Fuzzy Output Feedback Control Research Articles

Observer-Based Adaptive Fuzzy Output Feedback Control for a Class of Fractional-Order Nonlinear Systems with Full-State Constraints

Observer-Based Adaptive Fuzzy Output Feedback Control for a Class of Fractional-Order Nonlinear Systems with Full-State Constraints

Finite-time event-triggered output feedback [formula omitted] control for nonlinear systems via interval type-2 Takagi-Sugeno fuzzy systems

The finite-time event-triggered H∞ fuzzy output feedback control problem is investigated in this paper for a class of nonlinear systems. The considered nonlinear system is first modeled by an interval type-2 Takagi-Sugeno (IT2 T-S) fuzzy system with the modeling errors. A state observer and an event-triggered mechanism are then designed by using the sampled estimating states and measured output signals. Based on the designed state observer and event-triggered mechanism, an observer-based finite-time event-triggered H∞ fuzzy controller is developed. The sufficient conditions of guaranteeing the finite-time stability of the addressed system are established in the framework of linear matrix inequalities (LMIs). Furthermore, a computational algorithm of solving observer and controller gain matrices is given in terms of the established sufficient conditions. Finally, a practical simulation example is provided to demonstrate the effectiveness of the obtained theoretical results.

Adaptive fuzzy output feedback controller design for a HAGC system with input saturation and output error constraints

The comprehensive effect of external disturbance, measurement delay, unmeasurable states and input saturation makes the difficulties and challenges for a HAGC system. In this paper, an adaptive fuzzy output feedback control scheme is designed for a HAGC system under the simultaneous consideration of those factors. At the first place, by state transformation technique, the dynamic model of a HAGC system is simply expressed as a strict feedback form, where measurement delay is converted into input delay. Then, an auxiliary system is employed to compensate for the effect of input delay. Furthermore, an asymmetric barrier Lyapunov function (BLF) is constructed to ensure the output error constraint requirement of thickness error and the fuzzy observer is established to solve unmeasurable states, unknown nonlinear functions at the same time. With the aid of backstepping method, adaptive fuzzy controller is developed to assure that the closed-loop system is semi-globally boundedness and the output error of thickness error doesn’t violate its constraint. At the end, compared simulations are carried out to verify the efficiency of the proposed control scheme.

Adaptive fuzzy output-feedback event-triggered control for fractional-order nonlinear system.

This paper studies the issue of adaptive fuzzy output-feedback event-triggered control (ETC) for a fractional-order nonlinear system (FONS). The considered fractional-order system is subject to unmeasurable states. Fuzzy-logic systems (FLSs) are used to approximate unknown nonlinear functions, and a fuzzy state observer is founded to estimate the unmeasurable states. By constructing appropriate Lyapunov functions and utilizing the backstepping dynamic surface control (DSC) design technique, an adaptive fuzzy output-feedback ETC scheme is developed to reduce the usage of communication resources. It is proved that the controlled fractional-order system is stable, the tracking and observer errors are able to converge to a neighborhood of zero, and the Zeno phenomenon is excluded. A simulation example is given to verify the availability of the proposed ETC algorithm.

Command Filter-Based Adaptive Fuzzy Finite-Time Output Feedback Control of Nonlinear Electrohydraulic Servo System

In this paper, the command filter-based adaptive fuzzy finite-time output feedback control (FOFC) is investigated for the Electro-hydraulic servo system. For the uncertainties in the system, we utilize the fuzzy logic systems (FLSs) to estimate these uncertain nonlinearities and fuzzy state observer is established to approximate the unmeasurable hydraulic cylinder stem speed and the internal cylinder force. Then, a command filter-based finite time output feedback control is proposed to achieve high tracking precision, where the tracking errors can be regulated into a small neighborhood around the equilibrium proved by the Lyapunov finite-time stability theory. Moreover, a command filter is introduced to avoid the explosion of complexity in the backstepping procedure, where a compensation mechanism is developed to compensate for filter errors. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control.

Observer-based adaptive fuzzy output feedback control for functional constraint systems with dead-zone input.

This paper develops an adaptive output feedback control for a class of functional constraint systems with unmeasurable states and unknown dead zone input. The constraint is a series of functions closely linked to state variables and time, which is not achieved in current research results and is more general in practical systems. Furthermore, a fuzzy approximator based adaptive backstepping algorithm is designed and an adaptive state observer with time-varying functional constraints (TFC) is constructed to estimate the unmeasurable states of the control system. Relying on the relevant knowledge of dead zone slopes, the issue of non-smooth dead-zone input is successfully solved. The time-varying integral barrier Lyapunov functions (iBLFs) are employed to guarantee that the states of the system remain within the constraint interval. By Lyapunov stability theory, the adopted control approach can ensure the stability of the system. Finally, the feasibility of the considered method is conformed via a simulation experiment.

