Neural-network-based fault-tolerant control for nonlinear systems subjected to faults and saturations

This paper investigates a novel strategy which can address the fault-tolerant control (FTC) problem for nonlinear strict-feedback systems containing actuator saturation, unknown external disturbances, and faults related to actuators and components. In such method, the unknown dynamics including faults and disturbances are approximated by resorting to Neural-Networks (NNs) technique. Meanwhile, a back-stepping technique is employed to build a fault-tolerant controller. It should be stressed that the main advantage of this strategy is that the NN weights are updated online based on gradient descent (GD) algorithm by minimizing the cost function with respect to NNs approximation error rather than regarding weights as adaptive parameters, which are designed according to Lyapunov theory. In addition, the convergence proof of NN weights and the stability proof of the proposed FTC method are given. Finally, simulation is performed to demonstrate the effectiveness of the proposed strategy in dealing with unknown external disturbances, actuator saturation and the faults related to the components and actuators, simultaneously.     

Synchronous control of multiple electrohydraulic actuators under distributed switching topologies with lumped uncertainty

A leader-following synchronous control is proposed in multiple electrohydraulic actuators (MEHAs) under distributed switching topologies to guarantee the follower electrohydraulic actuators (EHAs) tracking the leader motion. Each EHA has a 3-orders nonlinear dynamics with lumped uncertainties involving uncertain hydraulic parameters and unknown external load. Then a quasi-synchronization controller together with a high-gain disturbance observer is designed by Lyapunov techniques to guarantee the synchronous errors asymptotically convergence to a zero neighborhood. Finally, the effectiveness of the proposed quasi-synchronous controller is verified by both simulation and experimental bench such that the finite EHA nodes achieve leader-following synchronous motion under distributed switching topologies.     

Substructural control of fuzzy nonlinear flexible structures

It is advantageous to use the substructural and/or decentralized techniques in structural control to save on computations and time. In this paper, a generalized substructural approach is presented in the control of fuzzy nonlinear flexible structures with discrete sensors/actuators. The substructural control scheme is developed using the static condensation technique together with the LQG control method. The subcontrollers and subobservers designed at substructure levels are used to assemble the global controller and observer for the whole structure. Nonlinear effects are included in the structural formulations and a fuzzy methodology is adopted for handling the imprecision present in the structure modeling. The nonlinear and fuzzy schemes are applied to one structural control problem to illustrate the accuracy and capability of the substructural control technique.     

Distributed secure consensus control of nonlinear multi-agent systems under sensor and actuator attacks

In this paper, we focus on an output secure consensus control issue for nonlinear multi-agent systems (MASs) under sensor and actuator attacks. Followers in an MAS are in strict-feedback form with unknown control directions and unknown dead-zone input, where both sensors and nonlinear characteristics of dead-zone in actuators are paralyzed by malicious attacks. To deal with sensor attacks, uncertain dynamics in individual follower are separated by a separation theorem, and estimation parameters are introduced for compensating and mitigating the influence from adversaries. The influence from actuator attacks are treated as a total displacement in a dead-zone nonlinearity, and an upper bound, as well as its estimation, is introduced for this displacement. The dead-zone nonlinearity, sensor attacks and unknown control gains are gathered together regarded as composite unknown control directions, and Nussbaum functions are utilized to address the issue of unknown control directions. A distributed secure consensus control strategy is thus developed recursively for each follower in the framework of surface control method. Theoretically, the stability of the closed-loop MAS is analyzed, and it is proved that the MAS achieves output consensus in spite of nonlinear dynamics and malicious attacks. Finally, theoretical results are verified via a numerical example and a group of electromechanical systems.     

