Active fault tolerant control for nonlinear systems with simultaneous actuator and sensor faults

The goal of this paper is to describe a novel fault tolerant tracking control (FTTC) strategy based on robust fault estimation and compensation of simultaneous actuator and sensor faults. Within the framework of fault tolerant control (FTC) the challenge is to develop an FTTC design strategy for nonlinear systems to tolerate simultaneous actuator and sensor faults that have bounded first time derivatives. The main contribution of this paper is the proposal of a new architecture based on a combination of actuator and sensor Takagi-Sugeno (T-S) proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators together with a T-S dynamic output feedback control (TSDOFC) capable of time-varying reference tracking. Within this architecture the design freedom for each of the T-S estimators and the control system are available separately with an important consequence on robust L₂ norm fault estimation and robust L₂ norm closed-loop tracking performance. The FTTC strategy is illustrated using a nonlinear inverted pendulum example with time-varying tracking of a moving linear position reference. Keyword

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 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

Active sensor fault tolerant output feedback tracking control for wind turbine systems via T-S model

This paper presents a new approach to active sensor fault tolerant tracking control (FTTC) for offshore wind turbine (OWT) described via Takagi–Sugeno (T–S) multiple models. The FTTC strategy is designed in such way that aims to maintain nominal wind turbine controller without any change in both fault and fault-free cases. This is achieved by inserting T–S proportional state estimators augmented with proportional and integral feedback (PPI) fault estimators to be capable to estimate different generators and rotor speed sensors fault for compensation purposes. Due to the dependency of the FTTC strategy on the fault estimation the designed observer has the capability to estimate a wide range of time varying fault signals. Moreover, the robustness of the observer against the difference between the anemometer wind speed measurement and the immeasurable effective wind speed signal has been taken into account. The corrected measurements fed to a T–S fuzzy dynamic output feedback controller (TSDOFC) designed to track the desired trajectory. The stability proof with H∞ performance and D-stability constraints is formulated as a Linear Matrix Inequality (LMI) problem. The strategy is illustrated using a non-linear benchmark system model of a wind turbine offered within a competition led by the companies Mathworks and KK-Electronic

H∞ Robust T-S Fuzzy Design for Uncertain Nonlinear Systems with State Delays Based on Sliding Mode Control

This paper presents the fuzzy design of sliding mode control (SMC) for nonlinear systems with state delay, which can be represented by a Takagi-Sugeno (TS) model with uncertainties. There exist the parameter uncertainties in both the state and input matrices, as well as the unmatched external disturbance. The key feature of this work is the integration of SMC method with H∞ technique such that the robust asymptotically stability with a prescribed disturbance attenuation level γ can be achieved. A sufficient condition for the existence of the desired SMC is obtained by solving a set of linear matrix inequalities (LMIs). The reachability of the specified switching surface is proven. Simulation results show the validity of the proposed method

Nonlinear control for Two-Link flexible manipulator

Recently the use of robot manipulators has been increasing in many applications such as medical applications, automobile, construction, manufacturing, military, space, etc. However, current rigid manipulators have high inertia and use actuators with large energy consumption. Moreover, rigid manipulators are slow and have low payload-to arm-mass ratios because link deformation is not allowed. The main advantages of flexible manipulators over rigid manipulators are light in weight, higher speed of operation, larger workspace, smaller actuator, lower energy consumption and lower cost. However, there is no adequate closed-form solutions exist for flexible manipulators. This is mainly because flexible dynamics are modeled with partial differential equations, which give rise to infinite dimensional dynamical systems that are, in general, not possible to represent exactly or efficiently on a computer which makes modeling a challenging task. In addition, if flexibility nature wasn\u27t considered, there will be calculation errors in the calculated torque requirement for the motors and in the calculated position of the end-effecter. As for the control task, it is considered as a complex task since flexible manipulators are non-minimum phase system, under-actuated system and Multi-Input/Multi-Output (MIMO) nonlinear system. This thesis focuses on the development of dynamic formulation model and three control techniques aiming to achieve accurate position control and improving dynamic stability for Two-Link Flexible Manipulators (TLFMs). LQR controller is designed based on the linearized model of the TLFM; however, it is applied on both linearized and nonlinear models. In addition to LQR, Backstepping and Sliding mode controllers are designed as nonlinear control approaches and applied on both the nonlinear model of the TLFM and the physical system. The three developed control techniques are tested through simulation based on the developed dynamic formulation model using MATLAB/SIMULINK. Stability and performance analysis were conducted and tuned to obtain the best results. Then, the performance and stability results obtained through simulation are compared. Finally, the developed control techniques were implemented and analyzed on the 2-DOF Serial Flexible Link Robot experimental system from Quanser and the results are illustrated and compared with that obtained through simulation

Motion control and synchronisation of multi-axis drive systems

Motion control and synchronisation of multi-axis drive system