Fuzzy Fault-tolerant Control Scheme Research Articles

Adaptive fuzzy fault-tolerant control for active seat suspension systems with full-state constraints

In this paper, an adaptive fuzzy fault-tolerant control (FTC) scheme is proposed for active seat suspension systems. The addressed system contains electromagnetic actuator faults. In addition, the constraints of the displacements of the car seat, active suspension, and wheel, their vertical vibration speeds and current intensity are included. In the control design, since the systems have dynamic characteristics of complexities and spring non-linearities, the fuzzy logic systems are utilized to approximate the unknown nonlinear dynamics. By the aid of Barrier Lyapunov functions and based on the adaptive backstepping recursive design algorithm, a novel adaptive fuzzy FTC scheme is formulated. When the electromagnetic actuator fails, the developed control scheme can guarantee that all the vertical vibration states are stable. Eventually, the effectiveness of the presented control method is offered to illustrate by a random road surface.

Fuzzy adaptive fixed-time fault-tolerant attitude tracking control for tailless flying wing aircrafts

This work investigates the fault-tolerant attitude tracking control problem for the tailless flying wing aircraft in the presence of an external disturbance, uncertain parameters, and time-varying actuator failures. First, the external disturbance, uncertainty, and time-varying actuator failures are skillfully transformed into a lumped uncertainty, followed by an approximator constructed by employing an interval type-2 fuzzy logic system (IT2-FLS). On this basis, a fixed-time IT2 fuzzy fault-tolerant control scheme is proposed, which can guarantee that all the signals of the closed-loop system have fixed-time convergence. The desired control torque is allocated to each control surface through a recurrent neural network (RNN) based control allocation algorithm by considering the magnitude and rate constraints of the actuators. Finally, the two representative simulations have been conducted to validate the effectiveness and superiority of the proposed control scheme and control allocation algorithm.

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

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

Fuzzy-approximation adaptive fault-tolerant control for nonlinear pure-feedback systems with unknown control directions and sensor failures

In this paper, the problem of adaptive fuzzy fault-tolerant control (FTC) is investigated for a class of nonlinear pure-feedback systems with unknown control directions and sensor failures. By utilizing the mean value theorem, the considered nonlinear pure-feedback system is transformed into a strict-feedback structure. The unavailability of state variables caused by sensor faults is dealt with by using parameter separation and regrouping technique. Based on cancelation and decoupled backstepping technique, an adaptive fuzzy fault-tolerant control method is developed. It is proved that the proposed adaptive FTC scheme can guarantee the exponential stabilization of the resulting closed-loop system. Furthermore, all the signals of the system remain semi-global uniformly ultimately bound (SGUUB). The simulation results are provided to illustrate the effectiveness of the proposed control scheme.

Decentralized adaptive fuzzy fault-tolerant tracking control of large-scale nonlinear systems with actuator failures

This study is concerned with the problem of decentralized adaptive fault-tolerant control for a class of large-scale non-affine and nonlinear systems with external disturbances and actuator failures including loss of effectiveness and bias. Based on fuzzy logic systems (FLSs) to approximate the appropriate nonlinear functions, a novel decentralized adaptive fuzzy fault-tolerant control scheme is developed via direct adaptive control technique. To tackle the non-affine term with actuator failures, with the help of a non-affine compensation term, the corresponding adaptive mechanism that depends on the unknown upper bound of a defined compounded disturbance is introduced. Meanwhile, by utilizing the on-line estimating information of the unknown upper bound and the unknown parameters of necessary FLSs, a new adaptive fuzzy fault-tolerant controller with the adjustable parameter updated laws is designed to achieve robust tracking performance. Furthermore, it is shown that all the closed-loop signals of the interconnected subsystems are uniformly bounded and the tracking errors asymptotically converge to zero via Lyapunov stability analysis. Finally, numerical simulation results are provided to demonstrate the efficiency of the presented decentralized adaptive fuzzy fault-tolerant tracking design scheme.