Decentralized adaptive neural control for interconnected stochastic nonlinear delay-time systems with asymmetric saturation actuators and output constraints

This paper investigates the problem of decentralized adaptive backstepping control for a class of large-scale stochastic nonlinear time-delay systems with asymmetric saturation actuators and output constraints. Firstly, the Gaussian error function is employed to represent a continuous differentiable asymmetric saturation nonlinearity, and barrier Lyapunov functions are designed to ensure that the output parameters are restricted. Secondly, the appropriate Lyapunov–Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions, and the neural networks are employed to approximate the unknown nonlinearities. At last, based on Lyapunov stability theory, a decentralized adaptive neural control method is proposed, and the designed controller decreases the number of learning parameters. It is shown that the designed controller can ensure that all the closed-loop signals are 4-Moment (or 2 Moment) semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges to a small neighborhood of the origin. Two examples are provided to show the effectiveness of the proposed method.     

Output feedback control of electro-hydraulic servo actuators with matched and mismatched disturbances rejection

In this paper, two output feedback controllers are proposed for motion control of double-rod electro-hydraulic servo actuators with matched and mismatched disturbances rejection. All of them employ an linear extended state observer (LESO) to achieve real-time estimates of the unmeasured system states and matched disturbance, and a nonlinear disturbance observer (NDO) to estimate the largely unknown mismatched disturbance at the same time. Thus, the disturbances are compensated via their online estimates in a feedforward way when implementing the resulting control algorithms, respectively. Furthermore, a continuously differentiable friction model is employed to compensate the majority of nonlinear friction existing in the system and reduce the burden of the NDO. Specially, one of the proposed control schemes utilizes model-based compensation terms depending on the desired trajectory to be tracked instead of the estimated system states. By doing this, online computation burden can be reduced. The stability of the whole closed-loop system under each control scheme is guaranteed by theoretical analysis. Moreover, the applicability of each control scheme are validated by experiments in different working conditions.     

A novel technique for optimal placement of piezoelectric actuators on smart structures

The problem of positioning of actuators and sensors on smart materials has been a point of interest in recent years. This is due to the fact that in many practical applications there are limitations in space, weight, etc. of the smart structures, which make the problem of positioning more complex. In addition, it is required that the actuators/sensors have the best possible performance. The development of smart structures technology in recent years has provided numerous opportunities for vibration control applications. The use of piezoelectric ceramics or polymers has shown great promise in the development of this technology. The employment of piezoelectric material as actuators in vibration control is beneficial because these actuators only excite the elastic modes of the structures without exciting the rigid-body modes. This is important since very often only elastic motions of the structures are needed to be controlled. The purpose of this paper is to introduce a novel approach developed for optimizing the location of piezoelectric actuators for vibration suppression of flexible structures. A flexible fin with bonded piezoelectric actuators is considered in this study. The frequency response function (FRF) of the system is then recorded and maximization of the FRF peaks is considered as the objective function of the optimization algorithm to find the optimal placement of the piezoelectric actuators on the smart fin. Three multi-layer perceptron neural networks are employed to perform surface fitting to the discrete data generated by the finite element method (FEM). Invasive weed optimization (IWO), a novel numerical stochastic optimization algorithm, is then employed to maximize the weighted summation of FRF peaks. Results indicate an accurate surface fitting for the FRF peak data and an optimal placement of the piezoelectric actuators for vibration suppression is achieved.     

我国水声换能器技术研究进展与发展机遇

概要评述我国水声换能器技术方面近20年的研究进展,包括应用新型功能材料、提出新的设计概念及新结构、改进工艺技术等。重点从低频换能器、高频宽带换能器、深水换能器、矢量水听器等4个技术方向进行介绍,最后对水声换能器技术领域未来所面临的挑战和发展机遇谈些认识。     

Vibration control of a membrane antenna structure using cable actuators

This paper presents a control strategy of using cable actuators to control the vibration of a membrane antenna structure. The tension cables of the membrane antenna structure are used as actuators, the vibration of the structure can be suppressed by controlling the tension force in the cable actuators. First, the antenna structure with cable actuators is discretized by the finite element method (FEM), and governing equation of the whole structure is established. Then, a controller is designed based on the Lyapunov's stability theory, and the mechanism of this controller is studied through a simple single-degree-of-freedom (SDOF) system. The optimal placement of the cable actuators is also studied numerically in this paper. Simulation results indicate that vibration of the membrane antenna structure can be suppressed effectively by the cable actuators, and optimally placed cable actuators can produce better control effect with smaller control input.     

