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This paper proposes a fuzzy modeling and event-triggered adaptive sliding mode control for steer-by-wire (SbW) systems subject to uncertain nonlinearity, time-varying perturbation, actuator fault, and limited communication resources. First, an interval type-2 fuzzy logic system (IT2 FLS) based on Lyapunov's adaptive scheme is built to model the uncertain nonlinearity. Then, an event-triggered adaptive sliding mode control method is designed to overcome the limited communication resources, time-varying perturbation, and actuator fault. This method eliminates the chattering phenomenon by utilizing nested adaptive technology and has practical finite-time stability. Theoretical analysis shows that the Zeno phenomenon is excluded. Finally, the validity of the methods is evaluated using simulations and vehicle experiments. [ABSTRACT FROM AUTHOR]

This article addresses the event-triggered output feedback control problem of steer-by-wire (SbW) systems subject to uncertain nonlinearity and time-varying disturbance. First, to solve the uncertainty and remove unnecessary sensors, an interval 2 fuzzy logic system and an adaptive state observer are proposed to estimate the uncertain nonlinearity and unavailable states of SbW systems. Then, an event-triggered output feedback control method is constructed for SbW systems to achieve the prespecified tracking performance. Much significantly, the jumping phenomenon of the control input caused by event-triggering communication can be eliminated by the proposed event-triggered control systems. Furthermore, theoretical analysis shows that the tracking error can converge to the preset neighborhood of origin within finite time, while the Zeno behavior can be avoided. Finally, simulations and vehicle experiments are presented to verify the validity of the proposed methods. [ABSTRACT FROM AUTHOR]

It is hard to achieve precise displacement for the permanent-magnet synchronous motor (PMSM) servo systems due to the nonlinear friction and time-varying end-load. This paper proposes an observer-based compensation control strategy to cope with the above issues. First, an adaptive interval type-2 Takagi-Sugeno-Kang (TSK) fuzzy logic system is adopted to estimate the inherent friction. By utilizing the tracking and modeling error, the composite adaptive updating law is constructed to improve the tracking performance. Then, the residual reconstruction errors and the bounded end-load are estimated and compensated by the designed disturbance observer. Estimation of friction and disturbance observer, as compensation terms, are employed in traditional cascade control. Finally, the proposed controller guarantees the tracking error is uniformly ultimately bounded based on Lyapunov theory. Simulations and experiments are presented to verify the effectiveness and superiority of the proposed controller. [ABSTRACT FROM AUTHOR]

This paper addresses the tracking control problem for the uncertain steer-by-wire (SbW) system with the controller area network (CAN) communication and unavailable variables. First, an adaptive interval type-2 fuzzy logic system (IT2 FLS) and sliding mode observer are constructed to estimate the uncertain nonlinearity and unavailable variables of SbW control systems. Further, an event-triggered sliding mode control (ET-SMC) is presented to achieve the transient steering performance of SbW systems while saving CAN communication resources. Much importantly, the dynamic gain and nested technologies are incorporated in this scheme to deal with estimation error and the chattering phenomenon of the sliding mode control system. It is shown that the practical fixed-time stability of the closed-loop system can be guaranteed without the initial condition of tracking errors. Finally, simulations and vehicle experiments are presented to verify the designed scheme. • An adaptive type-2 fuzzy logic system is used to realize the intelligent modeling. • A state observer is designed to estimate the angular velocity of front-wheels. • A sliding mode control is proposed to achieve practical fixed-time stability. • The communication resource can be saved by event-triggered communication. [ABSTRACT FROM AUTHOR]

This paper studies the tracking control of the SbW system with unknown nonlinear friction torque and the unmeasured angular velocity. An observer-based adaptive interval type-2 fuzzy logic system controller is proposed to eliminate the adverse influence of the friction torque on the SbW system. Firstly, the angular velocity of the front wheels is estimated via the observer, such that the system sensitivity to measurement noise, the hardware cost, and the structural complexity are reduced. Then, an interval type-2 fuzzy logic system (IT2 FLS) is used to model the friction torque, in which the model and parameters are not effectively identified. IT2 FLS has a more exceptional ability to deal with uncertainties than the traditional type-1 fuzzy logic system (T1 FLS), so the friction modeling based on IT2 FLS has more satisfactory effect in practical application. Finally, an adaptive interval type-2 fuzzy logic system controller is proposed to achieve excellent tracking performance. The tracking error can be guaranteed to converge asymptotically to zero by the Lyapunov stability theory. The numerical simulations and hardware-in-loop (HIL) experiments verify the effectiveness and superiority of the proposed friction modeling method and control strategy. [ABSTRACT FROM AUTHOR]