Adaptive output feedback fault-tolerant control of switched fuzzy systems

This paper investigated the adaptive fault-tolerant control problem for a class of switched Takagi–Sugeno fuzzy systems. The considered switched fuzzy systems contain unmeasured states and actuator failures. In the control design, a switched state observer is designed to estimate the unmeasured states. Under the parallel-distributed compensation (PDC) design scheme and using the online estimation of actuator faults, an adaptive fuzzy fault-tolerant control scheme is proposed, in which a compensation control term is introduced in order to reduce the effect of actuator faults. Utilizing the estimated states and a segmentation of state space, the switching law is constructed. The sufficient conditions for ensuring the asymptotic stability of the switched fuzzy systems are proposed and formulated in the form of linear matrix inequalities (LMIs). By using the single Lyapunov function method, it is proved that the proposed control approach can guarantee the asymptotic stability of the closed-loop system. One practical example and a numerical example are given to illustrate the effectiveness of the proposed control method.

Robust fuzzy adaptive fault-tolerant control for a class of nonlinear systems with mismatched uncertainties and actuator faults

This paper studies the adaptive fuzzy fault-tolerant control (FTC) problem for a class of nonlinear systems with mismatched uncertainties and actuator faults. Two control schemes are designed to compensate for the actuator faults including outage, stuck and loss of effectiveness. The fuzzy logic systems are applied to approximate the bound of unknown nonlinear functions without knowing the information about the upper bound of mismatched uncertainties. By using projection modification algorithm and the improved adaptation law with $$\sigma $$ -modification, the adaptive fuzzy FTC scheme is designed. It is shown that the system states can converge asymptotically to zero even in the presence of actuator faults. However, the chattering phenomenon may occur. To overcome the undesirable chattering phenomenon, a continuous-state feedback control strategy is adopted for the control design so that the required assumption can be removed. It is shown that all the signals in the resulting closed-loop system are semi-globally uniformly ultimately bounded. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control methods.

Fuzzy Adaptive Actuator Failure Compensation Control of Uncertain Stochastic Nonlinear Systems With Unmodeled Dynamics

This paper investigates fuzzy adaptive actuator failure compensation control for a class of uncertain stochastic nonlinear systems in strict-feedback form. These stochastic nonlinear systems contain the actuator faults of both loss of effectiveness and lock-in-place, unmodeled dynamics, and without direct measurements of state variables. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy state observer is established to estimate the unmeasured states. By introducing the dynamical signal and the changing supply function technique design into the backstepping control design, a robust adaptive fuzzy fault-tolerant control scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are bounded in probability in the presence of the actuator failures and the unmodeled dynamics. Simulation results are provided to show the effectiveness of the control approach.

Adaptive Type-2 Fuzzy Sliding Mode Controller for SISO Nonlinear Systems Subject to Actuator Faults

In this paper, an adaptive type-2 fuzzy sliding mode control to tolerate actuator faults of unknown nonlinear systems with external disturbances is presented. Based on a redundant actuation structure, a novel type-2 adaptive fuzzy fault tolerant control scheme is proposed using sliding mode control. Two adaptive type-2 fuzzy logic systems are used to approximate the unknown functions, whose adaptation laws are deduced from the stability analysis. The proposed approach allows to ensure good tracking performance despite the presence of actuator failures and external disturbances, as illustrated through a simulation example.

Fault Estimation and Tolerant Control for Fuzzy Stochastic Systems

This paper deals with the problem of fault estimation and fault-tolerant control for Takagi-Sugeno (T-S) fuzzy stochastic systems with sensor failures, where the system under consideration contains Itô-type stochastic disturbances. A new robust observer technique is presented to obtain the estimates of the system states and the sensor faults simultaneously, and a fuzzy fault-tolerant control scheme is developed to guarantee the closed-loop system to be exponentially stable in mean square. Sufficient conditions are obtained for the existence of admissible controllers, and it is shown that the reachability of the sliding-mode dynamics can be guaranteed under the proposed control techniques. Finally, a numerical example is provided to illustrate the effectiveness and applicability of the theoretic results obtained.

Fault tolerant control using a fuzzy predictive approach

This paper proposes the application of fault-tolerant control (FTC) using fuzzy predictive control. The FTC approach is based on two steps, fault detection and isolation (FDI) and fault accommodation. The fault detection is performed by a model-based approach using fuzzy modeling and fault isolation uses a fuzzy decision making approach. The information obtained on the FDI step is used to select the model to be used in fault accommodation, in a model predictive control (MPC) scheme. The fault accommodation is performed with one fuzzy model for each identified fault. The FTC scheme is used to accommodate the faults of two systems a container gantry crane and three tank benchmark system. The fuzzy FTC scheme proposed in this paper was able to detect, isolate and accommodate correctly the considered faults of both systems.