Comparing Kalman Filters and Observers for Power System Dynamic State Estimation with Model Uncertainty and Malicious Cyber Attacks

Kalman filters and observers are two main classes of dynamic state estimation (DSE) routines. Power system DSE has been implemented by various Kalman filters, such as the extended Kalman filter (EKF) and the unscented Kalman filter (UKF). In this paper, we discuss two challenges for an effective power system DSE: (a) model uncertainty and (b) potential cyber attacks. To address this, the cubature Kalman filter (CKF) and a nonlinear observer are introduced and implemented. Various Kalman filters and the observer are then tested on the 16-machine, 68-bus system given realistic scenarios under model uncertainty and different types of cyber attacks against synchrophasor measurements. It is shown that CKF and the observer are more robust to model uncertainty and cyber attacks than their counterparts. Based on the tests, a thorough qualitative comparison is also performed for Kalman filter routines and observers.Comment: arXiv admin note: text overlap with arXiv:1508.0725

LMI-Based Reset Unknown Input Observer for State Estimation of Linear Uncertain Systems

This paper proposes a novel kind of Unknown Input Observer (UIO) called Reset Unknown Input Observer (R-UIO) for state estimation of linear systems in the presence of disturbance using Linear Matrix Inequality (LMI) techniques. In R-UIO, the states of the observer are reset to the after-reset value based on an appropriate reset law in order to decrease the $L_2$ norm and settling time of estimation error. It is shown that the application of the reset theory to the UIOs in the LTI framework can significantly improve the transient response of the observer. Moreover, the devised approach can be applied to both SISO and MIMO systems. Furthermore, the stability and convergence analysis of the devised R-UIO is addressed. Finally, the efficiency of the proposed method is demonstrated by simulation results

Estimation and cancellation of friction in control systems

The research reported in this dissertation concerns the estimation and cancellation of friction in control systems. For purposes of analysis, the Coulomb friction model, the extended Coulomb friction model as well as dynamic friction models are used. In addition, for systems with multiple degrees-of-freedom, a general matrix representation of friction is presented. For the design of the friction estimators, the theory of nonlinear observers is applied. In particular, for a system with multiple degrees-of-freedom, holonomic constraints, and multiple friction sources, three different observers are presented to estimate the friction force or torque. The first (Generalized Coulomb Friction Observer) is designed by assuming that friction is described by the classical Coulomb model; the second (Generalized Tracking Observer) considers friction as a system unknown constant input; and the third (Generalized Dynamic Friction Observer) is designed by assuming that friction is described by a dynamic model. For the analysis of the performance of the proposed estimators, two cases are considered. First considered is the case where both the system positions and velocities are available for measurements. Second considered is the case where only the system positions can be measured. In the first case, the observers use the measurements of the states to estimate the friction forces. In the second case, an additional reduced-order velocity observer is used to estimate the unmeasured velocities . The problem of friction cancellation in a system with multiple degrees-of-freedom, external inputs and friction sources is also addressed. Necessary and sufficient conditions are derived for cancellation of the friction. The conditions are based on the relative distribution of the system inputs and friction sources at the different system degrees-of-freedom. When cancellation is possible, a control law for accomplishing it is presented. The effectiveness of the proposed algorithms for friction estimation and cancellation is demonstrated by simulations. The observers are applied and compared in systems with linear as well as nonlinear dynamics. Finally, experimental data for the different friction compensators are taken and compared, using an experimental apparatus built for this purpose. The results of the experiments confirm the theory and demonstrate that friction can be estimated and cancelled by the algorithms developed in this research

A review of convex approaches for control, observation and safety of linear parameter varying and Takagi-Sugeno systems

This paper provides a review about the concept of convex systems based on Takagi-Sugeno, linear parameter varying (LPV) and quasi-LPV modeling. These paradigms are capable of hiding the nonlinearities by means of an equivalent description which uses a set of linear models interpolated by appropriately defined weighing functions. Convex systems have become very popular since they allow applying extended linear techniques based on linear matrix inequalities (LMIs) to complex nonlinear systems. This survey aims at providing the reader with a significant overview of the existing LMI-based techniques for convex systems in the fields of control, observation and safety. Firstly, a detailed review of stability, feedback, tracking and model predictive control (MPC) convex controllers is considered. Secondly, the problem of state estimation is addressed through the design of proportional, proportional-integral, unknown input and descriptor observers. Finally, safety of convex systems is discussed by describing popular techniques for fault diagnosis and fault tolerant control (FTC).Peer ReviewedPostprint (published version

Filter for detecting and isolating faults for a nonlinear system

In the paper the problem of detecting and isolating multiple faults for nonlinear systems is considered. A strategy of state filtering is derived in order to detect and isolate multiple faults which appear simultaneously or sequentially in a discrete time nonlinear systems with unknown inputs. For the considered system for which a fault isolation condition is fulfilled the proposed method can isolate p simultaneous faults with at least p+q output measurements, where q is the number of unknown inputs or disturbances. A reduced output residual vector of dimension p+q is generated and the elements of this vector are decoupled in a way that each element of the vector is associated with only one fault or unmeasured input