Improved asynchronous stabilization method for nonhomogeneous Markovian jump fuzzy systems with incomplete transition rates

This paper proposes an improved asynchronous stabilization method for nonhomogeneous Markovian jump fuzzy systems (MJFSs) with incomplete transition rates via a nonparallel distributed compensation (non-PDC) control scheme. To cover a more realistic situation in the continuous-time MJFS domain, this paper focuses on addressing the following issues differently from previous studies: 1) emergence of a nonhomogeneous Markov process and asynchronous control mode, 2) separation of the Lyapunov matrix from the control gain within stabilization conditions, and 3) relaxation of stabilization conditions subject to multiple time-varying parameters. Specifically, the effects of nonhomogeneity and asynchronism are simultaneously reflected in the stabilization conditions, and separation and relaxation techniques are additionally developed as needed. Finally, the advantages of our method are illustrated through two examples: the first is provided to show the effectiveness of the proposed separation technique, and the second is provided to show that the relaxed stabilization conditions are less conservative than previous results.     

Stabilization via extended nonquadratic boundedness for constrained nonlinear systems in Takagi–Sugeno's form

This paper studies stabilization of the Takagi–Sugeno fuzzy system with input and state constraints and bounded noise. The technique of extended nonquadratic boundedness is proposed based on the existing quadratic boundedness. Under the non-parallel distributed compensation law, the state of the closed-loop system is stabilizing to a neighborhood of the origin specified via an extended nonquadratic Lyapunov function. The existing technique for relaxing the linear matrix inequality conditions can be properly applied to obtain computationally tractable stability conditions. A simulation example is given to show the effectiveness of the controller.     

Asymptotically necessary and sufficient stability conditions for discrete-time Takagi–Sugeno model: Extended applications of Polya's theorem and homogeneous polynomials

The stability and stabilization conditions of the nonlinear system in Takagi–Sugeno's form are considered. The homogeneously polynomially nonquadratic (HPNQ) Lyapunov functions and homogeneously polynomially parameterized (HPP) state feedback laws are adopted. By generalizing the procedure based on the Polya's theorem, the asymptotically necessary and sufficient (ANS) stability and stabilization conditions in the case of HPNQ Lyapunov functions and HPP control laws are reformulated. The major contribution of this paper is to give the parallel results using the multiple indices, so that the slack matrices can be extensively utilized to improve the numerical efficiency. The effectiveness of the results is illustrated by the numerical examples.     

Sum-of-squares-based robust H∞ controller design for discrete-time polynomial fuzzy systems

This paper investigates a robust H_∞ controller design for discrete-time polynomial fuzzy systems based on the sum-of-squares (SOS) approach when model uncertainties and external disturbances are simultaneously considered. At the beginning of the controller design procedure, a general discrete-time polynomial fuzzy control system proposed in this paper is used to represent a nonlinear system containing model uncertainties and external disturbances. Subsequently, through use of a nonquadratic Lyapunov function and the H_∞ performance index, the novel SOS-based robust H_∞ stability conditions are derived to guarantee the stability of the entire control system. By solving those stability conditions, control gains of the robust H_∞ polynomial fuzzy controller are obtained. Because the model uncertainties and external disturbances are considered simultaneously in the controller design procedure, the closed-loop control system achieves greater robustness and H_∞ performance against model uncertainties and external disturbances. Moreover, the novel operating-domain-based robust H_∞ stability conditions are derived by considering the operating domain constraint to relax the conservativeness of solving the stability conditions. Finally, simulation results demonstrated the availability and effectiveness of the proposed stability conditions, which are more general than those used in existing approaches.     

Asynchronous boundary stabilization for T-S fuzzy Markov jump delay reaction-diffusion neural networks

This paper deals with the exponential boundary stabilization for a class of Markov jump reaction-diffusion neural networks (MJRDNNs) with mixed time-varying delays, which is described by T-S fuzzy model. It is assumed that observed modes in boundary controller are not synchronized with the system modes. Based on a hidden Markov model (HMM), a novel asynchronous boundary control law is developed by using observed modes. Compared with the existing control strategies for distributed parameter systems, the asynchronous boundary control scheme can not only save the cost of the controller installation, but also bring less conservativeness. A delay-dependent sufficient condition to guarantee the exponentially mean square stability is established for T-S fuzzy MJRDNNs with mixed time-varying delays by constructing a Lyapunov functional and utilizing the vector-value Wirtinger-type inequality. Meanwhile, in order to get the designing scheme of the boundary controller, an equivalent LMI-based sufficient criterion is established. In the end, the effectiveness of the proposed results is illustrated by simulation examples.     

