Robust Adaptive Fault-tolerant Control Research Articles

Symmetric Collaborative Fault-Tolerant Control of Multi-Intelligence under Long-Range Transmission in Air–Ground Integrated Wireless High-Mobility Self-Organizing Networks

With the continuous development and progress of wireless self-organizing network communication technology, how to carry out long-distance cooperative control of multiple intelligences under the framework of an air–ground integrated wireless high-mobility self-organizing network has become a hot and difficult topic that needs to be solved urgently. This paper takes the air–ground integrated wireless high-mobility self-organizing network system as the basic framework and focuses on solving the long-distance cooperative fault-tolerant control of multi-intelligent bodies and the topological stability of a wireless mobile self-organizing network. To solve the above problems, a direct neural network with a robust adaptive fault-tolerant controller is designed in this paper. By constructing a symmetric population neural network model and combining it with the Lyapunov stabilization criterion, the system feedback matrix K has the ability of autonomous adaptive learning, and symmetrically distorts, rotates, or scales the training data to instantly adjust the system’s fault-tolerant corrections and adaptive adjusting factors to resist the unknown disturbances and faults, to achieve the goals of multi-intelligent body stable control and the stable operation of a wireless high-mobility self-organizing network topology. Simulation results show that with the feedback adjustment of the multi-system under the designed controller, the multi-system as a whole has good fault-tolerant performance and autonomous learning approximation performance, and the tracking error asymptotically converges to zero. The experimental results show that the multi-flight subsystems fly stably, the air–ground integrated wireless high-mobility self-organizing network topology has good stability performance, and the maximum relative improvement of the topology stability performance is 50%.

Robust adaptive fault tolerant control for nonlinear systems with actuator failure and mismatched disturbance

In this paper, a class of nonlinear systems with mismatched disturbance and actuator failure is investigated. A disturbance observer is proposed to estimate the disturbance first and the error of the estimation converges to zero exponentially. By introducing an integral sliding mode surface, the disturbance observer-based integral sliding mode fault tolerant control scheme is proposed to attenuate the disturbance and guarantee the stability of the system. In particular, the control law is designed for decoupling the partial disturbance and attenuating the disturbance that cannot be decoupled. Finally, two examples are given to illustrate the effectiveness of the proposed method.

Robust adaptive fault-tolerant control for path maneuvering of autonomous surface vehicles with actuator faults based on the noncooperative game strategy

This paper investigates a parameterized path-guided following/maneuvering control problem of an autonomous surface vehicle (ASV) subject to actuator faults via a noncooperative game strategy. Unlike the existing path maneuvering control methods, the noncooperative game of this paper includes two sub-games. On one hand, the path update is considered to be against the effort of kinematic control. On the other hand, the kinetic control is considered to be against the total disturbances consisting of actuator faults and external disturbances. A robust adaptive fault-tolerant path maneuvering controller is designed based on a noncooperative game approach. Specifically, we design a kinematic control law using an improved dynamic surface control approach to achieve the geometric objective. An improved neural predictor is constructed, in which a concurrent learning-based adaptation is designed to identify unknown fault coefficients. A path update law and a kinetic control law are calculated to cover noncooperative games by using an adaptive dynamic programming approach. Theoretical analysis shows that the closed-loop system is input-to-state stable, and the proposed method can meet the geometric objective, the dynamic objective, and the fault-tolerant objective. Finally, simulation results demonstrate the efficacy of the proposed robust adaptive fault-tolerant control method for path maneuvering.

Adaptive fault-tolerant control based on linear matrix inequalities for actuator failures in steer-by-wire system

Aiming at the vehicle stability and safety problems caused by the actuator failure of Steer-By-Wire (SBW) system, a two-layer control strategy combining the Performance-Preserving Robust Control (PPRC) and Adaptive Fault-Tolerant Control (AFTC) using the Linear Matrix Inequality (LMI) processing is proposed. The PPRC of the SBW system by tracking the ideal reference model is the first layer of control, the vehicle is robust to speed and low failure rate defects of the SBW system actuator within the performance range of the SBW system, and the side slip angle ([Formula: see text]) and yaw rate ([Formula: see text]) of the vehicle can approach optimal values; The second layer of control: AFTC is added to the above PPRC based on the online estimation of the final failure, when a high failure rate failure in the actuator of the SBW system occurs and the performance limit of the PPRC is exceeded, this allows the vehicle state in the high failure rate failure mode of the actuator to still track the specified ideal reference state. Compared with the traditional Fault-Tolerant Control (FTC) that requires Fault Detection and Isolation (FDI), the control method used in this paper does not require accurate fault information, but only uses the system state change generated by the fault as the information to automatically adjust the control input, which can still achieve the purpose of stabilizing the whole SBW system when the actuator fails.

