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

Analysis, filtering, and control for Takagi-Sugeno fuzzy models in networked systems

Copyright © 2015 Sunjie Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.The fuzzy logic theory has been proven to be effective in dealing with various nonlinear systems and has a great success in industry applications. Among different kinds of models for fuzzy systems, the so-called Takagi-Sugeno (T-S) fuzzy model has been quite popular due to its convenient and simple dynamic structure as well as its capability of approximating any smooth nonlinear function to any specified accuracy within any compact set. In terms of such a model, the performance analysis and the design of controllers and filters play important roles in the research of fuzzy systems. In this paper, we aim to survey some recent advances on the T-S fuzzy control and filtering problems with various network-induced phenomena. The network-induced phenomena under consideration mainly include communication delays, packet dropouts, signal quantization, and randomly occurring uncertainties (ROUs). With such network-induced phenomena, the developments on T-S fuzzy control and filtering issues are reviewed in detail. In addition, some latest results on this topic are highlighted. In the end, conclusions are drawn and some possible future research directions are pointed out.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 11301118 and 61174136, the Natural Science Foundation of Jiangsu Province of China under Grant BK20130017, the Fundamental Research Funds for the Central Universities of China under Grant CUSF-DH-D-2013061, the Royal Society of the U.K., and the Alexander von Humboldt Foundation of Germany

A virtual actuator approach for the secure control of networked LPV systems under pulse-width modulated DoS attacks

In this paper, we formulate and analyze the problem of secure control in the context of networked linear parameter varying (LPV) systems. We consider an energy-constrained, pulse-width modulated (PWM) jammer, which corrupts the control communication channel by performing a denial-of-service (DoS) attack. In particular, the malicious attacker is able to erase the data sent to one or more actuators. In order to achieve secure control, we propose a virtual actuator technique under the assumption that the behavior of the attacker has been identified. The main advantage brought by this technique is that the existing components in the control system can be maintained without need of retuning them, since the virtual actuator will perform a reconfiguration of the plant, hiding the attack from the controller point of view. Using Lyapunov-based results that take into account the possible behavior of the attacker, design conditions for calculating the virtual actuators gains are obtained. A numerical example is used to illustrate the proposed secure control strategy.Peer ReviewedPostprint (author's final draft

Integrated fault estimation and fault-tolerant control for uncertain Lipschitz nonlinear systems

This paper proposes an integrated fault estimation and fault-tolerant control (FTC) design for Lipschitz non-linear systems subject to uncertainty, disturbance, and actuator/sensor faults. A non-linear unknown input observer without rank requirement is developed to estimate the system state and fault simultaneously, and based on these estimates an adaptive sliding mode FTC system is constructed. The observer and controller gains are obtained together via H∞ optimization with a single-step linear matrix inequality (LMI) formulation so as to achieve overall optimal FTC system design. A single-link manipulator example is given to illustrate the effectiveness of the proposed approach

Design considerations for flight test of a fault inferring nonlinear detection system algorithm for avionics sensors

The modifications to the design of a fault inferring nonlinear detection system (FINDS) algorithm to accommodate flight computer constraints and the resulting impact on the algorithm performance are summarized. An overview of the flight data-driven FINDS algorithm is presented. This is followed by a brief analysis of the effects of modifications to the algorithm on program size and execution speed. Significant improvements in estimation performance for the aircraft states and normal operating sensor biases, which have resulted from improved noise design parameters and a new steady-state wind model, are documented. The aircraft state and sensor bias estimation performances of the algorithm's extended Kalman filter are presented as a function of update frequency of the piecewise constant filter gains. The results of a new detection system strategy and failure detection performance, as a function of gain update frequency, are also presented

H∞ fault estimation with randomly occurring uncertainties, quantization effects and successive packet dropouts: The finite-horizon case

In this paper, the finite-horizon H∞ fault estimation problem is investigated for a class of uncertain nonlinear time-varying systems subject to multiple stochastic delays. The randomly occurring uncertainties (ROUs) enter into the system due to the random fluctuations of network conditions. The measured output is quantized by a logarithmic quantizer before being transmitted to the fault estimator. Also, successive packet dropouts (SPDs) happen when the quantized signals are transmitted through an unreliable network medium. Three mutually independent sets of Bernoulli-distributed white sequences are introduced to govern the multiple stochastic delays, ROUs and SPDs. By employing the stochastic analysis approach, some sufficient conditions are established for the desired finite-horizon fault estimator to achieve the specified H∞ performance. The time-varying parameters of the fault estimator are obtained by solving a set of recursive linear matrix inequalities. Finally, an illustrative numerical example is provided to show the effectiveness of the proposed fault estimation approach

Robust Fault Tolerant Control for Discrete-Time Dynamic Systems With Applications to Aero Engineering Systems

Unexpected faults in actuators and sensors may degrade the reliability and safety of aero engineering systems. Therefore, there is motivation to develop integrated fault tolerant control techniques with applications to aero engineering systems. In this paper, discrete-time dynamic systems, in the presence of simultaneous actuator/sensor faults, partially decoupled unknown input disturbances, and sensor noises, are investigated. A jointly state/fault estimator is formulated by integrating an unknown input observer, augmented system approach, and optimization algorithm. Unknown input disturbances can be either decoupled by an unknown input observer, or attenuated by a linear matrix inequality optimization, enabling the estimation error to be input-to-state stable. Estimator-based signal compensation is then implemented to mitigate adverse effects from the unanticipated actuator and sensor faults. A pre-designed controller, which maintains normal system behaviors under a fault-free scenario, is allowed to work along with the presented fault tolerant mechanism of the signal compensations. The fault-tolerant closed-loop system can be ensured to mitigate the effects from the faults, guarantee the input-to-state stability, and satisfy the required robustness performance. The proposed fault estimation and fault tolerant control methods are developed for both discrete-time linear and discrete-time Lipschitz nonlinear systems. Finally, the proposed techniques are applied to a jet engine system and a flight control system for simulation validation