Adaptive output feedback fault tolerant control for uncertain nonlinear systems based on actuator switching

In this paper, an adaptive output feedback fault tolerant control (FTC) based on actuator switching is proposed for a class of single-input single-output (SISO) nonlinear systems with uncertain parameters and possible actuator failures, for which a set of healthy actuators are available as backups. While high-gain K-filters are utilized to estimate the unmeasured states, an adaptive control law is designed to compensate for the parameter uncertainties and certain actuator failures, an actuator switching strategy based on a set of appropriately designed monitoring functions (MFs) is proposed to tackle those serious actuator failures, make tracking error satisfy prescribed transient and steady-state performance and guarantee closed-loop signal boundedness.     

An adaptive actuator failure compensation scheme for a class of nonlinear MIMO systems

This paper develops an adaptive actuator failure compensation scheme for control of a class of nonlinear multi-input–multi-output systems with redundant actuators subject to uncertain failures. The design method is to estimate the failure pattern parameters and the failure signal parameters first, and then use the parameter estimates to construct the adaptive failure compensation controller, the control law calculation is done simultaneously with parameter estimation without explicit failure detection. Closed-loop signal boundedness and asymptotic output tracking, despite the actuator failure uncertainties, are ensured analytically and verified by simulation results from its application to attitude control of a near space vehicle dynamic model.     

Type-B Nussbaum function-based fault-tolerant control for a class of strict-feedback nonlinear systems

This paper studies the fault-tolerant control (FTC) problem of a class of strict-feedback nonlinear systems. First, we put forward a key theorem which shows that type-B Nussbaum functions can be extended to the cases containing multiple Nussbaum functions in the same Lyapunov inequality under certain conditions. Then, by using the techniques of Nussbaum functions and adaptive control, a new fault-tolerant control scheme is proposed. Compared with the previous work, this paper considers unknown time-varying control coefficients and unknown time-varying fault coefficients of actuators. It is proved that all the signals of the closed-loop system are globally bounded and the tracking error converges to zero asymptotically. Finally, simulations are provided to verify the effectiveness of the proposed control scheme.     

Time-varying formation control for nonlinear multi-agent systems against actuator attacks

The formation control problem with time-varying characteristics is investigated for the time-delayed nonlinear multi-agent systems against actuator attacks. A neural-network-based adaptive control method is constructed to achieve the desired control objective, which is outputs of the followers can complete the desired transformation of formation configuration. To eliminate the influence of malicious attacks on the actuators, an actuator attacks defense strategy is proposed to resist false data injection attacks occurred in the actuator. The uncertainty of the dynamics caused by nonlinear functions is resolved by the neural-network approximate method. The problem of the time delay is handled by an improved Lyapunov-Krasovskii functional approach, which can also avoid the singularity problem that may occur during the construction of the control method. Based on the Lyapunov stability theory, it is proved that all signals of closed-loop systems are semi-globally stable and the formation error can converge to a small neighborhood of the origin. Finally, the results of simulations are provided to verify the feasibility of the theoretical analysis and the effectiveness of the proposed control method.     

Active vibration control of an elastically connected double-string continuous system

The paper deals with the optimal control of a distributed host structure consisting of two elastically connected complex continuous double-string system and subjected to certain excitation load. Investigation of the behavior of such system is of great theoretical and practical importance. A technique is proposed to actively damp out the undesired vibrations in the structures by a combination of applied actuators and displacement feedback gains. Two performance measures, involving energies at the terminal time as well as applied and feedback control efforts, are introduced. The optimality conditions of the applied actuators are derived by using the method of eigenfunction expansion and calculus of variations. The feedback parameters are numerically determined from the solution of a minimization problem. The proposed approach is illustrated by a numerical example involving a system which consists of two strings subjected to a continuous load.     

