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Showing papers on "Fuzzy control system published in 2014"


Journal ArticleDOI
TL;DR: It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded, and the tracking errors between the system outputs and the reference signals converge to a small neighborhood of zero by appropriate choice of the design parameters.
Abstract: This paper investigates the adaptive fuzzy decentralized fault-tolerant control (FTC) problem for a class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear system contains the unknown nonlinear functions, i.e., unmeasured states and actuator faults, which are modeled as both loss of effectiveness and lock-in-place. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive observer is designed to estimate the unmeasured states. By combining the backstepping technique with the nonlinear FTC theory, a novel adaptive fuzzy decentralized FTC scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded, and the tracking errors between the system outputs and the reference signals converge to a small neighborhood of zero by appropriate choice of the design parameters. Simulation results are provided to show the effectiveness of the control approach.

493 citations


Journal ArticleDOI
TL;DR: A comparative analysis of different energy management schemes for a fuel-cell-based emergency power system of a more-electric aircraft and the main criteria for performance comparison are the hydrogen consumption, the state of charges of the batteries/supercapacitors, and the overall system efficiency.
Abstract: This paper presents a comparative analysis of different energy management schemes for a fuel-cell-based emergency power system of a more-electric aircraft. The fuel-cell hybrid system considered in this paper consists of fuel cells, lithium-ion batteries, and supercapacitors, along with associated dc/dc and dc/ac converters. The energy management schemes addressed are state of the art and are most commonly used energy management techniques in fuel-cell vehicle applications, and they include the following: the state machine control strategy, the rule-based fuzzy logic strategy, the classical proportional-integral control strategy, the frequency decoupling/fuzzy logic control strategy, and the equivalent consumption minimization strategy. The main criteria for performance comparison are the hydrogen consumption, the state of charges of the batteries/supercapacitors, and the overall system efficiency. Moreover, the stresses on each energy source, which impact their life cycle, are measured using a new approach based on the wavelet transform of their instantaneous power. A simulation model and an experimental test bench are developed to validate all analysis and performances.

403 citations


Journal ArticleDOI
TL;DR: This work focuses on designing state- feedback and output-feedback sampled-data controllers to guarantee the resulting closed-loop dynamical systems to be asymptotically stable and satisfy H∞ disturbance attenuation level and suspension performance constraints.
Abstract: This paper investigates the problem of sampled-data $H_{\infty}$ control of uncertain active suspension systems via fuzzy control approach. Our work focuses on designing state-feedback and output-feedback sampled-data controllers to guarantee the resulting closed-loop dynamical systems to be asymptotically stable and satisfy $H_{\infty}$ disturbance attenuation level and suspension performance constraints. Using Takagi-Sugeno (T-S) fuzzy model control method, T-S fuzzy models are established for uncertain vehicle active suspension systems considering the desired suspension performances. Based on Lyapunov stability theory, the existence conditions of state-feedback and output-feedback sampled-data controllers are obtained by solving an optimization problem. Simulation results for active vehicle suspension systems with uncertainty are provided to demonstrate the effectiveness of the proposed method.

359 citations


Journal ArticleDOI
TL;DR: The objective is to develop an interval type-2 fuzzy AHP method together with a new ranking method for type- 2 fuzzy sets that applies the proposed method to a supplier selection problem.
Abstract: The membership functions of type-1 fuzzy sets have no uncertainty associated with it. While excessive arithmetic operations are needed with type-2 fuzzy sets with respect to type-1's, type-2 fuzzy sets generalize type-1 fuzzy sets and systems so that more uncertainty for defining membership functions can be handled. A type-2 fuzzy set lets us incorporate the uncertainty of membership functions into the fuzzy set theory. Some fuzzy multicriteria methods have recently been extended by using type-2 fuzzy sets. Analytic Hierarchy Process (AHP) is a widely used multicriteria method that can take into account various and conflicting criteria at the same time. Our objective is to develop an interval type-2 fuzzy AHP method together with a new ranking method for type-2 fuzzy sets. We apply the proposed method to a supplier selection problem.

