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In this article, an adaptive fuzzy predefined time and accuracy tracking control scheme is proposed for strict-feedback nonlinear systems. A sufficient condition that can be used to determine whether the tracking error converges to a predefined region within a predefined time is first derived based on the definition of predefined time stability. Under the proposed stability criterion, an adaptive fuzzy controller is developed by applying the backstepping technique, and the stability time and convergence accuracy of the tracking error can be set previously, which facilitates the engineering application with requirements for convergence time and accuracy. Especially, to reduce chattering and decrease energy consumptions on the premise of ensuring the stability of the system, an inequality is introduced to construct a continuous term which can replace the sign function. Finally, a practical example is presented to illustrate the feasibility of main results. [ABSTRACT FROM AUTHOR]

In this article, an adaptive tracking control approach is developed for a class of strict-feedback nonlinear systems with time-varying full state constraints. As a breakthrough in this system, the special function constraints (whose constraint boundary is relevant to both state variables and time) are considered, which are rarely studied by research work. And there is no doubt that this method increases the complexity of designing this scheme. Furthermore, the time-varying integral barrier Lyapunov functions combining with backstepping technique is introduced to break the limitation of traditional methods as well as achieve the full state constraints. Meanwhile, fuzzy logic systems are selected to approximate unknown nonlinear functions. It is verified that all closed-loop signals are bounded and all states are forced in the time-varying boundness. In addition, the proposed control strategy has a good performance. The effectiveness of the theoretical analysis results is proved via a simulation example. [ABSTRACT FROM AUTHOR]

This article addresses fuzzy tracking control question when switched systems are subjected to unknown input backlash, nonconstant control gain, and asymmetric full-state constraints. A new mode-dependent integral barrier Lyapunov function (MIBLF) can handle conservative feasibility conditions that only assure asymmetric full-state constraints and all subsystems share a common controller. To handle unknown input backlash nonlinearities in the presence of unknown nonconstant control gain function, fuzzy logic systems are utilized and a new parameterized smooth backlash inverse (PSBI) is presented. It is hard to construct the barrier Lyapunov function-based controller in the presence of unknown backlash, switching framework, and full-state constraints. By employing the fuzzy logic systems and the PSBI, a novel MIBLF-based adaptive fuzzy controller is presented to overcome this challenge. Furthermore, the presented controller not only prevents violation of all constrained states, but also ensures the boundedness of the closed-loop system. Eventually, feasibility of achieved theoretical results can be proven by two examples. [ABSTRACT FROM AUTHOR]

This article investigates the nonfragile guaranteed cost (GC) control problem of discrete-time impulsive switched Takagi–Sugeno (T–S) fuzzy systems with input quantization and asynchronous switching. The model-dependent dynamic quantizers are applied to obtain the quantized input signal. To deeply study the GC performance analysis and GC control problems in the presence of quantization, asynchronous switching, and impulses, a novel piecewise cost function containing the quantized input instead of normal input is applied in this article. By using the mode-dependent average dwell time approach and introducing a class of Lyapunov-like functions allowing to increase during the asynchronous period, new sufficient conditions are established to guarantee the asymptotical stability with the GC performance index for the impulsive switched T–S fuzzy systems with quantized control input and asynchronous switching. Then, new design conditions about the nonfragile GC controllers and dynamic quantizers of impulsive switched T–S fuzzy systems are obtained in the form of linear matrix inequalities. Finally, a numerical example and a practical example are provided. [ABSTRACT FROM AUTHOR]

Tracking control of redundant and hyperredundant manipulators is a fundamental and critical problem in practical applications. In order to effectively decrease the end-effector position errors, a novel dual fuzzy-enhanced neurodynamic (DFEN) scheme is put forward for solving the position error accumulation problem followed by achieving accurate tracking control results. The proposed scheme is established based on a zeroing neurodynamic approach in conjunction with two fuzzy adjustment units that are capable of tuning the control parameters by monitoring the tracking error. Moreover, the DFEN scheme can effectively solve the tracking problem without requiring knowing a priori knowledge of the kinematic model of the robot. The convergence and the stability of the proposed approach are demonstrated by theoretical analysis. The effectiveness, accuracy, and robustness of the proposed DFEN scheme are verified on the simulative redundant manipulator, continuum robot, and hybrid robot (integrating the redundant manipulator and the continuum robot). A practical experiment is provided to validate the proposed scheme as well. [ABSTRACT FROM AUTHOR]