PDC and Non-PDC fuzzy control with relaxed stability conditions for contintuous-time multiplicative noised fuzzy systems

This paper presents a relaxed scheme of fuzzy controller design for continuous-time nonlinear stochastic systems that are constructed by the Takagi–Sugeno (T–S) fuzzy models with multiplicative noises. Through Nonquadratic Lyapunov Functions (NQLF) and Non-Parallel Distributed Compensation (Non-PDC) control law, the less conservative Linear Matrix Inequality (LMI) stabilization conditions on solving fuzzy controllers are derived. Furthermore, in order to study the effects of stochastic behaviors on dynamic systems in real environments, the multiplicative noise term is introduced in the consequent part of fuzzy systems. For decreasing the conservatism of the conventional PDC-based fuzzy control, the NQLF stability synthesis approach is developed in this paper to obtain relaxed stability conditions for T–S fuzzy models with multiplicative noises. Finally, some simulation examples are provided to demonstrate the validity and applicability of the proposed fuzzy controller design approach.     

On stability and stabilization of singular uncertain Takagi–Sugeno fuzzy systems

This paper deals with the problem of robust stability and robust stabilization for a class of continuous-time singular Takagi–Sugeno fuzzy systems. Sufficient conditions on stability and stabilization are proposed in terms of strict LMI (Linear Matrix Inequality) for uncertain T–S fuzzy models. In order to reduce the conservatism of results developed using quadratic method, an approach based on non-quadratic Lyapunov functions and S-procedure is proposed. Illustrative examples are given to show the effectiveness of the given results.     

Stabilization of positive Takagi–Sugeno fuzzy discrete-time systems with multiple delays and bounded controls

This paper deals with the problem of stabilization by state feedback control of Takagi–Sugeno (T–S) fuzzy discrete-time systems with multiple fixed delays while imposing positivity in closed-loop. The obtained results are presented under linear programming (LP) form. In particular, the synthesis of state feedback controllers is first solved in terms of Linear programming for the unbounded controls case. This result is then extended to the stabilization problem by nonnegative controls, and stabilization by bounded controls. The stabilization conditions are derived using the single Lyapunov–Krasovskii functional (LKF). An example of a real plant is studied to show the advantages of the design procedure. A comparison between linear programming and LMI approaches is presented.     

Improved stabilization criteria for fuzzy systems under variable sampling

This paper investigates the problem of stabilization for fuzzy sampled-data systems with variable sampling. A novel Lyapunov–Krasovskii functional (LKF) is introduced to the fuzzy systems. The benefit of the new approach is that the LKF develops more information about actual sampling pattern of the fuzzy sampled-data systems. In addition, some symmetric matrices involved in the LKF are not required to be positive definite. Based on a recently introduced Wirtinger-based integral inequality that has been shown to be less conservative than Jensen’s inequality, much less conservative stabilization conditions are obtained. Then, the corresponding sampled-data controller can be synthesized by solving a set of linear matrix inequalities (LMIs). Finally, an illustrative example is given to show the feasibility and effectiveness of the proposed method.     

Observer-based quantized control for discrete-time switched systems with infinitely distributed delay

This paper studies the globally almost surely exponential stabilization of discrete-time switched systems (DSSs) with infinitely distributed delay. On account of the limitation of communication resources in the actual environment, a novel class of observer-based quantized control scheme is designed that incorporates the quantization of three kinds of signals: the measurement output, the state of observer, and the measurement output of observer. By employing S-procedure and some matrix inequality techniques, an algorithm is given to design the controller parameters. To reduce the conservativeness of the obtained results, new multiple Lyapunov–Krasovskii functionals (LKFs) with negative terms are proposed to deal with the infinitely distributed delay and mode-dependent average dwell time (MDADT) switching based on transition probability (TP) is introduced to study the stabilization of DSSs with both stable and unstable modes. It is worth highlighting that the improved stabilization conditions for DSSs can release the restriction on the length of dwell time (DT) of stable and unstable subsystems. Finally, a simulation example is presented to demonstrate the validity of the proposed method.     