318 citations


Journal ArticleDOI
TL;DR: An IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions.
Abstract: This paper focuses on designing interval type-2 (IT2) control for nonlinear systems subject to parameter uncertainties. To facilitate the stability analysis and control synthesis, an IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions. A novel IT2 fuzzy controller is proposed to perform the control process, where the membership functions and number of rules can be freely chosen and different from those of the IT2 T-S fuzzy model. Consequently, the IT2 fuzzy-model-based (FMB) control system is with imperfectly matched membership functions, which hinders the stability analysis. To relax the stability analysis for this class of IT2 FMB control systems, the information of footprint of uncertainties and the lower and upper membership functions are taken into account for the stability analysis. Based on the Lyapunov stability theory, some stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and achieve the control design. Finally, simulation and experimental examples are provided to demonstrate the effectiveness and the merit of the proposed approach.

311 citations


Journal ArticleDOI
TL;DR: A novel CAFTFTC scheme is proposed to guarantee that all follower nodes asymptotically synchronize a leader node with tracking errors converging to a small adjustable neighborhood of the origin in spite of actuator faults.
Abstract: In this paper, the cooperative adaptive fault tolerant fuzzy tracking control (CAFTFTC) problem of networked high-order multiagent with time-varying actuator faults is studied, and a novel CAFTFTC scheme is proposed to guarantee that all follower nodes asymptotically synchronize a leader node with tracking errors converging to a small adjustable neighborhood of the origin in spite of actuator faults. The leader node is modeled as a higher order nonautonomous nonlinear system. It acts as a command generator giving commands only to a small portion of the networked group. Each follower is assumed to have nonidentical unknown nonlinear dynamics, and the communication network is also assumed to be a weighted directed graph with a fixed topology. A distributed robust adaptive fuzzy controller is designed for each follower node such that the tracking errors are cooperative uniform ultimate boundedness (CUUB). Moreover, these controllers are distributed in the sense that the controller designed for each follower node only requires relative state information between itself and its neighbors. The adaptive compensation term of the optimal approximation errors and external disturbances is adopted to reduce the effects of the errors and disturbances, which removes the assumption that the upper bounds of unknown function approximation errors and disturbances should be known. Analysis of stability and parameter convergence of the proposed algorithm are conducted that are based on algebraic graph theory and Lyapunov theory. Comparing with results in the literature, the CAFTFTC scheme can minimize the time delay between fault occurrence and accommodation and reduce its adverse effect on system performance. In addition, the FTC scheme requires no additional fault isolation model, which is necessary in the traditional active FTC scheme. Finally, an example is provided to validate the theoretical results.

289 citations


Journal ArticleDOI
TL;DR: In this paper, a sufficient condition of reliable dissipativity analysis is proposed for T-S fuzzy systems with time-varying delays and sensor failures and a reliable filter with strict dissipativity is designed by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms.
Abstract: In this paper, the problem of reliable filter design with strict dissipativity has been investigated for a class of discrete-time T-S fuzzy time-delay systems. Our attention is focused on the design of a reliable filter to ensure a strictly dissipative performance for the filtering error system. Based on the reciprocally convex approach, firstly, a sufficient condition of reliable dissipativity analysis is proposed for T-S fuzzy systems with time-varying delays and sensor failures. Then, a reliable filter with strict dissipativity is designed by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms. Finally, numerical examples are provided to illustrate the effectiveness of the developed techniques.

284 citations


Journal ArticleDOI
TL;DR: The simulation results show that the fuzzy logic and PID control can realize the regenerative braking and can prolong the driving distance of EVs under the condition of ensuring braking quality.
Abstract: Regenerative braking can improve energy usage efficiency and can prolong the driving distance of electric vehicles (EVs). A creative regenerative braking system (RBS) is presented in this paper. The RBS is adapted to brushless dc (BLDC) motor, and it emphasizes on the distribution of the braking force, as well as BLDC motor control. In this paper, BLDC motor control utilizes the traditional proportional-integral-derivative (PID) control, and the distribution of braking force adopts fuzzy logic control. Because the fuzzy reasoning is slower than PID control, the braking torque can be real-time controlled by PID control. In comparison to other solutions, the new solution has better performance in regard to realization, robustness, and efficiency. Then, this paper presents the simulation results by analyzing the battery state of charge, braking force, and dc bus current under the environment of MATLAB and Simulink. The simulation results show that the fuzzy logic and PID control can realize the regenerative braking and can prolong the driving distance of EVs under the condition of ensuring braking quality. At last, it is verified that the proposed method is realizable for practical implementation.

