Fuzzy Dynamic Output Feedback Controller Research Articles

Dynamic PDC and HMM-based asynchronous output feedback strict dissipative control for nonlinear singular incomplete jumping systems with actuator saturation

This paper investigates the asynchronous output feedback strict dissipative control for nonlinear singular incomplete jumping systems with actuator saturation via dynamic parallel distributed compensation technique and hidden Markov model mechanism. Dynamic parallel distributed compensation technique is used to design the asynchronous fuzzy dynamic output feedback controller and hidden Markov model is employed to describe the asynchronous phenomenon between the singular Markov jump system modes and the dynamic output feedback controller modes. Novel conditions of stochastic admissibility and strict dissipativity for the fuzzy closed-loop singular Markov jump systems are derived based on singular value decomposition technique and improved L-K functional. The asynchronous dynamic output feedback controller gains are developed in terms of linear matrix inequalities and the minimization optimization scheme is proposed by established ellipsoid. Single-link robot arm simulation results illustrate the practicability and effectiveness of the proposed methods.

Improved Nonlinear Extended Observer Based Adaptive Fuzzy Output Feedback Control for a Class of Uncertain Nonlinear Systems With Unknown Input Hysteresis

This study focuses on the problem of adaptive fuzzy dynamic surface output feedback control for a class of uncertain nonlinear systems subjected to unknown input hysteresis. A Prandtl–Ishlinskii (PI) model is applied to the uncertain nonlinear system for describing the unknown input hysteresis, making the controller design feasible. In addition, a nonlinear extended state observer (NESO) is designed for simultaneously estimating the unmeasurable states and generalized disturbances, including the nonlinear hysteresis term of the PI model and external disturbances. In addition, a novel nonlinear function is designed to replace the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$fal(\cdot)$</tex-math></inline-formula> function of the general NESO to address a modification that increases the convergence speed. Considering the incorporation of the improved nonlinear extended state observer (INESO), an adaptive output feedback control scheme is proposed based on fuzzy logic system and dynamic surface techniques. A command filter is employed to avoid the “explosion of complexity” problem inherent in the backstepping technique, while compensating the filtering error caused by adopting the filter. The Lyapunov approach is used to demonstrate the stability of the entire closed-loop system. Experiments regarding a piezoelectric micro–positioning stage are conducted, the results of which illustrate that the proposed adaptive fuzzy output feedback control method can guarantee a satisfactory tracking performance.

Adaptive Event-Triggered Interval Type-2 T-S Fuzzy Control for Lateral Dynamic Stabilization of AEVs With Intermittent Measurements and Actuator Failure

This article presents an adaptive event-triggered dynamic output feedback interval type-2 (IT-2) T-S fuzzy control method for autonomous electric vehicle systems. First, the IT-2 T-S fuzzy model is introduced to describe the nonlinear lateral dynamics of the vehicle systems. Second, a novel adaptive event-triggered strategy is designed to reduce the computational burden. Third, the phenomenon of intermittent measurements is depicted by the Bernoulli random distributed process, and the failure of the actuator is also included. According to the Lyapunov stability theory, an IT-2 T-S fuzzy dynamic output feedback controller (DOFC) is presented to ensure the random stability and performance of the vehicle systems. Finally, the effectiveness and real-time performance of the proposed control strategy are verified via numerical simulation and a hardware-in-the-loop (HIL) test platform.

Dynamic event-triggered security control for networked T-S fuzzy system with non-uniform sampling

This paper is focused on the security control problem for the dynamic event-triggered networked T-S fuzzy control system with non-uniform sampling and stochastic network attacks. Different from existing research, the signals from sensor are sampled in a non-uniform period. To improve communication, a novel dynamic event-triggered method is proposed, which can adjust the trigger parameters dynamically according to the changes of external output. Then, a T-S fuzzy dynamic output feedback control model with event-triggered mechanism and network attacks is constructed. Furthermore, by introducing a set of slack matrix, the asynchronous premise variable problem caused by event-triggered method is solved, and some sufficient conditions that insure the asymptotic stability with an H∞ performance requirement of the established closed-loop system can be obtained by utilizing Lyapunov function method and stochastic analysis technique. Moreover, the gains of the fuzzy dynamic output feedback controllers are found by solving the linear matrix inequalities (LMIs). Finally, two practical examples are given to support the merits and effectiveness of the proposed method.