This article presents a hybrid metaheuristic optimization algorithm that combines particle filter (PF) and particle swarm optimization (PSO) algorithms. The new PF–PSO algorithm consists of two steps: the first generates randomly the particle population;and the second zooms the search domain. An application of this algorithm to the optimal tuning of proportional-integral-fuzzy controllers for the position control of a family of integral-type servo systems is then presented as a second contribution. The reduction in PF–PSO algorithm's cost function allows for reduced energy consumption of the fuzzy control system. A comparison with other metaheuristic algorithms on canonical test functions and experimental results are presented at the end of this article. [ABSTRACT FROM AUTHOR]

This article focuses on developing a static output feedback (SOF) control scheme for Takagi–Sugeno fuzzy systems. The proposed SOF controller does not share the same premise membership functions with the model, which permits enhancing the flexibility in controller design and implementation. By contrast with the state feedback case, the SOF control generally results in nonconvex design conditions. To circumvent this problem, we develop a successive convex optimization algorithm, which is based on solving a sequence of more tractable convex optimization problems obtained by approximating the nonconvex constraints with some convex ones. As a heuristic algorithm, the validity of the developed successive convex optimization algorithm is highly affected by initial conditions, and, recognizing this, we put forward an iterative procedure for determining the feasible initial condition. Finally, two illustrative examples are presented to validate the efficiency of the proposed algorithms. [ABSTRACT FROM AUTHOR]

To reduce the influence of controller uncertainties and lower the computational burden of the system, a novel nonfragile sampled-data control scheme is proposed in this article for the Tagaki–Sugeno fuzzy system with time delay. First, an improved Lyapunov–Krasovskii functional is established with adjusted looped functional, which contains not only the current states, but the delayed states. Then, utilizing the Wirtinger inequality and improved single integral inequality, the new stability criteria are proposed with less conservativeness. By calculating the solution of linear matrix inequalities, the nonfragile controller parameters can be acquired. Furthermore, the sampled-data fuzzy controller leads to a good stable performance for the system, even under the possible gain fluctuations. Finally, three examples are given to verify the effectiveness and superiority of the proposed control scheme. [ABSTRACT FROM AUTHOR]

This article presents a new sampled-data-based event-triggered pointwise security controller by pointwise measurements for partial differential equation (PDE) systems under stochastic cyberattacks. First, according to the Takagi–Sugeno fuzzy model, the considered nonlinear system is reconstructed and an event-triggered pointwise fuzzy controller is proposed with pointwise measurements. Moreover, networked control systems are introduced to improve the transmission convenience; however, two deception cyberattacks with different characteristics are brought into PDE systems for the first time. In addition, based on novel Lyapunov–Krasovskii functionals, some relaxed conditions to assure system’s exponential stability are established. Finally, the effectiveness and practicability of the designed controller are demonstrated by numerical and application examples. [ABSTRACT FROM AUTHOR]

The generation of self-sustaining oscillations at the output of nonlinear systems without tracking a reference signal is under investigation. In this study, we proposed an internal double fuzzy inference system to generate an asymptotically stable limit cycle or self-oscillations for the second-order systems. The fuzzy system has been synthesized by invoking the Poincaré–Bendixson theorem, which states sufficient and necessary conditions of existence of an attracting periodic orbit at the output of the closed-loop system. This theorem was also used for design; that is, we set the tuning rules of the fuzzy controller. The effectiveness of the proposed controller is corroborated by numerical simulations and experiments made in a single-link pendulum system. [ABSTRACT FROM AUTHOR]

This article addresses the state and fault estimation problems for a class of quantized Takagi–Sugeno (T-S) fuzzy systems with sensor and actuator faults. Two types of observer design methods are developed for two different network transmission environments. In the first case, the signal quantization effect is only considered on the channel between sensor and controller, and a sliding mode observer is designed, which can reconstruct the actuator faults. In the second case, the quantization effects are considered in both the sensor-controller side and the controller-actuator side, which is more difficult to be dealt with compared to the first case, and the sliding mode observer method cannot be effective now since the discontinuous term is difficult to be designed. A descriptor reduced-order observer is presented to solve this problem, where the jumping behavior that resulted from the signal quantization is considered in the observer, which is novel and effective to compensate the quantization effects. Finally, simulation examples of rigid-body satellite attitude control T-S fuzzy system are presented to verify the effectiveness of the proposed observer design approaches. [ABSTRACT FROM AUTHOR]

This article investigates the $\eta$ -exponential stabilization and positivity of the controlled discrete-time polynomial fuzzy model (DPFM) system with time delay. $\eta$ -exponential polynomial copositive Lyapunov candidate is proposed to detect the system stability under the convergence (decay) rate. Static output feedback fuzzy controller is then synthesized to assure the DPFM closed-loop system with time delay. We propose Chebyshev membership functions (CMFs) to approach the primary membership function and attenuate the conservativeness of $\eta$ -exponential stability formulation and positivity analysis. Chebyshev norm approximation error is utilized to introduce the error between CMFs and primary membership functions using slack matrices. A numerical example is presented to validate the proposed methods. [ABSTRACT FROM AUTHOR]