273 citations


Journal ArticleDOI
TL;DR: In this article, a fuzzy logic controller (FLC)-based single-ended primary-induction converter (SEPIC) was proposed for maximum power point tracking (MPPT) operation of a photovoltaic (PV) system.
Abstract: This paper presents a fuzzy logic controller (FLC)-based single-ended primary-inductor converter (SEPIC) for maximum power point tracking (MPPT) operation of a photovoltaic (PV) system. The FLC proposed presents that the convergent distribution of the membership function offers faster response than the symmetrically distributed membership functions. The fuzzy controller for the SEPIC MPPT scheme shows high precision in current transition and keeps the voltage without any changes, in the variable-load case, represented in small steady-state error and small overshoot. The proposed scheme ensures optimal use of PV array and proves its efficacy in variable load conditions, unity, and lagging power factor at the inverter output (load) side. The real-time implementation of the MPPT SEPIC converter is done by a digital signal processor (DSP), i.e., TMS320F28335. The performance of the converter is tested in both simulation and experiment at different operating conditions. The performance of the proposed FLC-based MPPT operation of SEPIC converter is compared to that of the conventional proportional-integral (PI)-based SEPIC converter. The results show that the proposed FLC-based MPPT scheme for SEPIC can accurately track the reference signal and transfer power around 4.8% more than the conventional PI-based system.

265 citations


Journal ArticleDOI
TL;DR: The learning and modeling performances of the proposed PANFIS are numerically validated using several benchmark problems from real-world or synthetic datasets and showcases that the new method can compete and in some cases even outperform these approaches in terms of predictive fidelity and model complexity.
Abstract: Most of the dynamics in real-world systems are compiled by shifts and drifts, which are uneasy to be overcome by omnipresent neuro-fuzzy systems. Nonetheless, learning in nonstationary environment entails a system owning high degree of flexibility capable of assembling its rule base autonomously according to the degree of nonlinearity contained in the system. In practice, the rule growing and pruning are carried out merely benefiting from a small snapshot of the complete training data to truncate the computational load and memory demand to the low level. An exposure of a novel algorithm, namely parsimonious network based on fuzzy inference system (PANFIS), is to this end presented herein. PANFIS can commence its learning process from scratch with an empty rule base. The fuzzy rules can be stitched up and expelled by virtue of statistical contributions of the fuzzy rules and injected datum afterward. Identical fuzzy sets may be alluded and blended to be one fuzzy set as a pursuit of a transparent rule base escalating human's interpretability. The learning and modeling performances of the proposed PANFIS are numerically validated using several benchmark problems from real-world or synthetic datasets. The validation includes comparisons with state-of-the-art evolving neuro-fuzzy methods and showcases that our new method can compete and in some cases even outperform these approaches in terms of predictive fidelity and model complexity.

252 citations


Journal ArticleDOI
TL;DR: In this review, the application of genetic algorithms, particle swarm optimization and ant colony optimization are considered as three different paradigms that help in the design of optimal type-2 fuzzy controllers.

Journal ArticleDOI
TL;DR: In this article, a new load frequency control (LFC) for multi-area power systems is developed based on the direct-indirect adaptive fuzzy control technique, which guarantees stability of the overall closed-loop system.
Abstract: In this paper, a new load frequency control (LFC) for multi-area power systems is developed based on the direct–indirect adaptive fuzzy control technique. LFCs for each area are designed based on availability of frequency deviation of each area and tie-line power deviation between areas. The fuzzy logic system approximation capabilities are exploited to develop suitable adaptive control law and parameter update algorithms for unknown interconnected LFC areas. An ${H}_{\infty}$ tracking performance criterion is introduced to minimize the approximation errors and the external disturbance effects. The proposed controller guarantees stability of the overall closed-loop system. Simulation results for a real three-area power system prove the effectiveness of the proposed LFC and show its superiority over a classical PID controller and a type-2 fuzzy controller.