Vibration Suppression of an Input-Constrained Wind Turbine Blade System

During the actual wind power generation process, wind turbines are often affected by side effects such as blade vibrations, input constraints, and actuator faults. This can lead to a reduction in power generation efficiency and even result in unforeseen losses. This study discusses a robust adaptive fault-tolerant boundary control approach to address the issues of input-constrained and actuator-fault problems in wind turbine blade vibration control. By employing projection mapping techniques and hyperbolic tangent functions, a novel robust adaptive controller based on online dynamic updates is constructed to constrain vibrations, compensate for unknown disturbance upper bounds, and ensure the robustness of the coupled system. Additionally, considering the possibility of actuator faults during the control process, a fault-tolerant controller is proposed to effectively suppress elastic vibrations in the wind turbine blade system even in the presence of actuator faults. The effectiveness of the proposed controller is validated through numerical simulations.

Event-triggered adaptive robust fault-tolerant control for a class of uncertain switched nonlinear systems

In this paper, the adaptive robust fault-tolerant control problem for a class of switched nonlinear systems with parameter uncertainty, disturbances and actuator failures is concerned based on event-triggered control strategy. The adaptive laws based on state-dependent switched strategy are designed to eliminate the effects of actuator faults and parameter uncertainties by using the estimations of the unknown upper bounds of uncertain parameters. Then, the robust fault-tolerant technique and multiple Lyapunov functions method are used, the designed controller can guarantee that all signals of the switched closed-loop systems are uniformly bounded. Meanwhile, the desired performance of the systems is promised. Finally, the simulation results are given to illustrate the effectiveness of the proposed design method.

Fault tolerant attitude control of under-actuated spacecraft: Theory and experiment

This paper investigates fault tolerant attitude control theory and experiment for under-actuated spacecraft with one reaction wheel completely broken and two others suffering actuator faults of partial loss of effectiveness or bias. A non-smooth robust adaptive fault tolerant control law is proposed under the zero-momentum and input saturation conditions. It shows that the available reaction wheels need to produce sufficient control torque for the fault tolerance. Such a new control method is implemented in a semi-physical simulation system of an air-bearing platform. Experimental results show the effectiveness of the proposed method in spacecraft practical engineering.

ROBUST ADAPTIVE FAULT-TOLERANT CONTROL BASED ON GBF-CMAC NEURAL NETWORK FOR LOW-ALTITUDE UAV, 267-276.

For the problem that the attitude of the low-altitude UAV issusceptible to the external environment disturbance and actuatorfailures, a composite control strategy is designed to combine theGaussian basis function cerebellar model articulation controller(GBF-CMAC) neural network with robust adaptive fault-tolerantcontrol (FTC).

Robust adaptive fixed-time control for a class of nonlinear systems with actuator faults

This paper addresses the output tracking problem of adaptive fixed-time fault-tolerant control for a class of nonlinear systems. In particular, we focus on two types of actuator faults: lock-in-place and loss of effectiveness. Specifically, a robust adaptive fault-tolerant controller is designed to compensate for the effect of actuator faults. By applying the classical backstepping design algorithm and fixed-time control theory, an adaptive fixed-time controller is developed, ensuring that the tracking error converges into a small neighbourhood around the origin within a fixed time where the convergence time is independent of initial conditions. Theoretical analysis and simulation outcomes prove that the closed-loop system is fixed-time stable and all signals are bounded by choosing the parameters appropriately. The effectiveness and feasibility of the presented control scheme are verified through the simulation results.

Bidirectional robust and fault-tolerant [formula omitted] non-sensitive compensation filter controller based on amorphous flattened air-to-ground wireless self-assembly system