Uncertainty is a major concern in vehicle path tracking control design. The coefficients of the uncertainty bound are unknown. They are assumed to lie within prescribed fuzzy sets. First, based on the path tracking kinematic model, this article innovatively formulates the vehicle path tracking task as a constraint-following problem. Second, we put forward a deterministic adaptive robust control law with a tunable parameter to ensure the uniform boundedness and ultimate uniform boundedness of the closed-loop system. Third, an optimal scheme for the tunable parameter is proposed based on the fuzzy uncertainty. The resulting optimal robust control (ORC) minimizes a comprehensive fuzzy performance index that involves the fuzzy system performance and the control cost. The results of the CarSim-Simulink cosimulation and the hardware-in-loop experiment together show that the proposed ORC exhibits a superior path tracking performance. [ABSTRACT FROM AUTHOR]

This article is concerned with the $H_{\infty }$ proportional–integral–derivative (PID) control problem for class of discrete-time Takagi–Sugeno fuzzy systems subject to infinite-distributed time delays and round-robin (RR) protocol scheduling effects. The information exchange between the sensors and the controller is conducted through a shared communication network. For the purpose of alleviating possible data collision, the well-known RR communication protocol is deployed to schedule the data transmissions. To stabilize the target system with guaranteed $H_{\infty }$ performance index, a novel yet easy-to-implement fuzzy PID controller is developed whose integral term is calculated based on the past measurements defined in a limited time window with hope to improve computational efficiency and reduce accumulation error. Based on the Lyapunov stability theory and the convex optimization technique, sufficient conditions are derived to ensure the exponential stability as well as the $H_{\infty }$ disturbance attenuation/rejection capacity of the underlying system. Furthermore, by utilizing the cone complementarity linearization algorithm, the nonconvex controller design problem is transformed into an iterative optimization one that facilitates the controller implementation. Finally, simulation examples are given to show the effectiveness and correctness of the developed control method. [ABSTRACT FROM AUTHOR]

In this article, the problem of observer-based sliding-mode control for dynamic fuzzy systems with bounded external disturbances is investigated. First, the sufficient conditions for codesign of an observer and a sliding-mode control law are presented, such that the closed-loop system is asymptotically stable and affords satisfactory dissipative performance. The event-triggering mechanisms are also applied in the observer-based controller design. Then, an integral sliding-mode surface and an observer-based sliding-mode controller are designed such that the system trajectories are steadily maintained on the sliding surfaces. Finally, a numerical example is given to demonstrate the effectiveness of the developed new design method. [ABSTRACT FROM AUTHOR]

This article investigatesthe optimization $\mathcal {H}_{\infty }$ nonparallel distribution compensation (non-PDC) control issue for nonlinear systems under Takagi–Sugeno (T–S) fuzzy framework. First, sufficient conditions of designing fuzzy non-PDC controller to assure asymptotic stability while maintaining $\mathcal {H}_{\infty }$ performance for studied systems are presented. Afterward, in the case of guaranteeing performance requirements, based on the feasible region of controller membership functions, a novel membership functions online learning algorithm utilizing gradient decent strategy is first proposed to adjust controller membership functions in real time to achieve a superior $\mathcal {H}_{\infty }$ performance. Compared with conventional non-PDC fuzzy control scheme, the actual response of interference attenuation performance can be decreased efficaciously. In the light of Lyapunov stability theory, sufficient condition is derived to ensure the error convergence of cost function. At last, two illustrative examples are provided to demonstrate the effectiveness and usefulness of the proposed online learning algorithm. [ABSTRACT FROM AUTHOR]

In this article, we propose an improved delayed output-feedback sliding mode control of a fuzzy system with arbitrary order. A new time-delay estimator is designed for approximating the output derivatives in sliding surface, which has appealing noise attenuation capability. Then, such estimator is embedded in the feedback loops, which results in a static delayed output-feedback sliding surface. On this basis, the sliding mode control law depending on consecutive measurements is used to stabilize the fuzzy system subject to estimation biases and measurement noises. Different from the existing publications, the estimator and controller parameters are codesigned by genetic algorithm to make a tradeoff among multiple objectives: the closed-loop stability, noise attenuation, and estimation accuracy. The resulting design method is demonstrated by two examples: a mass-spring-damper system and a single-link rigid robot system. [ABSTRACT FROM AUTHOR]