Journal ArticleDOI
TL;DR: The proposed sampled-data fuzzy control scheme is successfully applied to the chaotic Lorenz system, which is shown to be effective and less conservative compared with existing results.
Abstract: In this paper, a sampled-data fuzzy controller is designed to stabilize a class of chaotic systems. A Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic systems. Based on this general model, the exponential stability issue of the closed-loop systems with an input constraint is first investigated by a novel time-dependent Lyapunov functional, which is positive definite at sampling times but not necessary between the sampling times. Then, two sufficient conditions are developed for sampled-data fuzzy controller synthesis of the underlying T-S fuzzy model with or without input constraint. All the proposed results in this paper depend on both the upper and lower bounds on a sampling interval, and the available information about the actual sampling pattern is fully utilized. The proposed sampled-data fuzzy control scheme is successfully applied to the chaotic Lorenz system, which is shown to be effective and less conservative compared with existing results.

Journal ArticleDOI
TL;DR: An adaptive perturb and observe (P&O)-fuzzy control maximum power point tracking (MPPT) for photovoltaic (PV) boost dc-dc converter is presented in this paper.
Abstract: This study presents an adaptive perturb and observe (P&O)-fuzzy control maximum power point tracking (MPPT) for photovoltaic (PV) boost dc-dc converter. P&O is known as a very simple MPPT algorithm and used widely. Fuzzy logic is also simple to be developed and provides fast response. The proposed technique combines both of their advantages. It should improve MPPT performance especially with existing of noise. For evaluation and comparison analysis, conventional P&O and fuzzy logic control algorithms have been developed too. All the algorithms were simulated in MATLAB-Simulink, respectively, together with PV module of Kyocera KD210GH-2PU connected to PV boost dc-dc converter. For hardware implementation, the proposed adaptive P&O-fuzzy control MPPT was programmed in TMS320F28335 digital signal processing board. The other two conventional MPPT methods were also programmed for comparison purpose. Performance assessment covers overshoot, time response, maximum power ratio, oscillation and stability as described further in this study. From the results and analysis, the adaptive P&O-fuzzy control MPPT shows the best performance with fast time response, less overshoot and more stable operation. It has high maximum power ratio as compared to the other two conventional MPPT algorithms especially with existing of noise in the system at low irradiance.

Journal ArticleDOI
TL;DR: It is proved that the proposed fuzzy adaptive control approach can guarantee the semiglobal uniform ultimate boundedness for all the solutions of the closed-loop systems.
Abstract: In this paper, an adaptive fuzzy robust output feedback control problem is considered for a class of single-input and single-output nonlinear systems in a strict-feedback form. The considered systems possess the unstructured uncertainties, unknown dead zone, and the dynamics uncertainties, and they do not assume the states being available for the controller design. In the controller design, fuzzy logic systems are first used to approximate the unstructured uncertainties, and by utilizing the information of the bounds of the dead-zone slopes and treating the time-varying inputs coefficients as a system uncertainty, a fuzzy state observer is designed to estimate the unmeasured states. By combining a backstepping technique with a nonlinear small-gain approach, a new adaptive fuzzy robust output feedback control has been developed. It is proved that the proposed fuzzy adaptive control approach can guarantee the semiglobal uniform ultimate boundedness for all the solutions of the closed-loop systems. Simulation studies and comparisons with previous methods are included to illustrate the effectiveness of the proposed approach.