Dynamic-output-feedback based interval type-2 fuzzy control for nonlinear active suspension systems with actuator saturation and delay

This paper proposes a fuzzy dynamic output feedback (DOF) controller for uncertain nonlinear active suspension systems (ASSs) with actuator saturation and time-varying delay. Firstly, given the time-delay and nonlinear characteristics of the suspension systems, an interval type-2 (IT-2) Takagi-Sugeno (T-S) fuzzy model is introduced to characterize the uncertain nonlinear ASSs with actuator saturation. Secondly, with the Lyapunov-Krasovskii function and the reciprocally convex technique, a series of sufficient delay-dependent conditions are derived to make sure that the control system with optimized H∞ performance and mechanical constraints is asymptotically stable. Thirdly, a DOF controller is designed to estimate the unmeasurable parameters of the system. Finally, the performance evaluation of the proposed controller is conducted through numerical and experimental tests.

Designing an Optimal Reset Controller for TS Fuzzy Systems

This study considers the problem of designing a reset dynamic output feedback controller (R-DOFC) for continuous-time nonlinear dynamics modeled by a Takagi-Sugeno (TS) fuzzy form. The exponential convergence of the closed-loop system state trajectories to the equilibrium point is satisfied by designing the fuzzy dynamic output feedback controller (DOFC) without reset action via the linear matrix inequality (LMI) technique. After that, by developing an optimization problem, the after-reset value is designed by using system output measurements at each reset time. In this approach, a genetic algorithm is adopted to minimize the proposed cost function of certain transient performances to achieve the best reset time instants. Moreover, sufficient conditions for choosing the DOFC after-reset value are formulated in the form of LMIs. The proposed reset fuzzy DOFC is applied to two nonlinear systems. The merits of the proposed reset DOFC are demonstrated by comparing the obtained results with those of other approaches.

Fuzzy dynamic output feedback control for nonlinear networked multirate sampled-data systems: An integral inequality method

This paper is devoted to fuzzy dynamic output feedback control for nonlinear networked multirate sampled-data systems based on T-S fuzzy systems. Using asynchronous multirate sampled-data, a multirate fuzzy controller is designed. The resultant closed-loop system is modeled as a perturbed system with two perturbed terms which include multirate sampling and the asynchronous membership functions between the controlled plant and the controller. A novel refined integral inequality is developed, and it improves Jensen's inequality and extends Wirtinger's inequalities by considering the sawtooth structure of time-varying delays. By applying the inequality to the perturbed system and constructing a new storage function, a stability criterion and two fuzzy dynamic output feedback controller design methods are presented for the nonlinear networked multirate sampled-data systems. Finally, three illustrative examples show the effectiveness of the proposed method.

Analysis and Design of Photovoltaic Nonlinear System: A Delta Operator Fuzzy Control Scheme

Aims: The paper is concerned with the problem of robust H∞ output feedback control for photovoltaic nonlinear system. Background: The PV systems are built to transform sun irradiance into electrical power. The dc-dc converters, such as buck type, boost type, and buck-boost type, have been widely implemented in the PV systems. Linear controllers for dc-dc converters are often designed based on mathematical models. To get a desired performance objective, an accurate model is essential. Objective: There has been increasing interest in the scheme of digital controller design for dc-dc converters. However, most of the research efforts are focused on the representation based on the standard forward-shift operator approach, which are of inherently ill-conditioned when datum are taken at high sampling rates. Compared with the forward-shift operator, the delta operator has many virtues which can be applied as a better representation of the underlying physical model under high sampling rates. Despite the delta operator possessing the superior high sample rate performance has been recognized in the past two decades, there exists little literature discussing the analysis and synthesis of photovoltaic nonlinear systems by using delta operator fuzzy control method, which motivates us to make an effort in this topic. Methods: We propose a Fuzzy Dynamic Output Feedback (FDOF) controller, and introduce a novel Lyapunov-Krasovskii Functional (LKF) in delta domain, the framework of robust H∞ output feedback control is investigated. Results: Sufficient conditions are derived for the existence of the desired FDOF controllers in terms of Linear-Matrix Inequalities (LMIs). A numerical example is used to illustrate the design procedure of the present method. Conclusion: This paper has studied the problems of robust H∞ output feedback control for photovoltaic nonlinear system with interval time-varying delay and parametric uncertainties. Based on the formulated fuzzy system and the FDOF controller, we introduced a Lyapunov-Krasovskii function in delta domain, the scheme of FDOF was proposed. Sufficient conditions for the existence of the FDOF controller were derived in terms of LMIs. A numerical example was used to demonstrate the effectiveness of our proposed methods.

