Resilient anti-disturbance dynamic surface control of uncertain strict-feedback systems subject to partial loss of actuator effectiveness

This paper is concerned with the tracking control of a class of uncertain strict-feedback systems subject to partial loss of actuator effectiveness, in addition to uncertain model dynamics and unknown disturbances. A resilient anti-disturbance dynamic surface control method is proposed to achieve stable tracking regardless of partial actuator faults. First, data-driven adaptive extended state observers are designed based on memory-based identifiers, such that the uncertain model dynamics, external disturbances and the unknown input gains due to actuator faults can be estimated. Next, a resilient anti-disturbance dynamic surface controller is developed based on recovered information from the data-driven adaptive extended state observers. After that, it is proven that the cascade system formed by the observer and controller is input-to-state stable. Finally, comparative studies are performed to validate the efficacy of the resilient anti-disturbance dynamic surface control method for nonlinear strict-feedback systems subject to partial loss of actuator effectiveness.

     

Finite time integral sliding mode control of hypersonic vehicles

This study investigates the tracking control problem for the longitudinal model of an airbreathing hypersonic vehicle (AHV) with external disturbances. By introducing finite time integral sliding mode manifolds, a novel finite time control method is designed for the longitudinal model of an AHV. This control method makes the velocity and altitude track the reference signals in finite time. Meanwhile, considering the large chattering phenomenon caused by high switching gains, an improved sliding mode control method based on nonlinear disturbance observer is proposed to reduce chattering. Through disturbance estimation for feedforward compensation, the improved sliding mode controller may take a smaller value for the switching gain without sacrificing disturbance rejection performance. Simulation results are provided to confirm the effectiveness of the proposed approach.     

Fault tolerant control for a class of uncertain chaotic systems with actuator saturation

This paper studies the fault tolerant control problem for a class of uncertain chaotic systems via sliding mode control. Both actuator faults and saturation are considered. Under an actuator redundancy assumption, an important lemma is first given and proved to find a lower bound of fault information and saturation degree. Then an adaptive sliding mode controller is designed to guarantee locally asymptotical stability of synchronization error. Compared with existing literature, an obvious relationship between actuator fault information and stability region is revealed. An improved strategy is also proposed to reduce conservativeness when estimating stability region. Finally, a model of Chua’s circuit systems is used to demonstrate these results.     

Fuzzy adaptive dynamic surface control for a single-link flexible-joint robot

In this paper, a fuzzy adaptive controller is proposed for a single-link flexible-joint robot. Fuzzy logic systems are used to approximate unknown nonlinearities, and then a fuzzy state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping design with dynamic surface control (DSC) technique, a fuzzy adaptive output-feedback backstepping control approach is developed. It is proved that all the signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and both the observer and tracking errors converge to a small neighborhood of the origin by appropriate choosing the design parameters. The simulation results are provided to demonstrate the effectiveness of the proposed controller. Two key advantages of our scheme are that (i)?the proposed control method does not require that the link velocity and actuator velocity of single-link flexible-joint robot be measured directly, and (ii)?the problem of ??explosion of complexity?? is avoided.     

Stabilizing the unstable periodic orbits of a chaotic system using model independent adaptive time-delayed controller

In this paper we deal with the control of chaotic systems. Knowing that a chaotic attractor contains a myriad of unstable periodic orbits (UPO’s), the aim of our work is to stabilize some of the UPO’s embedded in the chaotic attractor and which have interesting characteristics. First, using the input-to-state linearization method in conjunction with a time-delayed state feedback, we design a control signal that can achieve stabilization. Next, an adaptive time-delayed state feedback is proposed which shows at once efficiency and simplicity and circumvents the construction complexity of the first controller. Finally, we propose a reduced order sliding mode observer to estimate the necessary states for the design of an adaptive time delayed state feedback controller. This last controller has one main advantage, it in fact achieves UPO stabilization without using the system model. The efficacy of the proposed methods is illustrated by numerical simulations onto Chua’s system.     

