Anti-saturation fault-tolerant control and disturbance rejection based on Fourier series observers under communication constraints

In AC microgrids (MGs), the required high control gain for dealing with control faults would reduce the robustness of the secondary control to communication constraints. To tackle with this problem, the subarea physical infrastructure of AC MGs and the two-layer secondary control framework are designed. For the physical infrastructure, the whole AC MG is divided into several areas, where each area is composed of a distributed generator (DG) and several geographical-close loads. Furthermore, by utilizing the advanced metering infrastructure (AMI), loads transmit the local load change information to the DG in the same area. Based on this physical infrastructure, a distributed event-triggered fixed-time fault-tolerant (ET-FTFT) secondary control framework is proposed in this paper to improve the resilience of the secondary control to sensor and actuator faults/attacks, and communication constraints, simultaneously. The adopted two-layer control framework is to decouple the communication constraints and control faults. The event-based strategy is adopted in the upper layer to reduce the communication burden and Zeno behavior can be evaded. Real-time simulations based on the NI-PXI real-time simulator validate the advantages of the distributed ET-FTFT secondary control framework, which are the better robustness to control faults, and the fixed-time convergence to improve the power quality.

Disturbance Rejection with Information Constraints: Performance Limitations of a Scalar System for Bounded and Gaussian Disturbances

In this paper, a fault tolerant control (FTC) method is presented for a class of the nonlinear networked control systems (NCSs) with communication constraints. Firstly, using Euler approximate method and Takagi-Sugeno (T-S) fuzzy model, a new nonlinear NCSs model is given. Considering the sensor faults and the actuator faults, a fault-tolerant control method is proposed for nonlinear NCSs, which is based on robust control theory and information scheduling. The control law is given via some LMIs. Finally, an example is used to illustrate the efficiency of the proposed technique.

The fault-tolerant control problem is investigated for a linear networked system subject to an additive actuator fault as well as random network delays and packet dropouts in the backward and forward channels. To deal with the adverse effects of the actuator fault as well as those communication constraints, an active compensation scheme combining active fault-tolerant control and predictive control is proposed based on the simultaneous estimation of the system state and actuator fault. The obtained closed-loop system is a randomly switched system with bounded round-trip time delays, and the corresponding closed-loop stability condition is derived by using a switched Lyapunov approach. Simulation results for a networked DC motor system are provided to verify the proposed method.

In this study, the synchronization tracking control problem for underwater teleoperation systems with output and communication constraints under actuator failure is investigated. To tackle this issue, an adaptive neural learning event-triggered fault-tolerant control scheme, incorporating backstepping design, an asymmetric Integral Barrier Lyapunov Function (AIBLF), neural networks, and adaptive techniques, is developed for the first time. First, AIBLF is incorporated into the design of virtual control variables so that the output of the remote robot never violates the safety constraint boundaries, which subsequently ensures the safety of underwater operations; Second, neural networks are utilized to estimate the inexact model and adaptive robust terms are designed to eliminate the negative effects of the neural network estimation bias and the compound uncertainty. Following this, adaptive techniques are utilized to deal with the unknown control gain problem arising from actuator failure and event-triggered control. Finally, simulation results validate the effectiveness of the developed approach.

Fault tolerant compensation strategy for stochastic distribution systems with communication constraints

In this work, we propose the adaptive state filter for networked control system (NCS) with random induced delay. Communication constraints such as packet losses, random induced delay and quantization problems may be missing possibly in reality certain observations. Therefore, the proposed approach in this work is used ensure estimation in networked control system. We will show also the adaptive state filter can be implemented in a Fault Tolerant Control (FTC). We used a LQG Control law in order to reject the effect of sequential faults. A simulation example illustrates the effectiveness of the method used.

This brief presents an active fault-tolerant predictive control method for the output tracking of networked control systems (NCSs) subject to random communication constraints as well as actuator and sensor faults. The system state and actuator/sensor faults are simultaneously estimated via an observer and then used to perform a fault-tolerant predictive controller. Thus, both faults and the communication constraints in the backward and forward channels are actively compensated. A closed-loop stability condition is obtained, which also guarantees a zero steady-state tracking error. Moreover, the separation principle for designing the observer-based controller holds. Finally, the numerical simulation for a mass-spring-damper system is conducted to illustrate the effectiveness of the proposed method.