In our recent work, we propose an indirect adaptive fuzzy control scheme for uncertain unparametrizable nonlinear systems, which ensures that the number of adaptive laws does not increase with the number of fuzzy rules, and the time derivative of the chosen Lyapunov function is negative semidefinite. However, the scheme involves a class of high-order smooth functions and their time derivatives, which can make the controller structure become sophisticated especially when the relative degree of system is quite large. To overcome this problem, in the article, we propose a new direct adaptive fuzzy control scheme based on a class of reduced-order smooth functions. With the scheme, no partial-derivative term is involved in controller and virtual controllers, only one adaptive law is used regardless of the increase of fuzzy rules, and also the time derivative of Lyapunov function can be ensured negative semidefinite. It is proved that all closed-loop signals are bounded, and the output tracking error converges to a prescribed interval asymptotically. The transient tracking performance and robustness of the proposed control scheme are also considered. The effectiveness of the obtained results is illustrated by two practical control systems. [ABSTRACT FROM AUTHOR]

The problem of leader-following consensus fault-tolerant control is investigated for multiagent systems (MASs) with time-varying nonaffine nonlinear faults, where the interactive topology is directional. In this article, to guarantee the performance consensus on tracking error, in the design process, the inherent problem of “explosion of complexity” is solved by the dynamic surface control technique. Fuzzy logic systems are employed to approximate the unknown nonlinearity effects and changes in model dynamics due to faults. A fuzzy state observer is presented to estimate the unmeasured states. According to the backstepping technique, a distributed consensus fuzzy controller is developed to guarantee that output signals of all followers and leader are synchronized. It can be proved that all variables of MASs are uniformly ultimately bounded. Finally, the validity of the control scheme is illustrated by some simulation results. [ABSTRACT FROM AUTHOR]

This article proposes a new robust control design framework for uncertain mechanical systems, which may be fully actuated or underactuated. The uncertainty is (possibly fast) time varying, which lies in prescribed fuzzy sets (hence fuzzy mechanical systems) and may be unbounded. The control goal is formulated as servo constraints (hence constraint-following control), which may be holonomic or nonholonomic. We introduce the possibility theory into the Lyapunov stability analysis (LSA), proposing possibility-based LSA (PBLSA), which allows a maximum failure possibility (generally small) prescribed by designers. It can be viewed as a generalization of the conventional LSA, and the resultant performance is interpreted in the context of possibility. By the PBLSA, a class of robust constraint-following controls that is not IF–THEN heuristic rules based is proposed, which renders approximate constraint following for the system performance with a prescribed maximal failure possibility. Optimal design of a control parameter considering both system performance and control cost is investigated. The benefits of the proposed design framework are discussed and simulations on two applications are given for demonstrations. [ABSTRACT FROM AUTHOR]

This article investigates the memory adaptive event-triggered fault detection and isolation (FDI) problem for nonlinear networked control systems under periodic denial-of-service (DoS) attacks, where the nonlinear systems are described by Takagi–Sugeno (T–S) fuzzy models with unknown membership functions. First, a novel event-triggered mechanism is proposed to save communication resources. The triggering threshold is adaptively adjusted by multiple previous sampled data, not only depending on the latest triggering data. Second, taking DoS attacks, and event-triggered mechanism into consideration, a switching state-feedback controller is established, and the exponential stability is derived. Meanwhile, the controller, and the event-triggered mechanism are simultaneously developed based on a piecewise Lyapunov function. Then, a set of switching T–S fuzzy observers are constructed to realize FDI under DoS attacks. Besides, a switching variable method is introduced to address the asynchronous premise variables problem caused by the event-triggered mechanism. Finally, simulation cases are given to demonstrate the validity, and merit of the proposed FDI scheme. [ABSTRACT FROM AUTHOR]

This article investigates the problem of resilient control for the Takagi–Sugeno (T–S) fuzzy systems against bounded cyberattack. A novel memory-based event triggering mechanism (ETM) is developed, by which the past information of the physical process through the window function is utilized. Using such an ETM cannot only lead to a lower data-releasing rate but also reduce the occurrence of wrong triggering event. Furthermore, the frequency of event generation is relatively smoother than existing ETMs. From the current releasing instant to the next, two periods are designed. The ETM works only when the first period ends, thereby avoiding the Zeno behavior that commonly exists in continuous ETM designs. The control system is then formulated as a switched fuzzy control system with two modes in each releasing period. Based on an assumption of secure control, and the proposed ETM, sufficient conditions are obtained to guarantee the exponential stability of networked T–S fuzzy systems in the presence of deception attacks in secure sense. Finally, a single-link rigid robot is taken as an example to illustrate the advantages of theoretical results. [ABSTRACT FROM AUTHOR]