With the cross-fertilization development of automatic control technology, electronic science and technology, and wireless communication technology, a single filter is no longer able to solve the fault problem of the control system and communication system simultaneously and in a balanced manner. In this paper, we design a bidirectional robust fault-tolerant H∞ non-sensitive compensation filter controller based on the robust adaptive fault-tolerant control algorithm, and further optimize the fault-tolerance correction factor and robust adaptive factor by the LMI (Linear-Matrix-Inequation) method under the regulation of the feedback matrix K, so that the system estimation error can converge to zero asymptotically. It can simultaneously solve the optimization problems of unknown faults (including external disturbances, partial failure of internal actuators, and random interruptions) of the self-assembling node and the acquisition of SNR (Signal-Noise-Ratio) by wireless self-assembling nodes. The simulation results show that the system eventually tends to be asymptotically stable in all performance metrics with feedback adjustment under the designed filter controller, and the estimation error asymptotically tends to zero. The robustness and fault tolerance performance indicators are good against external disturbances and internal actuator failure of the wireless self-assembling network node. The control rate of the network system all increases significantly as the total feedback constraint rate of the system increases, allowing the system to eventually obtain the optimal SNR. The experimental results show that the network nodes of the amorphous flat wireless air-to-ground self-organizing network system can change flexibly and adaptively with the change of scenes, and the wireless communication distance between the network nodes is relatively improved by 86.36%, 110%, and 79.91%, and the loop success rate appears to be stable fluctuation interval, which can greatly improve the survival rate of the self-organizing network nodes. This paper is of great research significance for further realizing the long-spacing transmission of self-organizing nodes and laying the foundation for future low-altitude fly-by-wire research.

Analog Control Circuit Designs for a Class of Continuous-Time Adaptive Fault-Tolerant Control Systems.

This article is concerned with the robust adaptive fault-tolerant control (FTC) circuit designs for a class of continuous-time disturbed systems. A circuit realization method is investigated to convert the robust adaptive FTC control schemes into analog control circuits. An adaptive compensation control scheme against state-dependent and partially bounded actuator faults and disturbances is first developed to demonstrate the approach clearly, then its equivalent control circuits are implemented by using the circuit theory. Compared with simulation results achieved by MATLAB and professional circuit simulation software, the effectiveness of the proposed robust adaptive FTC circuits is validated by a rocket fairing system and a Chua's circuit system.

Robust adaptive fault-tolerant control for unmanned surface vehicle via the multiplied event-triggered mechanism

This paper investigates a novel robust adaptive fault-tolerant control algorithm for the path-following activity of the unmanned surface vehicle (USV) via the multiplied event-triggered mechanism. An improved multiplied event-triggered condition is designed by employing the estimate model with a concise form. Thus, the burden-some problem is released, especially for the channel from sensors to the controller. Besides, two discrete adaptive parameters are constructed to stabilize the perturbation caused by the gain constraint and actuator faults. The model uncertainties and the practical disturbance are compensated by utilizing neural networks (NNs) approximation, in which the weight updating is reduced with the robust neural damping technique. With the direct Lyapunov theorem, the semi-global uniformly ultimately bounded (SGUUB) stability can be guaranteed for the closed-loop system. Finally, both the simulation and the physical vehicle-based experiments are illustrated to verify the effectiveness of the algorithm.

Adaptive fault‐tolerant robust control based on radial basis function neural network for a class of mechanical systems with input constraints

AbstractIn this paper, a robust adaptive fault‐tolerant control (FTC) strategy based on hyperbolic tangent function is proposed for a class of mechanical systems with unknown disturbance and unknown nonlinear friction model. The robust adaptive FTC algorithm proposed in this paper can maintain the system performance even after partial failure occurs in the actuator. Different from the traditional fault‐tolerant control algorithms, the proposed algorithm uses the hyperbolic tangent function and a projection algorithm to limit the control input within a known upper bound. In addition, radial basis function neural network is used to approximate the unknown continuous nonlinear function that contains the friction model in the mechanical system. The control target of the system is realized; and the asymptotic stability of the closed‐loop system is proved via the Lyapunov direct method. Finally, the numerical simulation results also demonstrate the effectiveness of the designed controller.

Adaptive robust fault-tolerant control scheme for spacecraft proximity operations under external disturbances and input saturation

Adaptive robust fault-tolerant control scheme for spacecraft proximity operations under external disturbances and input saturation

Robust Adaptive Fault-tolerant Containment Control of Networked Heterogeneous Agent Systems with Multiple Active Leaders and Mismatched Affine Uncertainties

Robust Adaptive Fault-tolerant Containment Control of Networked Heterogeneous Agent Systems with Multiple Active Leaders and Mismatched Affine Uncertainties

Robust immersion and invariance adaptive fault-tolerant control of nonlinear systems with non-linearly parameterized faults

