required auxiliary functions to the desired functions that are going to be estimated. The algorithm increases the number of functions such that the necessary and sufficient conditions for the existence of a functional observer are satisfied. Moreover, a new methodology to solve the observer design interconnected equations is elaborated. Our new algorithm has advantages with regard to the other available methods in designing minimal order functional observers. Specifically, it is compared with the most common schemes, which are transformation based. Using numerical examples it is shown that under special circumstances, the conventional methods have some drawbacks. The problem partly lies in the lack of sufficient numerical degrees of freedom proposed by the conventional methods. It is shown that our proposed algorithm can resolve this issue. A recursive algorithm is also proposed to summarize the observer design procedure. Several numerical examples and simulation results illustrate the efficacy, superiority and different aspects of the theoretical findings.     

A modified sliding-mode observer design with application to diffusion equation

In many physical systems, the system's full state cannot be measured. An observer is designed to reconstruct the state from measurements. Disturbances often contribute to the dynamics of the system, and the designed observer must account for them. In this paper, a modified sliding-mode observer (SMO), a robust observer, is proposed that combines the efficiency of a nonlinear observer with the robustness of an SMO. The estimation error is proven to converge to zero under natural assumptions. This improved observer is compared with an extended Kalman filter and an unscented Kalman filter, as well as a standard SMO for three different versions of heat equation: a linear, a quasi-linear, and a nonlinear heat equation. The comparisons are done with and without an external disturbance. The simulations show improved performance of the modified SMO over other observers.     

LTR design of proportional-integral observers

This paper applies the proportional-integral (PI) observer in connection with loop transfer recovery (LTR) design for continuous-time systems. We show that a PI observer makes it possible to obtain time recovery, i.e., exact recovery for t →∞, under mild conditions. Based on an extension of the LQG/LTR method of proportional (P) observers, a systematic LTR design method is derived for the PI observer. Our recovery design method allows time recovery and frequency (normal) recovery to be done independently. Furthermore, we give explicit expressions for the recovery error when asymptotic recovery cannot be obtained. A design example demonstrates the advantages of time recovery in the non-minimum phase case.     

Multirate observer design via singular perturbation theory

In this paper multirate observer design is considered via singular perturbation theory. Following a discussion of the design of single-rate observers, i.e. fast- and slow-sampling observers, multirate observer design is developed within the framework of a decomposition-coordination principle. Problems of asymptotic stability and the responses of an error system are investigated, and the relation between single-rate and multirate observers is clarified.     

Robust decentralized output regulation of heterogeneous uncertain linear systems with multiple leaders via distributed adaptive protocols

In the current paper we consider the robust decentralized output regulation of heterogeneous uncertain linear systems with multiple leaders. A novel class of distributed observers is proposed. The states of the distributed observers synchronize to the states of their leaders, respectively. In contrast to the existing results, we consider a more general class of systems and furthermore we utilize the adaptive protocols to estimate the coupling weights between neighboring agents online. Therefore the observers and internal model based control laws can be designed in a purely distributed way, i.e., without knowledge of the associated matrix of the network topology. Finally we apply the proposed methods to solve the synchronization problem of a group of RLC networks and the simulation results show the effectiveness of the methods.     

Remarks on linearization of discrete-time autonomous systems and nonlinear observer design

This paper presents necessary and sufficient conditions under which a discrete-time autonomous system with outputs is locally state equivalent to an observable linear system or a system in the nonlinear observer form (Krener and Isidori, 1983). In particular, an open problem raised in Lee and Nam (1991), namely the observer linearization problem, is solved for a nonlinear system which may not be invertible (i.e., the mapping f may not be a local diffeomorphism). As a consequence, the nonlinear observer design problem is solved by means of exact linearization techniques.     