In this article, the problem of flight control for a two-degree-of-freedom helicopter system is studied. Since the helicopter is a multiinput, multioutput nonlinear control system, a Takagi–Sugeno (T–S) fuzzy model is applied to approximate the system. All submodels of the new T–S fuzzy model contain constant terms due to the nonlinear characteristics of the helicopter system. In this article, sampled-data control is considered and the sampled data are transmitted to the system over a communication network. A large amount of sampled data transmitted over the network can significantly increase the computational and communication burdens for the network with a limited bandwidth. To overcome this difficulty, an event-triggered mechanism is introduced. In order to validly control the T–S fuzzy system, a fuzzy proportional integral-derivative (PID) controller is designed based on the Lyapunov method and practical stability criteria, which are obtained by using improved integral inequalities and the linear matrix inequality technique. Finally, a numerical example is given to show the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

In the supply chain system, the working capital is the core factor of normal operation for each node enterprise, but the internal and external uncertainties seriously affect the stability of working capital. Therefore, how to effectively manage the dynamic working capital in the uncertain supply chain system is a challenge. This article aims to investigate a robust financing strategy of the uncertain supply chain system by introducing the fuzzy control theory. First, a basic dynamic working capital operation model of the supply chain system with the internal and external uncertainties is constructed. Then, in terms of the corresponding financing strategies for the different idle working capital levels, a multimodel supply chain system is designed based on the basic model. Second, the Takagi–Sugeno fuzzy system is used to transform the multimodel system into a fuzzy switching model. Third, a robust financing strategy is proposed to suppress the impact of uncertainties on the supply chain system. This robust financing strategy can not only guarantee the stability of the uncertain supply chain system, but also reduce the financing cost. Finally, the effectiveness of the proposed robust financing strategy is verified by the results of simulation experiments. [ABSTRACT FROM AUTHOR]

In this article, we show that a fuzzy system of relative degree two can be stabilized by proportion-integration-differentiation (PID) sliding mode control depending on the outputs and their derivatives. The main focus of this article is to formulate a novel event-based fuzzy PID sliding surface under the imperfect premise matching. First, the measured output is adequately sampled for frequently checking a delay-dependent event-triggered condition, which reduces the number of data transmissions and controller updates. Then, an artificial time-delay estimator is used to approximate the output derivative. Based on linear matrix inequalities, a heuristic algorithm is investigated to design an event-triggered sliding mode controller, which reveals how to choose the maximum sampling interval that maintains the estimation accuracy and preserves the stability under fast event triggering. In simulation, the effectiveness of the proposed design method is verified in a cart and pendulum system subject to system uncertainties. [ABSTRACT FROM AUTHOR]

In this article, the singularity-free adaptive fuzzy fixed-time control problem is studied for an uncertain n-link robotic system with the position tracking error constraint. The controlled robotic system can be described as a multiple-input–multiple-output system.To implement the user-defined performance, an improved error conversion mechanism based on performance functions is presented such that the converted error is limited to an interval greater than zero, and an appropriate barrier Lyapunov function (BLF) is constructed to avoid the breach of position tracking error constraint. The fuzzy approximator is utilized to estimate the unknown functions. The significance and challenges of this article are to establish a new error conversion mechanism and design corresponding BLF that can be integrated into fixed-time control design to present a singularity-free adaptive fuzzy fixed-time control scheme. Benefits of the proposed adaptive fixed-time controller in comparison to the current approaches are that it cannot cause the singularity issue appearing in backstepping-based fixed-time control design and ensures quick transient response. Combining with Lyapunov stability theory, the boundedness of the closed-loop signals is ensured, and the position tracking error can be constrained in the user-defined performance boundaries. Finally, simulation results demonstrate the feasibility of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article considers the transmission power scheduling in the control of a linear plant when the plant state is transmitted from a sensor to the controller over a wireless fading channel. The power allocated to these transmissions determines the probability of successful packet reception. This article focuses on investigating how much power should be assigned to transmit the data packet at each time. A new framework of optimal power allocation is established by introducing a cost function, which weighs the control performance and energy cost. First, a necessary and sufficient condition for the existence of the solution to finding an admissible schedule is given. Then, by combining an adaptive dynamic programming technique with fuzzy approximation theory, a new state-dependent scheduling algorithm is proposed to find the optimal power allocation policy. The convergence analysis shows that the proposed power scheduling algorithm can approximate the optimal solution on a compact set with a desired precision. Simulation results are presented to illustrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This article investigates the problem of event-triggered-based sliding mode control (SMC) for a class of Takagi–Sugeno (T–S) fuzzy systems with actuator failures and signal quantization. The classical dynamic uniform quantization strategy is employed to quantize data in both sensor-controller side and controller-actuator side. A new event-triggered adaptive SMC scheme is proposed to stabilize the fault closed-loop systems, where the event-triggered condition is based on quantized state vectors. Reachability of the proposed sliding surface can be ensured by the designed control scheme. Furthermore, the existence of minimal inter-event time and sufficient conditions under which zeno behavior can be avoided is analyzed and presented. Finally, two examples are provided to demonstrate the effectiveness of the proposed new design techniques. [ABSTRACT FROM AUTHOR]