Journal ArticleDOI
TL;DR: This tutorial paper explains four different mathematical representations for general type-2 fuzzy sets (GT2 FS) and demonstrates that for the optimal design of a GT2 FLS, one should use the vertical-slice representation of its GT2 FSs because it is the only one of the four mathematical representations that is parsimonious.
Abstract: The purpose of this tutorial paper is to make general type-2 fuzzy logic systems (GT2 FLSs) more accessible to fuzzy logic researchers and practitioners, and to expedite their research, designs, and use. To accomplish this, the paper 1) explains four different mathematical representations for general type-2 fuzzy sets (GT2 FSs); 2) demonstrates that for the optimal design of a GT2 FLS, one should use the vertical-slice representation of its GT2 FSs because it is the only one of the four mathematical representations that is parsimonious; 3) shows how to obtain set theoretic and other operations for GT2 FSs using type-1 (T1) FS mathematics (α- cuts play a central role); 4) reviews Mamdani and TSK interval type-2 (IT2) FLSs so that their mathematical operations can be easily used in a GT2 FLS; 5) provides all of the formulas that describe both Mamdani and TSK GT2 FLSs; 6) explains why center-of sets type-reduction should be favored for a GT2 FLS over centroid type-reduction; 7) provides three simplified GT2 FLSs (two are for Mamdani GT2 FLSs and one is for a TSK GT2 FLS), all of which bypass type reduction and are generalizations from their IT2 FLS counterparts to GT2 FLSs; 8) explains why gradient-based optimization should not be used to optimally design a GT2 FLS; 9) explains how derivative-free optimization algorithms can be used to optimally design a GT2 FLS; and 10) provides a three-step approach for optimally designing FLSs in a progressive manner, from T1 to IT2 to GT2, each of which uses a quantum particle swarm optimization algorithm, by virtue of which the performance for the IT2 FLS cannot be worse than that of the T1 FLS, and the performance for the GT2 FLS cannot be worse than that of the IT2 FLS.

Journal ArticleDOI
TL;DR: This paper presents an edge-detection method that is based on the morphological gradient technique and generalized type-2 fuzzy logic that was tested with benchmark images and synthetic images and used the merit of Pratt measure to illustrate the advantages of using generalizedtype- 2 fuzzy logic.
Abstract: This paper presents an edge-detection method that is based on the morphological gradient technique and generalized type-2 fuzzy logic The theory of alpha planes is used to implement generalized type-2 fuzzy logic for edge detection For the defuzzification process, the heights and approximation methods are used Simulation results with a type-1 fuzzy inference system, an interval type-2 fuzzy inference system, and with a generalized type-2 fuzzy inference system for edge detection are presented The proposed generalized type-2 fuzzy edge-detection method was tested with benchmark images and synthetic images We used the merit of Pratt measure to illustrate the advantages of using generalized type-2 fuzzy logic

Journal ArticleDOI
TL;DR: This paper investigates the problem of Hankel-norm output feedback controller design for a class of T-S fuzzy stochastic systems and proposes the fuzzy-basis-dependent Lyapunov function approach and the conversion on theHankel- norm controller parameters.

Journal ArticleDOI
TL;DR: It is proved that the proposed control approach can guarantee that all the signals in the closed-loop system are bounded, and the input and output constraints are circumvented simultaneously.

Journal ArticleDOI
TL;DR: It is shown that the proposed method improves the existing FD techniques and achieves a better FD performance as the additional reference input sensitivity for faulty cases is considered.
Abstract: This paper is concerned with the fault detection (FD) problem in finite frequency domain for continuous-time Takagi-Sugeno fuzzy systems with sensor faults. Some finite-frequency performance indices are initially introduced to measure the fault/reference input sensitivity and disturbance robustness. Based on these performance indices, an effective FD scheme is then presented such that the generated residual is designed to be sensitive to both fault and reference input for faulty cases, while robust against the reference input for fault-free case. As the additional reference input sensitivity for faulty cases is considered, it is shown that the proposed method improves the existing FD techniques and achieves a better FD performance. The theory is supported by simulation results related to the detection of sensor faults in a tunnel-diode circuit.

Journal ArticleDOI
TL;DR: D-stability criteria are proposed to ensure that all the poles of the descriptor T-S fuzzy system are located within a disk contained in the unit circle, and a sufficient condition is presented such that the closed-loop system is regular, causal, and D-stable, in spite of parameter uncertainties and multiple state delays.
Abstract: This paper is concerned with the problems of D-stability and nonfragile control for a class of discrete-time descriptor Takagi-Sugeno (T-S) fuzzy systems with multiple state delays. D-stability criteria are proposed to ensure that all the poles of the descriptor T-S fuzzy system are located within a disk contained in the unit circle. Furthermore, a sufficient condition is presented such that the closed-loop system is regular, causal, and D-stable, in spite of parameter uncertainties and multiple state delays. The corresponding solvability conditions for the desired fuzzy-rule-dependent nonfragile controllers are also established. Finally, examples are given to show the effectiveness and advantages of the proposed techniques.