Recently, distributed DC microgrids have gained prominence due to their modular design, scalability, and seamless integration with renewable energy sources. However, ensuring robust operation of distributed secondary control schemes remains challenging, particularly in the presence of unavoidable communication disruptions and parametric uncertainties encountered in practice. Most existing control strategies either assume ideal communication networks or address fault tolerance and communication constraints separately, which limits their applicability in realistic networked environments. This paper proposes an event-triggered fault-tolerant distributed secondary control framework for DC microgrids operating under communication faults. An embedded averaged model is incorporated to support fault-tolerant decision-making and to guide event-triggered communication updates. In addition, an auxiliary recovery mechanism is introduced, enabling neighboring converters to cooperatively compensate for information loss during communication interruptions without centralized supervision. Lyapunov-based stability analysis establishes boundedness and practical convergence of the closed-loop system under event-triggered updates and bounded disturbances while explicitly excluding Zeno behavior. The simulation results under communication fault scenarios demonstrate that the proposed approach achieves accurate DC bus voltage regulation with steady-state deviations below 1% while restoring proportional power sharing with an averaged error within 5%. The embedded model error remains bounded throughout the fault interval, and fault-tolerant control actions are triggered sparsely with well-separated inter-event times on the order of tens of milliseconds, thereby significantly reducing the communication burden. These results confirm the effectiveness and robustness of the proposed framework for the resilient operation of distributed DC microgrids under practical communication constraints.

The next generation aircraft engine control systems will be based on a distributed architecture, in which, the sensors and actuators will be connected to the controller through an engine area network. The advantages and challenges for implementing distributed engine control system are well discussed in public literature. Addition of an engine area network will introduce additional issues like network faults, network-induced delays and data loss. Although the communication protocol of the selected engine area network will have inherent fault diagnostic techniques to limit the data loss and time delay, these communication constraints will affect the performance of distributed engine control systems. Inflight fault diagnostics, onboard health management, fault-tolerant control and model-based control techniques are well studied for the current engine control systems. These diagnostic and control methodologies use an onboard engine model and depend on the accuracy of the tracking filter to estimate the measured and unmeasured parameters. The tracking filter is also used to update the engine model to match the actual engine characteristics. This paper studies the effect of network-induced time delays on model-based fault diagnostics. Design methodology for a parity relation based residual generator is presented. The proposed residual generator captures the time delay information and hence is more accurate than the conventional residual generator for detecting faults under a distributed framework. This paper also highlights the importance of including time delay information for model-based fault diagnostics and control.

In this paper, we consider a set up in which the plant and controller are local to each other, but are together driven by a remote reference signal that is transmitted through a finite-rate noiseless channel. When control must be done over a communication channel, there is a fundamental tradeoff between allowing enough time for reconstruction of signals over the channel and achieving performance in finite-time. Most work in the area of control under communication constraints have addressed infinite-horizon control objectives (e.g., stability, disturbance rejection). In this paper, we compute lower and upper bounds on worst-case performance for a finite-horizon tracking objective. We achieve the lower bound with a noncausal coding scheme and show that imposing causality on the coding scheme severly limits achievable performance. We illustrate how the bounds behave under various scenarios and show tradeoffs between time and performance accuracy

Disturbance rejection problem with communication constraints for the first order system is considered. The performance limitation of the control system is shown by describing the trade-off between channel capacity and control performance quantitatively. The optimal control performance can be achieved by the state observation based on the coding of state prediction error and control to cancel the state by the predicted value.

In this paper, we consider a set up in which the plant and controller are local to each other, but are together driven by a remote reference signal that is transmitted through a finite-rate noiseless channel. When control must be done over a communication channel, there is a fundamental tradeoff between allowing enough time for reconstruction of signals over the channel and achieving performance in finite-time. Most work in the area of control under communication constraints have addressed infinite- horizon control objectives (eg. stability, disturbance rejection). In this paper, we compute lower and upper bounds on worst-case performance for a finite-horizon tracking objective. We achieve the lower bound with a noncausal coding scheme and show how imposing causality on the coding scheme severely limits achievable performance. We illustrate how the bounds behave under various scenarios and show tradeoffs between time and performance accuracy.

In this paper, the active fault tolerant control problem of networked systems with sensor fault is studied. The network-induced delay treated as the round-trip time (RTT) delay and additive sensor fault are taken into consideration. A networked predictive active fault tolerant control (NPAFTC) scheme based on networked predictive control approach is proposed to eliminate the effect of the sensor fault and compensate for the network-induced delay at the same time. The network-induced delays of the two data transmission channels are described by the RTT delays, which can be extended to represent or include other communication constraints, such as packet disorder and loss. A new fault estimation method that can estimate the sensor fault and the system state simultaneously based on Kalman filter is presented. Then a predictive controller based state-feedback, which can generate a sequence of predictive control signals to actively compensate for the RTT delay, is designed. A sufficient condition is derived for the stability of the resulting closed-loop system by using the switched system theory. Finally, numerical simulation demonstrates the effectiveness of the proposed method.

Adaptive event-based robust passive fault tolerant control for nonlinear lateral stability of autonomous electric vehicles with asynchronous constraints