This article addresses an adaptive fuzzy control for the nonstrict-feedback nonlinear systems with asymmetric time-varying full state constraints. To prevent the state constraints being violated, the nonlinear state-dependent function (NSDF) is introduced instead of the tradition barrier lyapunov function (BLF). The constrained systems are transformed into a novel free-constrained systems based on the NSDF. A direct approach is given to cope with the state constraints. Fuzzy logic system is utilized to approximate the uncertain nonlinear system functions. The new affine variables are constructed for the transformed systems, and the prior knowledge of the control gains is not required necessarily. Under the designed control scheme, the boundedness of the signals in the closed-loop systems is guaranteed certainly, and the asymmetric time-varying constraints are maintained. This proposed method removes the feasibility condition on the virtual controller derived from the method of BLF. The effectiveness of the proposed control strategy is verified by two simulation examples. [ABSTRACT FROM AUTHOR]

This article investigates the observer-based finite-time H∞ control problem for interconnected fuzzy systems with quantization and random network attacks, where two types of network attacks including denial-of-service (DoS) and fault data injection (FDI) attacks are considered. In order to achieve the occupancy reduction of network resources, the measured outputs of interconnected systems are quantized through a logarithmic quantizer before being transmitted by the communication channel. Combining the effects of quantization and random network attacks, an observer-based control model is first constructed. Then, based on Lyapunov functional approach and stochastic analysis technique, some sufficient conditions are presented such that the considered closed-loop interconnected system is stochastically finite-time bounded with a prescribed disturbance attenuation level, and the gain matrices of fuzzy observer and fuzzy controller can be found by solving an optimization algorithm with linear matrix inequalities constraints. Finally, two simulation examples are given to illustrate the validity of the proposed approach. [ABSTRACT FROM AUTHOR]

It is interesting to study the problem of adaptive fuzzy control for uncertain nonlinear systems with input and state hysteresis. However, since the hysteresis behavior, especially the state hysteresis, present at the sensors is complicated, mainly in view of its multivalues and rate-dependent features, it is a challenging task to develop the backstepping-based control design. So far, there is still no available result in addressing the problem. In this article, we will pursue this task. A novel indirect fuzzy control scheme is proposed with an alternative adaptive hysteresis inverse, which is used to cancel the unknown input hysteresis. To tackle the effects of state hysteresis, a new dynamic compensation is developed to adaptively accommodate the uncertain dynamics involved in the sensors. It is proved that in addition to system stability, the proposed scheme enables the tracking error to approach a prescribed interval asymptotically. Illustrative examples are used to verify the method developed. [ABSTRACT FROM AUTHOR]

This article addresses the problem of continuous-time dynamic sliding mode control for Takagi–Sugeno fuzzy nonlinear systems based on an event-triggered mechanism. First, a novel sliding mode dynamic system is established by introducing a corresponding sliding mode function and an efficient event-triggered mechanism. Then, based on a new Lyapunov function and the reciprocally convex method, sufficient conditions are presented to guarantee that the constructed network sliding mode dynamics is asymptotically stable. It is shown that the trajectories of the sliding mode dynamic system can converge into a bounded domain of a sliding mode surface in finite time. Furthermore, the explicit expression of the desired sliding mode controller is given in the form of linear matrix inequalities. Finally, the applicability and effectiveness of the proposed design techniques are demonstrated by a numerical example. [ABSTRACT FROM AUTHOR]

In this article, the stability analysis and control synthesis of interval type-2 (IT2) polynomial-fuzzy-model-based networked control systems are investigated under the event-triggered control framework. The nonlinear dynamics in the plant is efficiently represented by an IT2 polynomial fuzzy model that the IT2 membership functions are utilized to capture the uncertainties in the plant. An event-triggered IT2 polynomial fuzzy controller is then designed to stabilize the nonlinear model subject to uncertainties. The stability conditions of the closed-loop control system are summarized in the form of sum-of-squares. Under the imperfectly premise matching (IPM) concept, the membership-function-dependent (MFD) approach is applied to endow the polynomial fuzzy controllers with more flexibility in terms of number of rules and premise membership functions. In the MFD approach under the IPM concept, both the number of rules and the shape of membership functions in the fuzzy models and controllers can be different. Also, the information of IT2 membership functions of the polynomial fuzzy model and controller is considered and adopted to further relax the stability conditions. Furthermore, the intrinsic mismatched issue of the premise variables of the fuzzy model and controllers due to the event-triggering mechanism is handled by the MFD approach. A detailed simulation example is provided to verify the effectiveness of the proposed event-based control strategy. [ABSTRACT FROM AUTHOR]