Event-triggered output-based control of T-S fuzzy systems under quantisation, actuator saturation and cyber attacks

This paper studies output-based event-triggered security control of networked T-S fuzzy systems under signal quantisation, actuator saturation and deception attacks governed by a Bernoulli distribution. Firstly, using periodically sampled output of a T-S fuzzy system, a discrete event-triggered mechanism (ETM) is introduced to save network bandwidth, which excludes Zeno behaviour absolutely. Secondly, a closed-loop system model is built, which integrates parameters of the T-S fuzzy plant, the ETM, quantiser, actuator saturation, stochastic attacks, network-induced delays and fuzzy dynamic output feedback controller in a unified framework. Thirdly, sufficient conditions for asymptotic stability of the T-S fuzzy system are obtained, and further a fuzzy output-based security controller is designed. Finally, examples confirm effectiveness of the proposed methods.

RobustH∞output feedback control for type‐2Takagi‐Sugenofuzzy systems with multiple time‐delays and disturbances: A descriptor redundancy approach

AbstractTheH∞stability analysis and interval type‐2 Takagi‐Sugeno (T‐S) fuzzy control is studied for a class of interval type‐2 T‐S fuzzy systems. Firstly, the interval type‐2 T‐S fuzzy model is employed to approximate the system plant. Secondly, the delay‐dependent interval type‐2 T‐S fuzzy dynamic output feedback controller is designed. Thirdly, two classes of stability conditions in terms of linear matrix inequalities (LMIs) are derived, and the closed‐loop system is asymptotically stable and prescribedH∞performance is achieved. The delay‐dependent interval type‐2 T‐S fuzzy dynamic output feedback controller is designed to relax the control design conditions. The descriptor redundancy method is employed for avoiding the crossing vectors between the system gain matrices and controller gain matrices. The delay‐dependent Lyapunov functional with descriptor redundancy matrix is introduced, and the upper and lower membership functions information is considered. Some slack matrices are introduced via the upper and lower membership functions information to solve the obtained LMIs. Finally, simulation examples are performed to show the effectiveness of the proposed methods.

Dynamic output feedback control for interval type-2 fuzzy systems against DoS attacks and sensor failures

This article focuses on investigating a dynamic output feedback control issue for uncertain nonlinear networked control systems (NCSs) in the presence of Denial-of-Service (DoS) attacks and sensor failures. By using the low and upper membership functions (LUMFs) of interval type-2 (IT2) Takagi-Sugeno (T-S) fuzzy model, the uncertainties existing in the considered NCSs are depicted effectively. Based on the IT2 fuzzy system, a switching fuzzy model is further established to correspond to different DoS attack scenarios. According to the average dwell-time approach and Lyapunov stability theory, an IT2 fuzzy dynamic output feedback control scheme is proposed so that the exponential stability of the considered NCSs can be achieved regardless of DoS attacks and sensor failures. Lastly, illustrative examples are presented to confirm the theoretical results proposed in this paper.

ISS control synthesis of T–S fuzzy systems with multiple transmission channels under denial of service

This paper investigates the input-to-state stabilizing (ISS) problem for Takagi–Sugeno (T–S) fuzzy systems with multiple transmission channels under denial-of-service (DoS) attacks. To achieve ISS, time-triggered data update logics on different channels are determined by linear matrix inequalities (LMIs). Under DoS attacks, a switched fuzzy dynamic output feedback controller which takes the security of premise variables into consideration is constructed. A novel time division mechanism is proposed to deal with the uncertainties caused by DoS attacks at different time periods. The proposed mechanism considers all cases of DoS attacks, which is more general compared to the existing method. Then, sufficient conditions are given to ensure the ISS of T–S fuzzy systems under DoS attacks. Finally, two examples are given to illustrate the effectiveness and merits of the proposed method.

