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

Discrete Time Systems

Discrete-Time Systems comprehend an important and broad research field. The consolidation of digital-based computational means in the present, pushes a technological tool into the field with a tremendous impact in areas like Control, Signal Processing, Communications, System Modelling and related Applications. This book attempts to give a scope in the wide area of Discrete-Time Systems. Their contents are grouped conveniently in sections according to significant areas, namely Filtering, Fixed and Adaptive Control Systems, Stability Problems and Miscellaneous Applications. We think that the contribution of the book enlarges the field of the Discrete-Time Systems with signification in the present state-of-the-art. Despite the vertiginous advance in the field, we also believe that the topics described here allow us also to look through some main tendencies in the next years in the research area

Market liquidity and its incorporation into risk management.

The excessively optimistic assessment of market liquidity, i.e. the belief that transactions can be settled at current prices without any notable delays or transaction costs, may be a serious threat to financial stability–the near failure of the LTCM hedge fund in 1998 was a case in point. Admittedly, the financial community today appears to have a better grasp of the risks arising from liquidity illusion. The fact nonetheless remains that current risk management tools, particularly the most common Value at Risk (VaR) measures, do not capture this complex component of market risk satisfactorily. In fact, standard VaR calculations do not take specific account of the risk to which a portfolio is exposed at the time it is liquidated. This article aims to explore the different aspects of liquidity risk and provide signposts to methods for incorporating this risk into existing risk control tools. We fi rst examine “normal” or average liquidity risk, which corresponds to the costs of liquidating or hedging a position in tranquil periods, then illiquidity risk that arises in crisis periods and results in the market’s inability to absorb order flows without violent price adjustments. Two separate methodologies, which must nonetheless be combined in a comprehensive approach, are required to analyse these two situations. In the first case we seek to assess the frictions that emerge in imperfect markets by using bid-ask spread measures and by analysing the negative impact on prices resulting from the liquidation of a sizeable portfolio. In the case of extreme risk, we assess the potential consequences of occurrences that are rare, fundamentally uncertain and systemically important. In each case, we suggest and describe a number of techniques that aim to incorporate these elements into the risk measurement and management systems used by private market participants, while underscoring the obstacles to application given the frequent unavailability of the data required. We show that these techniques are relevant because they provide a more cautious and more realistic assessment of financial institutions’ exposure to risk. Lastly, it is in market participants’ own interest for central banks and supervisory bodies to have at their disposal the information required to construct indicators for monitoring market liquidity or conducting suffi ciently comprehensive stress tests in order to assess the fi nancial system’s resilience to liquidity shocks, while taking into account all the externalities that market participants do not individually consider.

A parametric approach to logistic control within manufacturing simulation

Simulation offers a powerful way to investigate the boundaries of what can be achieved by a manufacturing system, demonstrating the impact of schedules and policy decisions such as the placement of buffers and the size of safety stocks. Unfortunately, the construction of factory models at the necessary level of detail is a time-consuming process, requiring specialist skills. This paper describes a novel approach to the representation of logistic control in the simulation of a business unit at Volvo Aero in Trollhättan, Sweden. Several innovative features were built into the model, making it possible for users who were not simulation experts to explore a broad range of scenarios. The resulting model architecture, as described in this paper, takes simulation out of the computer lab and places it in the hands of managers, as an enabler of the responsive enterprise

Fractional Order Fault Tolerant Control - A Survey

In this paper, a comprehensive review of recent advances and trends regarding Fractional Order Fault Tolerant Control (FOFTC) design is presented. This novel robust control approach has been emerging in the last decade and is still gathering great research efforts mainly because of its promising results and outcomes. The purpose of this study is to provide a useful overview for researchers interested in developing this interesting solution for plants that are subject to faults and disturbances with an obligation for a maintained performance level. Throughout the paper, the various works related to FOFTC in literature are categorized first by considering their research objective between fault detection with diagnosis and fault tolerance with accommodation, and second by considering the nature of the studied plants depending on whether they are modelized by integer order or fractional order models. One of the main drawbacks of these approaches lies in the increase in complexity associated with introducing the fractional operators, their approximation and especially during the stability analysis. A discussion on the main disadvantages and challenges that face this novel fractional order robust control research field is given in conjunction with motivations for its future development. This study provides a simulation example for the application of a FOFTC against actuator faults in a Boeing 747 civil transport aircraft is provided to illustrate the efficiency of such robust control strategies

A parametric approach to logistic control within manufacturing simulation

Simulation offers a powerful way to investigate the boundaries of what can be achieved by a manufacturing system, demonstrating the impact of schedules and policy decisions such as the placement of buffers and the size of safety stocks. Unfortunately, the construction of factory models at the necessary level of detail is a time-consuming process, requiring specialist skills. This paper describes a novel approach to the representation of logistic control in the simulation of a business unit at Volvo Aero in Trollhättan, Sweden. Several innovative features were built into the model, making it possible for users who were not simulation experts to explore a broad range of scenarios. The resulting model architecture, as described in this paper, takes simulation out of the computer lab and places it in the hands of managers, as an enabler of the responsive enterprise

Non-Fragile Observer-Based Adaptive Integral Sliding Mode Control for a Class of T-S Fuzzy Descriptor Systems With Unmeasurable Premise Variables

The issue of non-fragile observer-based adaptive integral sliding mode control for a class of Takagi–Sugeno (T-S) fuzzy descriptor systems with uncertainties and unmeasurable premise variables is investigated. General nonlinear systems are represented by nonlinear T-S fuzzy descriptor models, because premise variables depend on unmeasurable system states and fuzzy models have different derivative matrices. By introducing the system state derivative as an auxiliary state vector, original fuzzy descriptor systems are transformed into augmented systems for which system properties remain the same. First, a novel integral sliding surface, which includes estimated states of the sliding mode observer and controller gain matrices, is designed to obtain estimation error dynamics and sliding mode dynamics. Then, some sufficient linear matrix inequality (LMI) conditions for designing the observer and the controller gains are derived using the appropriate fuzzy Lyapunov functions and Lyapunov theory. This approach yields asymptotically stable sliding mode dynamics. Corresponding auxiliary variables are introduced, and the Finsler's lemma is employed to eliminate coupling of controller gain matrices, observer gain matrices, Lyapunov function matrices, and/or observer gain perturbations. An observer-based integral sliding mode control strategy is obtained to assure that reachability conditions are satisfied. Moreover, a non-fragile observer and a non-fragile adaptive controller are developed to compensate for system uncertainties and perturbations in both the observer and the controller. Finally, example results are presented to illustrate the effectiveness and merits of the proposed method