In this article, an output feedback model predictive control for fuzzy systems to track a time-varying steady-state target is presented. The steady-state target is calculated through a steady-state target calculation (SSTC) module, which is combined with the controller in the lower layer designing based on the linear time invariant model. The presence of SSTC makes the recursive feasibility as well as the stability difficult to guarantee. This article presents a promising approach by specifying the solution of SSTC as a function of estimated artificial disturbance, designing the robust invariant set offline and including the invariance condition in SSTC. Hence, the proposed approach in this article guarantees that if SSTC optimization problem is feasible, then the dynamic controller steers the system to the time-varying steady-state target. Furthermore, in order to reduce the conservativeness of the proposed approach, a heuristic online approach with N free control moves is proposed where the invariant set specified offline is acting as a terminal region for the dynamic controller. A numerical example is given to show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This article investigates the nonfragile retarded fuzzy sampled-data control design of Takagi–Sugeno (T–S) fuzzy system. When compared to the traditional sampled-data control scheme, a constant signal transmission delay is involved with uncertainties in control gain parameters, which exploited for the first time to tackle the stabilization analysis of the closed-loop T–S fuzzy systems based on the switched control idea. By constructing a fuzzy membership function (FMF)-dependent Lyapunov–Krasovskii functional (LKF) and utilizing the time-derivative information of the FMF, the sufficient conditions are carried out in terms of linear matrix inequalities (LMIs) such that the resultant T–S fuzzy systems can achieve the globally asymptotically stable under the designed control. Then, the desired control gain is determined by solving the obtained LMIs. Finally, the numerical simulations are demonstrated to show the advantage and applicability of the derived sufficient conditions. [ABSTRACT FROM AUTHOR]

This article concentrates on the output feedback controller design problem for discrete-time nonlinear switched systems with actuator faults. The Takagi–Sugeno fuzzy model is adopted to approximate the nonlinearity of the plant with a set of local linear models. The persistent dwell-time (DT) switching law, which is more general than DT or average DT switching, is introduced to govern the switching among subsystems. In order to alleviate the effects of actuator failures on system stability and performance, a synthesized fault-tolerant output feedback controller ensuring various performance requirements is designed. Intensive attention is focused on establishing sufficient conditions, which can guarantee the exponential mean-square stability as well as the prescribed extended dissipativity property of the closed-loop system. By virtue of the Lyapunov stability theory and appropriate matrix transformation methods, the desired controller gains can be obtained by solving a convex optimization problem. The developed method is finally applied to address the control issue of a tunnel diode circuit system model to illustrate its efficiency and applicability. [ABSTRACT FROM AUTHOR]

In this paper, the stability and positivity of positive polynomial fuzzy model based (PPFMB) control system are investigated, in which the positive polynomial fuzzy model and positive polynomial fuzzy controller are allowed to have different premise membership functions from each other. These mismatched premise membership functions can increase the flexibility of controller design; however, it will lead to the conservative results when the stability is analyzed based on the Lyapunov stability theory. To relax the positivity/stability conditions, the improved Taylor-series-membership-functions-dependent (ITSMFD) method is introduced by introducing the sample points information of Taylor-series approximate membership functions, local error information and boundary information of substate space of premise variables into the stability/positivity conditions. Meanwhile, the ITSMFD method is extended to the PPFMB control system with input saturation to relax the estimation of domain of attraction. Finally, simulation examples are presented to verify the feasibility of this method. [ABSTRACT FROM AUTHOR]

This article studies the sliding mode control (SMC) of a class of Takagi–Sugeno (T–S) fuzzy singular systems with matched external disturbances. The key advantage of this article is that the input matrices of the considered fuzzy systems could be different, and a novel SMC provided in this article has strong robustness. In this article, systems with delayed state are considered. The time delay is a known constant, and the full state vector is available for feedback. At first, a new sliding mode surface, vector integral sliding mode surface, is proposed. By use of this surface, the stabilization problem for some T–S fuzzy singular systems with different input matrices can be settled. Second, a new SMC law is provided to avoid the state of the considered fuzzy system escaping from every subsliding mode surface. Finally, two examples are provided to verify the validity of the method proposed in this article. [ABSTRACT FROM AUTHOR]