Observer-based adaptive stabilization of the fractional-order chaotic MEMS resonator

Compared to the integer-order chaotic MEMS resonator, the fractional-order system can better model its hereditary properties and exhibit complex dynamical behavior. Following the increasing attention to adaptive stabilization in controller design, this paper deals with the observer-based adaptive stabilization issue of the fractional-order chaotic MEMS resonator with uncertain function, parameter perturbation, and unmeasurable states under electrostatic excitation. To compensate the uncertainty, a Chebyshev neural network is applied to approximate the uncertain function while its weight is tuned by a parametric update law. A fractional-order state observer is then constructed to gain unmeasured feedback information and a tracking differentiator based on a super-twisting algorithm is employed to avoid repeated derivative in the framework of backstepping. Based on the Lyapunov stability criterion and the frequency-distributed model of the fractional integrator, it is proved that the adaptive stabilization scheme not only guarantees the boundedness of all signals, but also suppresses chaotic motion of the system. The effectiveness of the proposed scheme for the fractional-order chaotic MEMS resonator is illustrated through simulation studies.     

A new adaptive fuzzy sliding mode observer for a class of MIMO nonlinear systems

In this paper, a new adaptive fuzzy sliding mode (AFSM) observer is proposed which can be used for a class of MIMO nonlinear systems. In the proposed algorithm, the zero-input dynamics of the plant could be unknown. In this method, a fuzzy system is designed to estimate the nonlinear behavior of the observer. The output of fuzzy rules are tuned adaptively, based on the observer error. The output connection matrix is used to combine the observer errors of individual subsystems. A robust term, which is designed based on the sliding mode theory, is added to the observer to compensate the fuzzy estimation error. The estimation error bound is adjusted by an adaptive law. The main advantage of the proposed observer is that, unlike many of the previous works, the measured outputs is not limited to the first entries of a canonical-form state vector. The proposed observer estimates the closed-loop state tracking error asymptotically, provided that the output gain matrix includes Hurwitz coefficients. The chattering is eliminated by using boundary layers around the sliding surfaces and the observer convergence is proved using a Lyapunov-based approach. The proposed method is applied on a real multilink robot manipulator. The performance of the observer shows its effectiveness in the real world.     

Property and evolution of the running-in attractor in an actual dynamic system

In this paper, the issue of adaptive neural tracking control for uncertain switched multi-input multi-output (MIMO) nonstrict-feedback nonlinear systems with average dwell time is studied. The system under consideration includes unknown dead-zone inputs and output constraints. The uncertain nonlinear functions are identified via neural networks. Also, neural networks-based switched observer is constructed to approximate all unmeasurable states. By means of the information for dead-zone slopes and barrier Lyapunov function (BLF), the problems of dead-zone inputs and output constraints are tackled. Furthermore, dynamic surface control (DSC) scheme is employed to ensure that the computation burden is greatly reduced. Then, an observer-based adaptive neural control strategy is developed on the basis of backstepping technique and multiple Lyapunov functions approach. Under the designed controller, all the signals existing in switched closed-loop system are bounded, and system outputs can track the target trajectories within small bounded errors. Finally, the feasibility of the presented control algorithm is proved via simulation results.

     

A differential flatness theory approach to observer-based adaptive fuzzy control of MIMO nonlinear dynamical systems

The paper proposes a solution to the problem of observer-based adaptive fuzzy control for MIMO nonlinear dynamical systems (e.g. robotic manipulators). An adaptive fuzzy controller is designed for a class of nonlinear systems, under the constraint that only the system’s output is measured and that the system’s model is unknown. The control algorithm aims at satisfying the $H_\infty $ tracking performance criterion, which means that the influence of the modeling errors and the external disturbances on the tracking error is attenuated to an arbitrary desirable level. After transforming the MIMO system into the canonical form, the resulting control inputs are shown to contain nonlinear elements which depend on the system’s parameters. The nonlinear terms which appear in the control inputs are approximated with the use of neuro-fuzzy networks. Moreover, since only the system’s output is measurable the complete state vector has to be reconstructed with the use of a state observer. It is shown that a suitable learning law can be defined for the aforementioned neuro-fuzzy approximators so as to preserve the closed-loop system stability. With the use of Lyapunov stability analysis, it is proven that the proposed observer-based adaptive fuzzy control scheme results in $H_{\infty }$ tracking performance.     