Journal ArticleDOI
TL;DR: An adaptive fuzzy controller design is studied for uncertain nonlinear systems and it is proven that all the signals in the closed-loop system are bounded and that the system output can be to follow the reference signal to a bounded compact set.
Abstract: An adaptive fuzzy controller design is studied for uncertain nonlinear systems in this paper. The considered systems are of the discrete-time form in a triangular structure and include the backlash and the external disturbance. By using the prediction function of future states, the systems are transformed into an n-step ahead predictor. The fuzzy logic systems (FLSs) are used to approximate the unknown functions, unknown backlash, and backlash inversion, respectively. A discrete-time tuning algorithm is developed to estimate the optimal fuzzy parameters. Compared with the previous works for the discrete-time systems with backlash, the main contributions of the paper are that 1) the rigorous restriction for the functional estimation error is removed, and 2) the external disturbance is bounded, but the bound is not required to be known. A novel controller and the adaptation laws are constructed by using the discrete Taylor series expansion and the difference Lyapunov analysis, and thus, those limitations in the previous works are overcome. It is proven that all the signals in the closed-loop system are bounded and that the system output can be to follow the reference signal to a bounded compact set. A simulation example is provided to illustrate the effectiveness of the proposed approach.

Journal ArticleDOI
TL;DR: A novel fault diagnostic algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known, and an accommodation scheme is proposed to compensate for both actuator time-varying gain and bias faults.
Abstract: The problem of fault-tolerant dynamic surface control (DSC) for a class of uncertain nonlinear systems with actuator faults is discussed and an active fault-tolerant control (FTC) scheme is proposed. Using the DSC technique, a novel fault diagnostic algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known. Further, an accommodation scheme is proposed to compensate for both actuator time-varying gain and bias faults, and avoids the controller singularity. In addition, the proposed controller guarantees that all signals of the closed-loop system are semiglobally uniformly ultimately bounded, and converge to a small neighborhood of the origin. Finally, the effectiveness of the proposed FTC approach is demonstrated on a simulated aircraft longitudinal dynamics example.

Journal ArticleDOI
TL;DR: The proposed design methods not only suit for a standard form of the fuzzy filter but also give more relaxed design conditions, which guarantees a prescribed H∞ performance of the filtering error system.
Abstract: This paper is concerned with the problem of nonfragile H∞ filtering for continuous-time Takagi-Sugeno (T-S) fuzzy systems. The filter to be designed is assumed to have two types of multiplicative gain variations. First, two relaxed H∞ filtering analysis conditions are proposed based on useful linear matrix inequality preliminaries. Whereafter, the results are exploited to derive sufficient conditions for designing a nonfragile H∞ filter, which guarantees a prescribed H∞ performance of the filtering error system. Compared with the existing results, the proposed design methods not only suit for a standard form of the fuzzy filter but also give more relaxed design conditions. Finally, simulation examples will be given to show the efficiency of the proposed design methods.

Journal ArticleDOI
TL;DR: A new funnel variable is defined so that the funnel virtual control forces the tracking error to fall within funnel boundary, and adaptive FESN method is also proposed to improve the approximation performance in conventional neural network algorithms.
Abstract: This paper presents a funnel dynamic surface control combined with fuzzy echo state networks (FESNs) for the prescribed tracking performance of a strict feedback multi-input-multi-output (MIMO) nonlinear dynamic system. A new funnel variable is defined so that the funnel virtual control forces the tracking error to fall within funnel boundary, and adaptive FESN method is also proposed to improve the approximation performance in conventional neural network algorithms. A strict feedback controller and adaptive laws for estimating the uncertainties were derived using the recursive steps of dynamic surface control based on the Lyapunov stability theory. Lyapunov stability analysis confirmed the boundedness and convergence of the closed-loop system. The performance of the proposed control scheme was validated by simulations and experimental applications to the tracking control of a MIMO nonlinear system and a robot manipulator.