This paper is concerned with the event-triggered dynamic output feedback control problem for Takagi–Sugeno (T–S) fuzzy systems under asynchronous network communications. Compared with the existing event-triggered output feedback results for the T–S fuzzy systems, two event-triggered mechanisms are predefined independently to check in an asynchronous manner whether the measurement output and the control input should be transmitted over networks or not. Consequently, network resources can be further saved. By introducing an auxiliary function in modeling, a delay system model is constructed. Then, a new stability criterion is presented such that the resulting closed-loop system is asymptotically stable. Furthermore, event-triggered parameters and controller gains can be codesigned if the related linear matrix inequalities are feasible. Finally, the validity of the theoretical result is illustrated by two examples. [ABSTRACT FROM AUTHOR]

This paper is concerned with the observer-based fault-tolerant tracking controller design problem for a class of T–S fuzzy systems with mismatched faults and disturbances. First, a sequence of adaptive observers are constructed, based on which an iterative algorithm is given to obtain the estimations of the system states and the fault signals simultaneously. Different from the existing results which mainly focus on the compensation of matched faults, by employing an equivalent matrix transformation technique and the backsteppinglike technique, a novel observer-based fault-tolerant tracking control scheme is developed to compensate the effects of the mismatched faults and achieve the output tracking objective. Furthermore, it is proven that all the signals of the resulting closed-loop fuzzy system are uniformly ultimately bounded and the output tracking error converges to a bounded region whose upper bound is relevant to the design parameters and the estimate errors. Finally, two simulation examples are provided to illustrate the validity of the proposed controller design method. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of sliding mode observer design for a class of uncertain fuzzy time-delay systems based on an event-triggered strategy. The objective is to design an event-triggered mechanism by utilizing the information of system output and observer function. Based on the delay partitioning method and the Lyapunov–Krasovskii function approach, delay-dependent sufficient conditions are proposed to guarantee the overall system, including sliding mode dynamics and error dynamics, to be asymptotically stable with an $\mathcal {H}_{\infty }$ performance. Furthermore, an event-triggered sliding mode controller is synthesized to ensure that the system dynamics can be driven to the sliding region near the equilibrium point in finite time. Finally, a verification example is provided to demonstrate the feasibility and efficiency of the theoretical results presented. [ABSTRACT FROM AUTHOR]

In this paper, sampled-data control is proposed to stabilize the nonlinear system, which is expressed as a Takagi–Sugeno (T–S) fuzzy submodels. Based on suitable Lyapunov– Krasovskii functional (LKF) along with new weighted integral inequalities, the sufficient conditions are derived in terms of linear matrix inequalities, which ensure the exponential stability of the proposed closed loop T–S fuzzy system. The peculiarity of this paper is: as novel integral inequalities and LKF are proposed, less conservative results are provided when compared to existing results. Besides that, wind energy conversion systems, chaotic systems, and an inverted pendulum are validated with derived sufficient conditions. The corresponding simulation results show the merit of the proposed results over the existing works. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of robust $H_{\infty }$ control for a class of nonlinear systems with state and input time-varying delays. The nonlinearity is presented by a continuous-time Takagi-Sugeno (T-S) fuzzy model with parameter uncertainties. A sufficient asymptotic stability condition is first proposed by constructing a delay-product-type augmented Lyapunov–Krasovskii functional and utilizing an extended reciprocally convex matrix inequality together with a Wirtinger-based integral inequality. Then, a state feedback controller is derived that guarantees the closed-loop fuzzy system being asymptotically stable with an $H_{\infty }$ performance index. Finally, four numerical examples are given to reveal the effectiveness and merits of the developed new design techniques. [ABSTRACT FROM AUTHOR]

This paper concentrates on the bumpless transfer control problem for a category of switched fuzzy systems with $L_2$ -gain property. A description of the bumpless transfer performance for switched fuzzy systems is introduced for the first time. A general multiple Lyapunov functions strategy is exploited to solve the bumpless transfer control problem of the switched fuzzy systems with the $L_2$ -gain property. The multiple Lyapunov functions scheme allows the disconnection of the successive Lyapunov functions when a switching happens. A criterion on the bumpless transfer performance with the $L_2$ -gain property is established, allowing each subsystem to satisfy neither the bumpless transfer performance nor the $L_2$ -gain property. Moreover, when only the $L_2$ -gain property is considered, the condition is mildly expressed in terms of matrix inequalities rather than the usual combination of matrix inequalities and matrix equalities. Finally, an example of controlling a mass-spring-damping model is offered to validate the effectiveness of the developed control strategy. [ABSTRACT FROM AUTHOR]