The steering-by-wire (SbW) system is one of the main subsystems of automatic vehicles, realizing the steering control of autonomous vehicles. This paper proposes an event-triggered adaptive sliding mode control for the SbW system subject to the uncertain nonlinearity, time-varying disturbance, and limited communication resources. Firstly, an event-triggered nested adaptive sliding mode control is proposed for SbW systems. The uncertain nonlinearity is approximated by the interval type-2 fuzzy logic system (IT2 FLS). The time-varying disturbance, modeling error, and event-triggering error can be offset by robust terms of sliding mode control. The key advantage is that the high-frequency switching of sliding mode control only appears on the time derivate of control input without increasing the input-output relative degree of closed-loop SbW systems, such that the chattering phenomenon can be eliminated. Finally, theoretical analysis shows that the practical finite-time stability of the closed-loop SbW system can be achieved, and communication resources in the controller-to-actuator channels can be saved while avoiding the Zeno-behavior. Numerical simulations and experiments are given to evaluate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Control aims to avoid oxygen starvation and maximize the net power output by maintaining the optimal oxygen excess ratio (OER), which varies between 1.8 and 2.5. Because of the nonlinearity of the proton exchange membrane fuel cell (PEMFC) air supply system and the different conditions, ensuring an optimal OER is still a challenge. In this study, a model-free adaptive controller is presented for the PEMFC air supply system based on feedback linearization and interval type-2 fuzzy logic systems (IT2 FLSs). Theoretical analysis and experimental results verify the effectiveness of the proposed control scheme. For the theoretical analysis, first, the PEMFC air supply system is transformed into a canonical form with the feedback linearization technique. Then, zero-dynamics stability is discussed in detail to determine the stability of the internal dynamics. Finally, an adaptive interval type-2 fuzzy logic system controller (AIT2FLSC) is designed on the basis of the Lyapunov stability theory, which does not require complete a priori knowledge of the system dynamics. For the experimental results, the root mean square error (RMSE), variance, and standard deviation (SD) of the tracking error are used as tracking performance metrics to evaluate the control accuracy of the proposed AIT2FLSC, which are 0.0968, 0.0093, and 0.0962, respectively. Compared with the traditional proportion integration differentiation controller (RMSE 0.1119, variance 0.0122, and SD 0.1105), this proposed algorithm obtains better adaptability and the RMSE of the tracking error improves 13.48%. Compared with the adaptive type-1 fuzzy logic system controller (AT1FLSC) (RMSE 0.1076, variance 0.0113, and SD 0.1063), this AT2FLSC has a stronger ability to deal with uncertainty and the RMSE of the tracking error improves 10% when the stack temperature is fixed (353.15 K). Furthermore, when the stack temperature is time-varying, the RMSE, variance, and SD of the tracking error under the AIT2FLSC are 0.0966, 0.0092, and 0.0960, respectively, which is less than AT1FLSC (0.1085, 0.0115, and 0.1073) and the RMSE of the tracking error improves 10.99%. [ABSTRACT FROM AUTHOR]

This paper addresses a tracking control problem for Steer-by-Wire (SbW) systems with unmeasurable states, model uncertainty, and limited communication resources. An interval type-2 fuzzy logic system (IT2 FLS)-based fixed-time state observer are proposed to estimate the unavailable state. Different from the accurate model-based state observers and the observers with some additional assumptions, under the proposed observer, the extra conditions can be removed and the fixed-time convergence of observation error can be guaranteed. To save communication resources of the controller-to-actuator channels and achieve the prescribed tracking performance, an event-triggered prescribed performance control (PPC) scheme is proposed. Compared with these existing PPC methods, the computational complexity is reduced and a new prescribed performance function with fixed-time convergence is suggested to improve the steady-state and transient performance of the closed-loop system. The Zeno behavior of the event-triggered communication can be avoided. Simulations and experiments are carried out to demonstrate the effectiveness and superiority of the proposed control technique. [ABSTRACT FROM AUTHOR]