Journal ArticleDOI
TL;DR: In this paper, a defect appeared in finite-time H∞ fuzzy control of nonlinear jump systems with time delays via dynamic observer-based state feedback, which the observerbased H ∞ controller cannot ensure stochastic finite time boundedness, and satisfying a prescribed level of disturbance attenuation for the resulting closed-loop error fuzzy Markov jump systems.
Abstract: This paper investigates a defect appearing in “Finite-time H∞ fuzzy control of nonlinear jump systems with time delays via dynamic observer-based state feedback,” which the observer-based finite-time H∞ controller via dynamic observer-based state feedback could not ensuring stochastic finite-time boundedness, and satisfying a prescribed level of H∞ disturbance attenuation for the resulting closed-loop error fuzzy Markov jump systems. The corrected results are presented, and the improved optimal algorithms and new simulation results are also provided in this paper.

Journal ArticleDOI
TL;DR: Novel stability conditions for Takagi-Sugeno (T-S) fuzzy systems are presented and it is shown that the conservativeness of the obtained criteria can be further reduced as the degree of the Lyapunov function increases.
Abstract: In this paper, novel stability conditions for Takagi-Sugeno (T-S) fuzzy systems are presented. The so-called nonquadratic membership-dependent Lyapunov function is first proposed, which is formulated in a higher order form of both the system states and the normalized membership functions than existing techniques in the literature. Then, new membership-dependent stability conditions are developed by the new Lyapunov function approach. It is shown that the conservativeness of the obtained criteria can be further reduced as the degree of the Lyapunov function increases. Two numerical examples are given to demonstrate the effectiveness and less conservativeness of the obtained theoretical results.

Book
16 Jun 2014
TL;DR: This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.
Abstract: Written by world-class leaders in type-2 fuzzy logic control, this book offers a self-contained reference for both researchers and students. The coverage provides both background and an extensive literature survey on fuzzy logic and related type-2 fuzzy control. It also includes research questions, experiment and simulation results, and downloadable computer programs on an associated website. This key resource will prove useful to students and engineers wanting to learn type-2 fuzzy control theory and its applications.

Journal ArticleDOI
TL;DR: This paper is concerned with the problems of dissipativity analysis and synthesis for discrete-time Takagi-Sugeno fuzzy systems with stochastic perturbation and time-varying delay with model transformation method combined with Lyapunov-Krasovskii technique.
Abstract: This paper is concerned with the problems of dissipativity analysis and synthesis for discrete-time Takagi-Sugeno fuzzy systems with stochastic perturbation and time-varying delay. First, a novel model transformation method is introduced to pull the time-varying delay uncertainty out of the original system. Consequently, the transformed model is composed of a linear time-invariant system and a norm-bounded uncertain subsystem. By using this model transformation method combined with the Lyapunov-Krasovskii technique, sufficient conditions of the dissipativity are established. Then, a fuzzy controller is designed to guarantee the dissipative performance of the closed-loop system. Finally, three examples are presented: one shows the effectiveness of model transformation method, the second performs the comparison with alternative approaches, and the third illustrates the applicability of the proposed dissipative control methods.

Journal ArticleDOI
TL;DR: A novel k-step fault-estimation observer is proposed to construct the k-1)th fault error dynamics and a dynamic output feedback fault tolerant controller is designed to compensate the fault effects on the closed-loop fuzzy system.
Abstract: This paper is concerned with the problem of robust fault estimation and fault-tolerant control for a class of Takagi–Sugeno (T–S) fuzzy systems with time-varying state delay and actuator faults. Based on the ( $k-1$ )th fault estimation information, a novel $k$ -step fault-estimation observer is proposed to construct the $k$ th fault error dynamics. The obtained fault estimates via $k$ -step fault-estimation can practically better depict the size and shape of the faults. Then, based on the information of online $k$ -step fault-estimation, a dynamic output feedback fault tolerant controller is designed to compensate the fault effects on the closed-loop fuzzy system. Furthermore, some less conservative delay dependent sufficient conditions for the existence of fault estimation observers and fault tolerant controllers are given in terms of solution to a set of linear matrix inequalities. Finally, simulation results of two numerical examples are presented to show the effectiveness and merits of the proposed methods.