Dynamic event-triggered optimal tracking control for constrained nonlinear stochastic systems

This paper investigates the optimal tracking control problem (OTCP) for nonlinear stochastic systems with input constraints under the dynamic event-triggered mechanism (DETM). Firstly, the OTCP is converted into the stabilizing optimization control problem by constructing a novel stochastic augmented system. The discounted performance index with nonquadratic utility function is formulated such that the input constraint can be encoded into the optimization problem. Then the adaptive dynamic programming (ADP) method of the critic-only architecture is employed to approximate the solutions of the OTCP. Unlike the conventional ADP methods based on time-driven mechanism or static event-triggered mechanism (SETM), the proposed adaptive control scheme integrates the DETM to further lighten the computing and communication loads. Furthermore, the uniform ultimately boundedness (UUB) of the critic weights and the tracking error are analysed with the Lyapunov theory. Finally, the simulation results are provided to validate the effectiveness of the proposed approach.     

Fixed-time stabilization of IT-2 T-S fuzzy control systems with discontinuous interconnections: Indefinite derivative Lyapunov method

Using the interval type-2 Takagi–Sugeno (IT-2 T-S) fuzzy control method, this paper formulates a class of non-autonomous interconnected dynamical system (IDS) with discontinuities. Under the differential inclusion (DI) framework, the fixed-time stabilization (FXTS) problem is studied via indefinite derivative Lyapunov approach, where the time-derivative of constructed Lyapunov function doesn’t have to be negative/semi-negative. By designing novel IT-2 T-S fuzzy switching control protocol possessing time-varying control gain coefficients, several sufficient stabilization conditions are obtained to determine the system’s stability in fixed time. Furthermore, the settling time (ST) of FXTS is estimated. Due to the time-varying property of control gain coefficients and indefiniteness of system’s parameters, the advantage of the IT-2 T-S fuzzy switching control protocol designed in this paper is that its control gain coefficients are not only more flexible, but also can affect the estimation of ST. Finally, the designed control protocols and FXTS results are confirmed by numerical example.     

Fuzzy adaptive fault-tolerant tracking control of MIMO stochastic pure-feedback nonlinear systems with actuator failures

This paper studies the adaptive fuzzy fault-tolerant control design problem for a class of stochastic multi-input and multi-output (MIMO) nonlinear systems in pure-feedback form. The nonlinear systems under study contain unknown functions, unmeasured states and actuator faults, which are described by the loss of effectiveness and lock-in-place modes. With the help of fuzzy logic systems identifying uncertain stochastic nonlinear systems, a fuzzy state observer is established for estimating the unmeasured states. Based on the backstepping design technique with the nonlinear tolerant-fault control theory, an adaptive fuzzy output feedback faults-tolerant control approach is developed. It is proved that the proposed fault-tolerant control approach can guarantee that all the signals of the resulting closed-loop system are bounded in probability. Moreover, the observer errors and tracking errors can be regulated to a small neighborhood of the origin by choosing design parameters appropriately. A simulation example is provided to show the effectiveness of the proposed approach.     

Fault estimation and fault tolerant control for discrete-time nonlinear systems with perturbation by a mixed design scheme

This paper focuses on the observer-based fault-tolerant control problem for the discrete-time nonlinear systems with the perturbation and the fault signals. First, the nonlinear term with perturbation is put into the local nonlinear part so that the nonlinear system with perturbation can be described as an interval type-1 (IT1) T-S fuzzy system. Then, based on the unknown input observer technology, the IT1 T-S fuzzy fault estimation (FE) observer scheme is presented to obtain the real-time FE information and decouple the local nonlinear part from the estimation error system, where the design complexity and the computational burden are reduced simultaneously. Second, based on the real-time FE information, an FE-based interval type-2 (IT2) T-S fuzzy fault-tolerant control scheme is presented to achieve the compensation for the influence of the fault signal and the stabilization for the system. Different from the traditional methods, a mixed design scheme, which is based on the IT1 T-S fuzzy fault estimation observer method and the IT2 T-S fuzzy fault-tolerant controller method, is proposed in this paper. This strategy can not only reduce the computational burden, but also obtain a less conservative result. Finally, the effectiveness of the mixed design approach is illustrated by an example.     