Adaptive controller design for spacecraft formation flying using sliding mode controller and neural networks

A spacecraft formation flying controller is designed using a sliding mode control scheme with the adaptive gain and neural networks. Six-degree-of-freedom spacecraft nonlinear dynamic model is considered, and a leader–follower approach is adopted for efficient spacecraft formation flying. Uncertainties and external disturbances have effects on controlling the relative position and attitude of the spacecrafts in the formation. The main benefit of the sliding mode control is the robust stability of the closed-loop system. To improve the performance of the sliding mode control, an adaptive controller based on neural networks is used to compensate for the effects of the modeling error, external disturbance, and nonlinearities. The stability analysis of the closed-loop system is performed using the Lyapunov stability theorem. A spacecraft model with 12 thrusts as actuators is considered for controlling the relative position and attitude of the follower spacecraft. Numerical simulation results are presented to show the effectiveness of the proposed controller.     

Continuous finite-time extended state observer design for electro-hydraulic systems

This paper presents a novel framework towards a time-varying observer design for nonlinear electro-hydraulic actuators. The key idea of this paper is to employ a positive-increasing function associated with the observer objective to improve the estimation performance. An extended state observer is designed to estimate the full state variables and the uncertainties without any knowledge about the upper bounds of the uncertainties and their derivatives. First, without loss of generality, the system model is divided into three parts, and the extended state observers are designed for each part, independently. Then, the time-varying gains of each observer are designed to make the observation errors uniformly bounded. Finally, the simulated performance of the presented framework is compared with two valid approaches including high-order sliding mode and high-gain extended state observers.     

Programmable deformation of patterned bimorph actuator swarm

Graphene-based actuators featuring fast and reversible deformation under various external stimuli are promising for soft robotics. However, these bimorph actuators are incapable of complex and programmable 3D deformation, which limits their practical application. Here, inspired from the collective coupling and coordination of living cells, we fabricated a moisture-responsive graphene actuator swarm that has programmable shape-changing capability by programming the SU-8 patterns underneath. To get better control over the deformation, we fabricated SU-8 micropattern arrays with specific geometries and orientations on a continuous graphene oxide film, forming a swarm of bimorph actuators. In this way, predictable and complex deformations, including bending, twisting, coiling, asymmetric bending, 3D folding, and combinations of these, have been achieved due to the collective coupling and coordination of the actuator swarm. This work proposes a new way to program the deformation of bilayer actuators, expanding the capabilities of existing bimorph actuators for applications in various smart devices.     

Integrated design of switching control and mobile actuator/sensor guidance for a linear diffusion process

This paper is concerned with the exponential stabilization problem for a class of diffusion processes described by a linear parabolic partial differential equation (PDE) using mobile collocated actuators and sensors. Each collocated actuator/sensor pair is capable of moving within the respective spatial domain divided in advance and a mode indicator function is employed to indicate the different modes for all actuator/sensor pairs according to whether each actuator/sensor pair is static or mobile. By utilizing Lyapunov direct method, an integrated design of switching controllers and mobile actuator/sensor guidance laws for the diffusion process is developed such that the resulting closed-loop system is exponentially stable. Finally, numerical simulations are presented to illustrate the effectiveness of the proposed design method.     

Stochastic fault tolerant control of networked control systems

A problem of stabilization about uncertain networked control systems (NCSs) with random but bounded delays is discussed in this paper. By using augmented state-space method, this class of problems can be modeled as discrete-time jump linear systems governed by finite-state Markov chains. A new switched model based on probability is proposed to research problems of reliable control when actuators become ageing or partially disabled. Using improved V-K iteration algorithm, a class of reliable controllers are designed to make systems asymptotically mean square stable under several stochastic disturbances such as random time-delay and stochastic actuator failure and the maximal redundancy degree is given through this method.