Adaptive event-triggered dynamic output feedback H ∞ control for networked T-S fuzzy systems

This paper investigates the design problem of fuzzy dynamic output feedback controller for nonlinear networked systems via mismatched membership functions and adaptive event-triggered (AET) mechanism. Firstly, an AET mechanism is introduced to save communication resources, which causes the controller and the original system's premise variables to be asynchronous. Then, considering the influence of AET and mismatched membership functions, a model of fuzzy control system is established. In addition, utilizing the Lyapunov-Krasovskii(L-K) functional, sufficient conditions for the global exponential stability of the closed-loop system with performance are derived. Besides, the controller parameters and event-triggered (ET) weight matrix are solved by a set of linear matrix inequalities (LMIs). Finally, an example is given to demonstrate the effectiveness of the proposed control method.

Stability analysis and output feedback control for stochastic networked systems with multiple communication delays and nonlinearities using fuzzy control technique

This paper addresses the H-infinity Takagi-Sugeno (T-S) fuzzy control for a class of T-S fuzzy discrete networked control systems with random interval communication delays and random sector nonlinearities. Firstly, the T-S fuzzy model is employed to approximate the discrete networked control system and the ℓth-order Rice fading channels model is introduced in the system model. Secondly, the T-S fuzzy dynamic output feedback controller with ℓth-order Rice fading channels output is designed for the T-S fuzzy discrete networked control system. Thirdly, the discrete delay-dependent Lyapunov-Krasovskii functional, stochastic system theory and Bernoulli probability distribution are employed to derive the stability conditions in terms of linear matrix inequalities (LMIs). Compared with previous works, the fading channels in the signal transmission are described clearly by setting the different channels coefficients of the ℓth-order Rice fading channels model. The closed-loop system is exponentially mean-square stable and prescribed H-infinity performance is guaranteed by designing the T-S fuzzy dynamic output feedback controller. The factorizations in the polynomial and the congruence transformation matrices are introduced to solve the LMIs, such that the controller gain matrices are determined. Finally, simulation examples are presented to show the effectiveness of proposed methods.

Tracking control of a class of nonlinear systems with output delay based on adaptive fuzzy dynamic surface control

ABSTRACTThis paper concerns with the tracking control problem of a class of unknown nonlinear time-delay systems in the presence of output delay and inaccessible states. To deal with the difficulties arising from unmeasurable states, a fuzzy logic observer based on delayed outputs is firstly employed. Then, based on the delayed output, observed states and filtered virtual control signals, proper change of coordinates is defined for the purpose of designing dynamic surface control. By introducing appropriate Lyapunov-Krasovskii functionals in the design procedures, a controller and adaptation laws are obtained for the control strategy of nonlinear systems subject to output delay. Moreover, by selecting design parameters and matrices based on the acquired stability criteria, it is proved that the proposed adaptive fuzzy dynamic surface output feedback control approach is able to guarantee the uniformly ultimately boundedness of all the signals in the closed loop unknown nonlinear output-delay systems. Finally, the theoretic achievements are applied to three well-known benchmark systems to illustrate the effectiveness and efficiency of the proposed approach.

H-infinity stability analysis and output feedback control for fuzzy stochastic networked control systems with time-varying communication delays and multipath packet dropouts

The H-infinity stability analysis and delay-dependent Takagi–Sugeno (T–S) fuzzy dynamic output feedback control are proposed for the T–S fuzzy discrete networked control systems with time-varying communication delay and multipath packet dropouts. T–S fuzzy model is employed to approximate the discrete networked control system with time-varying state delay and external disturbance. Stochastic system theory and Bernoulli probability distribution are employed to describe the time-varying communication delay and multipath packet dropouts. Delay-dependent T–S fuzzy dynamic output feedback controller is designed. The delay-dependent T–S fuzzy dynamic output feedback controller is employed to relax the design conditions and enhance the design flexibility. The delay-dependent Lyapunov–Krasovskii functional, stochastic system theory and Bernoulli probability distribution are introduced to guarantee the stochastic mean-square stability and prescribed H-infinity performance. Some slack matrices are introduced to reduce the computation complexity. Finally, simulation examples are presented to show the effectiveness and advantages of the proposed methods.