Actuator fault diagnosis for uncertain T–S fuzzy systems with local nonlinear models

This article investigates the problem of fault diagnosis (FD) for a class of nonlinear state-feedback control systems subject to parameter uncertainties. The considered nonlinear systems are described by T–S fuzzy models with local nonlinear parts and uncertain grades of membership. First, a general actuator fault model is proposed, which considers bias faults and gain faults. Then, a switching technique is introduced to address the unknown membership functions, external disturbances, faults, and their coupling. Furthermore, an adaptive FD observer design method combined with the switching technique is proposed to estimate the occurred actuator fault. It is noted that the obtained fault errors converge exponentially to zero. Finally, a numerical example of NSV reentry dynamic model is given to confirm the effectiveness of the new results.     

航天器有限时间饱和姿态跟踪控制

针对刚体航天器系统,对存在模型不确定性、外界干扰力矩和控制器饱和等条件下的姿态跟踪控制问题进行了研究。首先,考虑未知模型不确定性和外界干扰,且总干扰上界为未知常数,结合快速非奇异终端滑模、快速终端滑模趋近律以及辅助系统构造了基本的鲁棒有限时间饱和控制器,并通过辅助系统直接补偿了控制器饱和;其次,针对系统总干扰具有多项式上界的情形,进一步结合自适应控制算法,对其上界函数中的未知参数进行在线估计,并设计了自适应有限时间饱和控制器。同时,基于Lyapunov稳定性理论证明了所提出控制算法的有限时间收敛特性。最后,通过数值仿真验证所提出控制算法的控制效果,在两种控制器作用下姿态的跟踪精度分别为5×10-5和1×10-5,证明了所提出控制算法的有效性。     

Event-triggered finite-time resilient control for switched systems: an observer-based approach and its applications to a boost converter circuit system model

Under an event-triggered communication scheme (ETCS), this note focuses on the observer-based finite-time resilient control problem for a class of switched systems. Different from the existing finite-time problems, not only the problem of finite-time boundedness (FTBs) but also the problem of input-output finite-time stability (IO-FTSy) are considered in this paper. To effectively use the network resources, an ETCS is formulated for switched systems. Considering that not all the states could be measured, thus an event-triggered observer is constructed, and then, an observer-based resilient controller is devised, which robustly stabilizes the given systems in the meaning of finite-time control. Based on time-delay method and Lyapunov functional approach, interesting results are derived to verify the properties of the FTBs and the IO-FTSy of the event-triggered (ET) closed-loop error switched systems. All the matrix inequalities can be converted to linear matrix inequalities (LMIs) so as to simultaneously obtain the controller gain and observer gain. Finally, the applicability of the proposed control scheme is verified via a boost converter circuit system.     

Adaptive fuzzy output feedback control of uncertain nonlinear systems with nonsymmetric dead-zone input

In this paper, we present an adaptive control scheme for a class of uncertain nonlinear system with unknown nonsymmetric dead-zone nonlinearity. It is assumed that the system states are unmeasurable. Therefore, an observer is designed to estimate those unmeasured states. The controller is designed by using the backstepping control design procedure. The proposed adaptive scheme requires only the information that the dead-zone slopes are bounded. The new control scheme ensures bounded-error trajectory tracking and the boundedness of all the signals in the closed-loop. The feasibility is investigated by an illustrative simulation example.     

Adaptive control of a chaotic permanent magnet synchronous motor

This paper proposes a simple adaptive controller design method for a chaotic permanent magnet synchronous motor (PMSM) based on the sliding mode control theory which has given an effective means to design robust controllers for nonlinear systems with bounded uncertainties. The proposed sliding mode adaptive controller does not require any information on the PMSM parameter and load torque values, thus it is insensitive to model parameter and load torque variations. Simulation results are given to verify that the proposed method can be successfully used to control a chaotic PMSM under model parameter and load torque variations.     

Adaptive fuzzy output-feedback control of uncertain SISO nonlinear systems

The output-feedback control problem of a class of uncertain SISO nonlinear systems is investigated based on an indirect adaptive fuzzy approach. Because the system states are not required to be available for measurement, an observer is designed to estimate the system states. Compared with the existing results in the observer design, the main advantages of the proposed adaptive fuzzy output-feedback control approach are as follows: (1) It does not require to assume that the sign of the control gain coefficient is known and Nussbaum-gain technique is utilized to control the nonlinear systems with both the unknown control direction and the unmeasured states; (2) The observer in this paper is designed for the states rather than the tracking errors, then it is convenient to compute; (3) The controller singularity problem is perfectly avoided. The stability of the closed-loop system is analyzed by using Lyapunov method. A simulation example is given to verify the feasibility of the proposed approach.     