连续切换非方广义线性系统的观测器设计

针对一类连续切换非方广义线性系统,设计了广义状态观测器,并分析了状态估计误差的稳定性。首先通过矩阵的初等变换将连续切换非方广义线性系统的观测器设计问题转换为连续切换广义线性系统的观测器设计问题,之后设计第i个子系统的子观测器,可根据第i个子观测器构造这个广义切换系统的观测器。当观测器是全维观测器,且每个子系统都可检测时,状态估计误差甚至可以在任意切换下指数收敛到零。最后,通过数值实例和Matlab仿真分析说明了观测器设计方法简单可行,观测误差较其他方法的收敛速度快,证实了该方法的有效性和正确性。     

Computing by observing: Simple systems and simple observers

We survey and extend the work on the paradigm called “computing by observing”. Its central feature is that one considers the behavior of an evolving system as the result of a computation. To this purpose an external observer records this behavior. In this way, several computational trade-offs between the observer and the observed system can be determined. It has turned out that the observed behavior of computationally simple systems can be very complex, when an appropriate observer is used. For example, a restricted version of context-free grammars with regular observers suffices to obtain computational completeness. As a second instantiation presented here, we apply an observer to sticker systems, an abstract model of DNA computing. Finally, we introduce and investigate the case where the observers can read only one measure of the observed system (e.g., mass or temperature), modeling in this way the limitations in the observation of real physical systems. Finally, a research perspective on the topic is presented.     

Set-valued observers and optimal disturbance rejection

A set-valued observer (also called guaranteed state estimator) produces a set of possible states based on output measurements and models of exogenous signals. We consider the guaranteed state estimation problem for linear time-varying systems with a priori magnitude bounds on exogenous signals. We provide an algorithm to propagate the set of possible states based on output measurements and show that the centers of these sets provide optimal estimates in an l^∞-induced norm sense. We then consider the utility of set-valued observers for disturbance rejection with output feedback and derive the following general separation structure. An optimal controller can consist of a set-valued observer followed by a static nonlinear function on the observed set of possible states. A general construction of this function is provided in the scalar control case. Furthermore, in the special case of full-control, i.e., the number of control inputs equals the number of states, optimal output feedback controllers can take the form of an optimal estimate of the full-state feedback controller     

Insensitive observers for discrete time linear systems

This paper considers the problem of designing an observer insensitive to system parameter variations in discrete time linear multivariable systems. A K-insensitive observer is defined as an observer that can reconstruct a linear function of the state vector in spite of the variations of system parameters, provided the initial state of the observer is suitably chosen. A deadbeat observer is defined to be an observer that reconstructs the linear function for an arbitrary initial condition of the observer. Then, the existence of the K-insensitive observer is examined, and the class of K-insensitive observers is characterized. A necessary and sufficient condition is derived under which the K-insensitive deadbeat observer can be designed, and a simple algorithm is proposed to design the observer. The resulting observer is shown to be stable. The order of the observer is evaluated. The condition for generic solvability of the problem is also given.     

Full-order observer design for linear systems with unknown inputs

In this article, a full-order observer without unknown inputs reconstruction is suggested in order to achieve finite-time reconstruction of the state vector for a class of linear systems with unknown inputs. The observer is a simple one, its derivation being direct and easy. It will be shown that the problem of full-order observers for linear systems with unknown inputs can be reduced in this case to a standard one (the unknown input vector will not interfere in the observer equations). The effectiveness of the suggested design algorithm is illustrated by a numerical example (aircraft longitudinal motion), and, for the same aircraft dynamics, we make a comparison between our new observer and other already existing observers from the existence conditions and dynamic characteristics’ point of view; the superiority of the new designed observer is demonstrated.     

Control design based on a linear state function observer

A control design method based on a linear state function observer is proposed. The method is a semi-inverse design procedure in that the control law is not designed before the observer system, but is a result of the observer design. However, the observer design is not completely independent of the control design, but seeks to yield a feedback signal that is close to a prescribed control law. First, the observer design problem is considered as the reconstruction of a linear function of the state vector. The linear state function to be reconstructed is the given control law. Then, based on the derivation for linear state function observers, the observer design is formulated as a parameter optimization problem. The optimization objective is to generate a matrix that is close to the given feedback gain matrix. Based on that matrix, the form of the observer and a new control law can be determined. The semi-inverse design procedure can yield a reduced-order observer with dimension considerably smaller than that of the system. Two numerical examples are used to demonstrate the proposed design procedure.     

Partial state observers for linear systems with unknown inputs

We consider the problem of constructing partial state observers for discrete-time linear systems with unknown inputs. Specifically, for any given system, we develop a design procedure that characterizes the set of all linear functionals of the system state that can be reconstructed through a linear observer with a given delay. By treating the delay as a design parameter, we allow greater flexibility in estimating state functionals, and are able to obtain a procedure that directly produces the corresponding observer parameters. Our technique is also applicable to continuous-time systems by replacing delayed outputs with differentiated outputs.