Robust H∞ dynamic output feedback control for interval type-2 T-S fuzzy multiple time-varying delays systems with external disturbance

This research focuses on the H∞ stability analysis and fuzzy dynamic output feedback control for a class of interval type-2 T-S fuzzy systems. Interval type-2 T-S fuzzy model is employed to approximate the uncertain system with multiple time-varying delays and external disturbance. Interval type-2 T-S fuzzy dynamic output feedback controller is designed by employing the interval type-2 T-S fuzzy model. Some stability criterions in terms of linear matrix inequalities (LMIs) are presented by introducing the fuzzy Lyapunov function. The closed-loop system is described as a descriptor system by employing the descriptor redundancy approach. Some less conservative stability criterions un-including the product terms between system gains and controller gains are presented and the fuzzy-basis-dependent matrix with system gains transformation is introduced. The stability criterions are extended to a finite set of LMIs constraints. Finally, simulation examples and comparison figures are presented to show the effectiveness of the proposed approach.

Adaptive Event-Triggered Output Feedback Fuzzy Control for Nonlinear Networked Systems With Packet Dropouts and Actuator Failure

This paper studies the problem of adaptive eventtriggered dynamic output feedback fuzzy control for nonlinear networked control systems. Two crucial factors, packet dropouts and actuator failure, are taken into consideration simultaneously. Takagi-Sugeno fuzzy model is introduced to describe considered systems. The Bernoulli random distribution process is employed to depict the phenomenon of data missing. The actuator failure model is adopted to depict actuator failure. An innovative adaptive event-triggered strategy is built to save computational resource. In the light of Lyapunov stability theory, a fuzzy dynamic output feedback controller is designed to guarantee the stochastic stability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance for considered systems. Finally, simulation results are provided to demonstrate the usefulness of the proposed control strategy.

Stability analysis and dynamic output feedback controller design of T–S fuzzy systems with time-varying delays and external disturbances

This paper investigates the stability analysis and Takagi–Sugeno (T–S) fuzzy dynamic output feedback control for a class of T–S fuzzy systems with multiple time-varying delays and unmatched disturbances. Firstly, the T–S fuzzy model is employed to represent the system based on the system input matrix and output matrix. Secondly, the T–S fuzzy dynamic output feedback controller is designed based on the T–S fuzzy model. Thirdly, the line-integral fuzzy Lyapunov functional is employed and the boundary information of membership functions is considered in the stability analysis. Compared with previous works, the multiple time-varying delays and unmatched disturbances are considered in the T–S fuzzy system. The T–S fuzzy dynamic output feedback controller and T–S fuzzy system employ the same number of fuzzy rules but different membership functions to relax the control design conditions. The line-integral fuzzy Lyapunov functional is employed and the boundary information of membership functions is considered to obtain the less conservative stability conditions. Finally, two simulation examples are performed and some comparison figures/results are presented to show the effectiveness and advantage of proposed method, respectively.

Event-Triggered Dynamic Output Feedback Control for Networked T-S Fuzzy Systems With Asynchronous Premise Variables

This paper investigates the problem of event-triggered dynamic output feedback control for networked Takagi-Sugeno (T-S) fuzzy systems with asynchronous premise variables. Our attention is focused on the design of an event-triggered fuzzy dynamic output feedback controller that guarantees that the closed-loop system is asymptotically stable. First, with consideration of the limited bandwidth and restricted network resource, an event-triggered communication scheme is proposed to save the limited network resource. Second, different from the existing results in the literature, a fuzzy dynamic output feedback controller with asynchronous premise variables is constructed such that the premise membership functions are not necessarily the same as the networked T-S fuzzy systems. Then, by using the Wirtinger inequality and some slack matrices, a less conservative stability and stabilization conditions for the existence of fuzzy dynamic output feedback controller are derived in the form of linear matrix inequalities, which can be solved by the standard MATLAB toolbox. Finally, an example is given to demonstrate the effectiveness of the designed event-triggered fuzzy dynamic output feedback controller.