Fault-tolerant sliding mode attitude control for flexible spacecraft under loss of actuator effectiveness

In this paper, a novel fault-tolerant attitude control synthesis is carried out for a flexible spacecraft subject to actuator faults and uncertain inertia parameters. Based on the sliding mode control, a fault-tolerant control law for the attitude stabilization is first derived to protect against the partial loss of actuator effectiveness. Then the result is extended to address the problem that the actual output of the actuators is constrained. It is shown that the presented controller can accommodate the actuator faults, even while rejecting external disturbances. Moreover, the developed control law can rigorously enforce actuator-magnitude constraints. An additional advantage of the proposed fault-tolerant control strategy is that the control design does not require a fault detection and isolation mechanism to detect, separate, and identify the actuator faults on-line; the knowledge of certain bounds on the effectiveness factors of the actuator is not used via the adaptive estimate method. The associated stability proof is constructive and accomplished by the development of the Lyapunov function candidate, which shows that the attitude orientation and angular velocity will globally asymptotically converge to zero. Numerical simulation results are also presented which not only highlight the ensured closed-loop performance benefits from the control law derived here, but also illustrate its superior fault tolerance and robustness in the face of external disturbances when compared with the conventional approaches for spacecraft attitude stabilization control.     

Stabilization control for offshore steel jacket platforms with actuator time-delays

This paper is concerned with the stabilization control for the offshore steel jacket platforms subject to wave-induced force. Two state feedback stabilization control schemes are proposed to reduce the vibration amplitudes of the systems. One scheme is that for the systems without actuator time-delay, a state feedback controller is designed. Compared with the nonlinear controller, both the control force and the vibration amplitudes of the systems under the state feedback controller are much reduced; and compared with the dynamic output feedback controller and the integral sliding mode controller, the required control force under the state feedback controller are significantly reduced. The other scheme is that based on the integral inequality approach, a delay-dependent state feedback controller, which can be solved by using the cone complementarity algorithm, is developed to control the systems with actuator time-delays. Compared with the state feedback controller, the delay-dependent state feedback controller is less conservative with actuator time-delays. In addition, it is capable of improving the control performance of the offshore platforms significantly, which are illustrated by simulation results.     

Velocity-based tuning of degree of homogeneity for finite-time stabilization and fault tolerant control of an ROV in the presence of thruster saturation and rate limits

This paper introduces a homogeneous controller along a fixed-time state and fault observer for finite-time stabilization and fault accommodation of a remotely-operated vehicle in the presence of actuator saturation and rate limits. For this, a novel tuning algorithm is improvised for manipulating the degree of homogeneity in homogeneous controllers to effectively acquire different properties from the overall control system. The tuning of degree of homogeneity is based on vehicle’s velocity. The proposed algorithm results in a switching-type controller, which undergoes three different stages during the operation, to eliminate the sensitivity of conventional finite-time and fixed-time controllers to large initial errors in the presence of thruster constraints. In addition, a new fixed-time fault and state observer is designed for the realization of output feedback control and fault tolerance by combining a fixed-time state observer with a fault estimation unit. In contrast to conventional extended-state observers, this observer considers the dynamics of the thruster system in its formulation so that better performance can be provided for the control system upon thruster failures. Control allocation is utilized to accommodate thruster failures and faults and to take account of thruster saturation and rate limits. Stability analyses are carried out for the overall control system and the proposed observer. It is shown that the closed-loop control system would be globally finite-time stable. The state estimation subsystem is fixed-time stable and the fault estimation unit is input-to-state stable. Simulations are carried out and comparisons are made with several finite-time and fixed-time controllers to outline the advantages of the proposed homogeneous controller and the benefits of the overall fault-tolerant control system.

     

Adaptive terminal sliding mode control for anti-synchronization of uncertain chaotic systems

This paper presents an adaptive terminal sliding mode control method for anti-synchronization of uncertain chaotic systems. By fusion of the terminal sliding mode control and the adaptive control techniques, a robust controller is designed so that the states tracking error can reach the terminal sliding mode surface and converge to zero in a finite time. Finally, some simulation results are included to demonstrate the effectiveness and the feasibility of the proposed anti-synchronization scheme.