Formula omitted] output feedback control for fractional-order T-S fuzzy model with time-delay

This paper addresses H∞ observer-based control issue for fractional-order uncertain Takagi-Sugeno (T-S) fuzzy model with unknown input and time-delay in the case of system order in (0,1). In order to construct the state estimation variables, reduced-order fuzzy observer is devised. By utilizing Lyapunov method of fractional-order derivative, the sufficient conditions are provided to ensure the effectiveness of proposed reduced-order unknown input observer and the stabilization of augmented T-S fuzzy model with an H∞-norm σ. The conditions are shown in terms of linear matrix inequalities (LMIs) and the matrices of unknown input fuzzy observer are computed by relevant LMIs. Furthermore, by solving LMIs, the T-S fuzzy output feedback control is realized. Finally, a numerical example and a single-link robot arm example are simulated to illustrate the validity of the addressed strategy.

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.

Fuzzy adaptive output-feedback tracking control for nonlinear strict-feedback systems in prescribed finite time

The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form. Under the situation of system states being unavailable, the system output is used to set up the state observer to estimate the real system states. Furthermore, the estimation states are employed to design controller. During the control design process, fuzzy logic systems (FLSs) are used to model the unknown nonlinearities. A novel observer-based finite-time tracking control scheme is proposed via fuzzy adaptive backstepping and barrier Lyapunov function approach. The suggested fuzzy adaptive output feedback controller can force the output tracking error to meet the pre-specified accuracy in a fixed time. Meanwhile, all the closed-loop variables are bounded. Compared to some existing finite-time output feedback control schemes, the developed control strategy guarantees that the settling time and the error accuracy are independent of the uncertainties and can be specified by the designer. At last, the effectiveness and feasibility of the proposed control scheme are demonstrated by two simulation examples.

Fuzzy adaptive finite-time output feedback control of stochastic nonlinear systems

An adaptive finite-time approach to the feedback control of stochastic nonlinear systems is presented. The fuzzy logic system (FLS) and a state observer are used to estimate the uncertain function and unmeasured state of the controlled system, respectively. A dynamic surface control (DSC) scheme is employed to deal with the “computational explosion” problem, which is inherent in traditional backstepping methods since the repetitive calculation of the derivatives of virtual control signals is avoided. A new output feedback controller is developed to guarantee that all the signals of the controlled system are bounded within a finite time range and the tracking deviation can converge to an arbitrarily small residual set within finite time. Simulations confirm the analytical and theoretical results of the presented algorithm.

Output feedback fuzzy control of nonlinear dynamic systems: Event‐triggered case

AbstractThe event‐triggered output feedback controller design problem is investigated in this article for a class of discrete‐time Takagi–Sugeno fuzzy systems. We focus on constructing a closed‐loop system by considering the event generator communication mechanism, interval time‐varying delays, and packet dropouts. Under this newly established system, a less conservative stability condition is obtained using the Wirtinger‐based inequality and reciprocally convex approach, which guarantees that the corresponding augmented system is asymptotically stable in the mean‐squared sense with a prespecified – performance. The solution of the designed output feedback controller parameters can then be obtained by variable substitution method and by conversion of the controller parameters. Finally, two examples are presented to demonstrate the effectiveness of the proposed controller design technique.

Adaptive Fuzzy Output-Feedback Control Design for a Class of p-Norm Stochastic Nonlinear Systems With Output Constraints

This paper considers the control problem of p-norm stochastic nonlinear systems with output constraints, while the system nonlinearities are completely unknown and the system states are unavailable except the output. A nonlinear observer is constructed to estimate the unmeasurable states. Then, based on the constructed observer and a tan-type barrier Lyapunov function (BLF), an adaptive fuzzy output-feedback control strategy is developed by combining the technique of adding a power integrator with the fuzzy logic systems (FLSs). The proposed scheme enables that all the signals of the considered closed-loop systems are bounded in probability while the prespecified output constraint is not violated. Finally, a numerical example verifies the validation of the proposed scheme.

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.

Observer-Based Event-Triggered Adaptive Fuzzy Control for Unmeasured Stochastic Nonlinear Systems With Unknown Control Directions.

The issue of adaptive output-feedback stabilization is investigated for a category of stochastic nonstrict-feedback nonlinear systems subject to unmeasured state and unknown control directions. By combining the event-triggered mechanism and backstepping technology, an adaptive fuzzy output-feedback controller is devised. In order to make the controller design feasible, a linear state transformation is introduced into the initial system. At the same time, the Nussbaum function technology is used to overcome the difficulties caused by unknown control directions, and the state observer solves the problem of the unmeasured state. Based on the fuzzy-logic system and its structural characteristics, the issue of unknown nonlinear function with nonstrict-feedback structure in the system is tackled. The designed controller could not only guarantee all signals of closed-loop systems are bounded in probability but also save communication resources effectively. Finally, numerical simulation and ship dynamics example are given to confirm the effectiveness of the proposed method.