The cutoff frequency of filter has a great influence on the image quality of positron emission tomography (PET). Understanding this physical phenomenon and developing some intelligent strategies to effectively determine cutoff frequency have both theoretical and practical significance. This paper proposes a new algorithm for automatically choosing filter cutoff frequency using neuro-fuzzy system. In the proposed method, wavelet theory is used to extract noise information which enhances the accuracy of cutoff frequency calculation and improves filtering performance. A neuro-fuzzy system is developed for modeling cutoff frequency function and adjusting weight values using gradient descent scheme. As a general method, the proposed approach is tested by using typical window functions. Results show that proposed techniques are effective and efficient for automatically determining cutoff frequency. [ABSTRACT FROM AUTHOR]

This paper proposes an event-triggered higher-order sliding mode control for steer-by-wire (SbW) systems subject to limited communication resources and uncertain nonlinearity. First, an interval type-2 fuzzy logic system (IT2 FLS) is adopted to approximate the uncertain nonlinearities. A fuzzy-based state observer is developed to estimate unavailable states of the extended SbW system. Then, to save communication resources and eliminate chattering, an event-triggered higher-order sliding mode control is proposed for the SbW system. The key advantage is that the proposed control scheme can offset the observation error and the event-triggering error. After that, the practical finite-time stability of the closed-loop SbW system is proved in the framework of the Lyapunov theory. Finally, numerical simulations and vehicle experiments are given to evaluate the effectiveness and superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

Modeling of friction forces has been a challenging task in mechanical engineering. Parameterized approaches for modeling friction find it difficult to achieve satisfactory performance due to the presence of nonlinearity and uncertainties in dynamical systems. This paper aims to develop adaptive fuzzy friction models by the use of data-mining techniques and system theory. Our main technical contributions are twofold: extraction of fuzzy rules and formulation of a static fuzzy friction model and adaptation of the fuzzy friction model by the use of the Lyapunov stability theory, which is associated with a control compensation of a typical motion dynamics. The proposed framework in this paper shows a successful application of adaptive data-mining techniques in engineering. A single-degree-of-freedom mechanical system is employed as an experimental model in simulation studies. Results demonstrate that our proposed fuzzy friction model has promise in the design of uncertain mechanical control systems. [ABSTRACT FROM AUTHOR]

• An adaptive state observer is proposed to estimate the unavailable state. • The nonlinearity is approximated by the interval type-2 fuzzy logic system. • The time-varying disturbance is estimated by the disturbance observer. • A finite-time control is presented to achieve prespecified tracking accuracy. • The event-triggered communication is applied to save communication resources This paper addresses the event-triggered tracking control problem of the SbW system subject to unavailable steering angular velocity of front-wheels, time-varying external disturbance, and uncertain dynamics, including friction torque and self-aligning torque. First, an adaptive state observer is proposed to estimate the unavailable steering angular velocity of front-wheels. The uncertain nonlinearity and time-varying disturbance can be estimated by the adaptive interval type-2 fuzzy logic system (IT2 FLS) and the disturbance observer, respectively. An event-triggered control is proposed for SbW systems to guarantee the prespecified control performance and save communication resources in the controller-to-actuator channel. Much importantly, the nested robust terms are incorporated in the control scheme to counteract the observation error and overcome the negative influence of the event-triggering error. Theoretical analysis shows that the prespecified arbitrary tracking accuracy can be guaranteed within finite time, and the Zeno-behavior can be strictly avoided while saving communication resources in the controller-to-actuator channel. Finally, simulation and vehicle experiment results and some comparisons are given to evaluate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Steer-by-Wire (SbW) system is a significant electromechanical subsystem of automated vehicles. This paper proposes an observer-based type-2 fuzzy control method for the SbW system with uncertain nonlinearity, unknown modeling parameters, and unavailable state. First, an interval type-2 fuzzy logic system (IT2 FLS) and an IT2 FLS-based state observer are constructed to estimate the uncertain nonlinearity and unavailable state of SbW systems. Then, a prescribed performance control (PPC) method is proposed to achieve the prescribed tracking performance of SbW systems. Much importantly, a modified performance function is incorporated in this control method, such that the prescribed tracking performance can be guaranteed within a finite time regardless of the initial state. Finally, simulation and vehicle experiments are given to verify the effectiveness and superiority of the proposed methods. [ABSTRACT FROM AUTHOR]