Fuzzy sliding mode control design of Markovian jump systems with time-varying delay

This paper studies the robust stochastic stabilization problem for a class of fuzzy Markovian jump systems with time-varying delay and external disturbances via sliding mode control scheme. Based on the equivalent-input-disturbance (EID) approach, an online disturbance estimator is implemented to reject the unknown disturbance effect on the considered system. Specifically, to obtain exact EID estimation Luenberger fuzzy state observer and a low-pass filter incorporated to the closed-loop system. Moreover, novel fuzzy EID-based sliding mode control law is constructed to ensure the stability of the closed-loop system with satisfactory disturbance rejection performance. By employing Lyapunov stability theory and some integral inequalities, a new set of delay-dependent robust stability conditions is derived in terms of linear matrix inequalities (LMIs). The resulting LMI is used to find the gains of the state-feedback controller and the state observer a for the resulting closed-loop system. At last, numerical simulations based on the single-link arm robot model are provided to illustrate the proposed design technique.     

Affine matched parameterization approach to sampled-data stabilization criteria for T-S fuzzy systems with variable sampling

This paper presents new parameterized sampled-data stabilization criteria using affine transformed membership functions for T-S fuzzy systems. To deal with the sampled control input having aperiodic sampling intervals, the proposed method adopts new looped functionals, and employs a modified free weighting matrix inequality. A relaxed condition for the controller design is derived by formulating the constraint conditions of the membership functions in the proposed controller with affinely matched weighting parameter vectors. Based on a newly devised lemma for handling affinely matched vectors, the stabilization and guaranteed cost performance criteria are given in terms of linear matrix inequalities (LMIs). The superiority of the presented method is demonstrated via significantly improved results in numerical examples.     

Fuzzy quantized sampled-data control for extended dissipative analysis of T–S fuzzy system and its application to WPGSs

This paper investigates the issues of extended dissipativity performance and stabilization for T–S fuzzy model (TSFM) based wind power generation systems (WPGSs). Firstly, the stochastic coupled leakage time-varying delays (CLTVDs) and randomly occurring uncertainty parameters (ROUPs) are firstly introduced for constructing more general TSFM. Second, on basis of the time-delay-product function (TDPF) and looped function strategy, a relaxed Lyapunov–Krasovskii functional (LKF) with the negative definite term and the time-varying matrix is developed, which can get the utmost out of the information of various communication delays. Third, by utilizing the tighter integral inequalities and reciprocally convex combination technique (RCCT), new stabilization criteria are established in terms of the linear matrix inequalities (LMIs). Simultaneously, the desired fuzzy sampled-data control (FSDC) is designed under the state quantization mechanism. Finally, a simulation example is presented to validate the efficiency of the proposed result.     

Dynamic output-feedback control for nonlinear continuous-time systems based on parametric uncertain subsystem and interval type-2 fuzzy model

This paper addresses the interval type-2 fuzzy robust dynamic output-feedback control problem for a class of nonlinear continuous-time systems with parametric uncertainties and immeasurable premise variables. First, the parametric uncertainties are assumed to be a subsystem based on the control input matrix and output matrix, and described as a linear fractional. Secondly, the nonlinear continuous-time systems are described by the interval type-2 fuzzy model. Thirdly, the new dynamic output feedback controller is designed based on the interval type-2 fuzzy model and the linear fractional (parametric uncertainties), the sufficient conditions for robust stabilization are given in the form of linear matrix inequalities (LMIs). Compared with previous work, the developed methods not only have abilities to handle the fuzzy system with immeasurable premise variables but also can deal with the parametric uncertainties effectively. The results are further extended to a mobile robot case and a chemical process case. Finally, two simulation examples are performed to show the effectiveness of the propose methods.     

Advanced controller synthesis for fuzzy parameter varying systems

A novel nonlinear time-varying model termed as the fuzzy parameter varying (FPV) system is proposed in this research, which inherits both advantages of the conventional T-S fuzzy system in dealing with nonlinear plants and strengths of the linear parameter varying (LPV) system in handling time-varying features. It is, therefore, an attractive mathematical model to efficiently approximate a nonlinear time-varying plant or to serve as a type of time-varying controller. Using the full block S-procedure, sufficient stability conditions have been derived in the form of linear matrix inequalities (LMIs) to test quadratic stability of the open-loop FPV system. Moreover, sufficient conditions have been derived on synthesizing both state feedback and dynamical output feedback fuzzy gain-scheduling controllers that can stabilize the FPV system. An inverted pendulum with a variable length pole is utilized to demonstrate advantages of the FPV system compared to the conventional T-S fuzzy system in representing a practical time-varying nonlinear plant and to validate the controller synthesis conditions.