Fuzzy adaptive event-triggered output feedback control for nonlinear systems with tracking error constrained and unknown dead-zone

ABSTRACT In this paper, an adaptive fuzzy event-triggered output feedback control scheme is studied for a class of non-strict feedback systems with tracking error constrained and unknown dead-zone. Fuzzy logical systems (FLSs) are employed to solve the uncertainties of the controlled plant, and the immeasurable states are estimated by employing the fuzzy observer. In the designed observer, to compensate for the effect of unknown dead-zone by invoking the known designed event-triggered input signal, an adaptive parameter is designed. Furthermore, due to event-triggered control (ETC) places a great burden on the computing space, the dynamic surface control (DSC) technique is used to solve the problem of ‘explosion of complexity’ in each step, and the simplified barrier Lyapunov function (SBLF) is utilised to restrict the tracking error within the prescribed boundaries. Consequently, the designed parameter adaptive laws and event-triggered controller can ensure that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB). Ultimately, two numerical simulation examples are provided to illustrate the effectiveness of the proposed event-triggered control theory.

State and Output Feedback Controller Design of Takagi-Sugeno Fuzzy Singular Fractional Order Systems

This paper investigates the admissibility issue of a class of singular fractional order nonlinear systems based on Takagi-Sugeno (T-S) fuzzy model. First, the fuzzy model and the state and output feedback controllers share the different membership functions. Then, we propose the methods about designing the fuzzy state and output feedback controllers, which guarantee the asymptotical stability of closed-loop systems. Next, the equality constraint existing in most of admissibility theorems is eliminated and strict linear matrix inequalities (LMIs) are obtained. Finally, two numerical simulation examples are given to illustrate the effectiveness of the proposed methods.

Observer-Based Adaptive Hybrid Fuzzy Resilient Control for Fractional-Order Nonlinear Systems With Time-Varying Delays and Actuator Failures

This article investigates the adaptive output feedback resilient control problem for a class of incommensurate fractional-order (FO) nonlinear systems in the presence of time-varying delays and actuator faults by combining with an adaptive backstepping technique and a modified FO dynamic surface control (FODSC) method. Considering that the information of system states is not fully available, a hybrid fuzzy observer is designed to estimate the unmeasurable system states, where the neuro-fuzzy network system is introduced to handle the unknown nonlinear functions existing in the system. Furthermore, in order to overcome the problem of the explosion of complexity caused by traditional backstepping design procedure, an FO filter is constructed to pass the virtual control signal based on the FODSC scheme. Moreover, according to an indirect Lyapunov stability method, an adaptive hybrid fuzzy output feedback controller is designed to guarantee that all the signals of the closed-loop systems are bounded. Finally, three examples are given to verify the validity and superiority of the presented control scheme.

Observer-Based Finite-Time Adaptive Fuzzy Control for Nontriangular Nonlinear Systems With Full-State Constraints.

This article focuses on finite-time adaptive fuzzy output-feedback control for a class of nontriangular nonlinear systems with full-state constraints and unmeasurable states. Fuzzy-logic systems and the fuzzy state observer are employed to approximate uncertain nonlinear functions and estimate the unmeasured states, respectively. In order to solve the algebraic loop problem generated by the nontriangular structure, a variable separation approach based on the property of the fuzzy basis function is utilized. The barrier Lyapunov function is incorporated into each step of backstepping, and the condition of the state constraint is satisfied. The dynamic surface technique with an auxiliary first-order linear filter is applied to avoid the problem of an "explosion of complexity." Based on the finite-time stability theory, an adaptive fuzzy controller is constructed to guarantee that all signals in the closed-loop system are bounded, the tracking error converges to a small neighborhood of the origin in a finite time, and all states are ensured to remain in the predefined sets. Finally, the simulation results reveal the effectiveness of the proposed control design.

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.

Reachable set bounding of output-feedback control for discrete-time large-scale IT-2 fuzzy descriptor systems using distributed event-based broadcasts

This paper studies the distributed event-based broadcasting of output-feedback control for discrete-time large-scale fuzzy descriptor systems subject to reachable set bounding. First, each nonlinear subsystem is represented by the interval type-2 fuzzy model, where fuzzy representation is assumed to be appearing not only in both the state and input matrices but also in the derivative matrix. By using a descriptor redundancy approach, the fuzzy representation in the derivative matrix is reformulated into the linear one. Then, we introduce an output-feedback fuzzy controller with distributed event-based broadcasting, where all subsystems communicate with each other via a distributed network, and each subsystem broadcasts its decision-making of transmission based on a prescribed event. Two event-based mechanisms (EBMs) are respectively proposed to examine when the system output and fuzzy premise variable should be transmitted to the controller. Moreover, by further employing a descriptor redundancy representation, combined with reachable set analysis method, it will be shown that the proposed fuzzy controller guarantees that the estimation error is bounded within the ellipsoidal boundary while communication data are transmitted to the controller as little as possible, and sufficient condition for designing the desired controller is derived in terms of linear matrix inequalities (LMIs). Finally, a simulation study is given to show the effectiveness of the proposed method.