This paper presents a robust adaptive fault-tolerant control (FTC) scheme based on Immersion and Invariance (I&I) manifold method for a class of disturbed nonlinear systems on the occurrence of non-linearly parameterized (NLP) faults. The fault detection method based on adaptive observer is proposed firstly, and the fault tolerant controller for the NLP faults based on robustified I&I adaptation law is presented on the basis of nominal control law. Different from traditional adaptation law, the proposed robustified I&I adaptation law can not only eliminate the parameterized uncertainty but also shape the convergnce performance of the parameter estimates. The stability of the closed-loop system is rigorously analyzed. Numerical simulations are carried out to verify the effectiveness of the proposed scheme. • Different from linearly parameterized faults, a class of disturbed nonlinear systems on occurrence of non-linear parameterized (NLP) faults are considered in this paper. • A new robust adaptation law based on Immersion and Invariance manifold and non-certainty equivalence principle is proposed to shape the transient performance of the parameters convergence in the NLP faults. • Before a fault is detected, the nominal controller of the system can guarantee output tracking in the absence of fault and the stability of the system in the presence of faults. As the fault is detected, the fault-tolerant control (FTC) scheme can guarantee all the signals of the closed-loop systems are uniformly ultimately bounded and render the output tracking error converge to a small neighborhood of zero with satisfying transient performance.

Robust adaptive fault‐tolerant control using RBF‐based neural network for a rigid‐flexible robotic system with unknown control direction

AbstractIn this article, a radial basis function (RBF)‐based robust adaptive fault‐tolerant control (FTC) is developed for a class of rigid‐flexible robotic systems under actuator failures, unknown control direction, and uncertain external disturbances. The dynamics of the rigid‐flexible robotic over a vertical plane is governed by the hybrid ordinary differential equations–partial differential equations. The uncertain external disturbance is estimated via an RBF neural network. Meanwhile, the robust adaptive FTC law is utilized to follow the given joint angular and attenuate the vibration of the flexible structure in the case of actuator failures and unknown distributed disturbances. To handle the unknown control direction, the Nussbaum function is employed to robust FTC laws. By virtue of the Lyapunov direct approach, the trajectory tracking and vibration elimination for the controlled rigid‐flexible robotic system are proved and uniformly bounded in face of bounded external disturbances and unknown control directions. The efficacy of the developed control strategy is also illustrated via four comparison examples.

Adaptive robust fault-tolerant control for a two-slider synchronization system with a flexible beam

In this paper a novel adaptive robust fault-tolerant sync control method is proposed for a two-slider system where two sliders are constrained by a flexible beam. At first the dynamic models of sync motion system subject to external disturbances and actuator faults are derived. In order to avoid the shortcomings of truncated model, the model of flexible beam is described by using infinite dimensional equation. Then based on the models a novel disturbance observer and an adaptive fault-tolerant control law are designed. The disturbance observer is used to estimate and cancel external disturbances. The adaptive fault-tolerant control is used to deal with the partial loss of effectiveness faults. Lyapunov functional approach is used to prove that the closed-loop system with the proposed control laws is uniformly bounded stable. Finally, some simulation results display that the proposed control laws can obtain excellent sync performance in the present of external disturbances and actuator partial loss of effectiveness faults.

Fault tolerant consensus of multiple nonholonomic chained‐form systems with actuator and communication faults

AbstractThis article investigates the fault tolerant consensus problem of multiple nonholonomic chained‐form systems with both actuator and communication faults. The systems are enabled to follow a reference trajectory and realize practical consensus, by applying distributed reference state observers and robust adaptive fault tolerant control (FTC) strategies. The proposed state observers are robust to communication faults and can estimate the actual reference trajectory for each system. Based on such an observer, a robust adaptive FTC scheme is further provided to address actuator faults. A sine function is injected into the FTC law to relax the persistent excitation condition to avoid uncontrollability of the two‐input chained‐form system when one of reference control input tends to zero. Simulation result of wheeled mobile robots shows the effectiveness of proposed FTC methods.

Robust Adaptive Fault-Tolerant Tracking Control for Uncertain Linear Systems With Actuator Failures Based on the Closed-Loop Reference Model

This paper addresses the problem of robust adaptive fault-tolerant tracking control for a class of linear systems with parameter uncertainty, external disturbance, and actuator faults including loss of effectiveness, outage, and stuck. According to the online estimation information provided by adaptive mechanism, a fault-tolerant compensation controller is constructed for robust tracking of closed-loop reference model systems. Compared with the existing results, by introducing the closed loop reference model which provides the additional degree-of-freedom, the transient performance of the systems can be improved. It is shown that the signals of the resulting adaptive closed-loop systems are bounded and the tracking error converges to zero asymptotically. A simulation example is provided to verify the effectiveness of the proposed fault-tolerant design method.