Active fault tolerant control of wind turbine systems based on DFIG with actuator fault and disturbance using Takagi–Sugeno fuzzy model

This paper presents an active fault tolerant control (FTC) for doubly fed induction generator (DFIG) with actuator fault and disturbance using Takagi–Sugeno (TS) fuzzy model. The control structure has two parts: fault and disturbance estimation part and FTC part. First, a TS fuzzy model is used to describe the DFIG system. Using a special linear transformation, the original system is decoupled into three independent subsystems: state subsystem without fault and disturbance, disturbance subsystem without fault, and fault subsystem without disturbance. By solving linear matrix inequalities (LMIs), a TS fuzzy observer is designed for the state subsystem without fault and disturbance. Second, estimations of faults and disturbance are obtained using the other subsystem models. Third, an active FTC scheme is developed to reduce the effect of disturbance and actuator faults. Finally, the performance of the proposed FTC is tested for a wind turbine system based on DFIG with actuator faults and disturbance. The simulation results demonstrate that the new FTC scheme makes possible to obtain an efficient fault and disturbance estimation and to reduce the peak current in the transient process.     

A fuzzy control framework for interconnected nonlinear power networks under TDS attack: Estimation and compensation

This article focuses on time delay switch (TDS) attacks on power networks subject to highly nonlinear and interconnection. T–S model is utilized to represent each nonlinear power subsystem in the network. In order to attenuate adverse impacts from TDS attacks, a novel control technique of estimation and compensation is proposed. Combined with the method of finite time boundedness (FTB), transient stability of power systems could be achieved. First, an augmented fuzzy observer is constructed to capacitate a synchronous estimation for system states and TDS attacks, which ensures that the estimation error is limited via the intersection operation of ellipsoids within a specified finite time interval. Then, a compensation technique is employed to attenuate the influence from TDS attacks. Finally, simulation results of a distributed power network show the efficacy of the proposed method against TDS attacks.     

Cascade design for formation control of nonholonomic systems in chained form

This paper presents a constructive method to design a cooperative state and output feedback to steer a group of nonholonomic mobile robots in chained form to form a desired geometric formation shape. The control methodology divides the resulting tracking error dynamics into a cascaded of linear and time-varying subsystems. A basic consensus algorithm is first applied to the linear subsystem which makes the states synchronize exponentially to zero. Once this first linear subsystem has converged, the second cascade can be treated as a linear time-varying subsystem perturbed by a vanishing term from its cascade. A dynamic state and output feedback is constructed to achieve synchronization of the rest of the states. The proof of stability is given using a result from cascade systems. Since time delay appears in many interconnection networks and particularly in cooperative control, its effect on the stability of the closed-loop system is analyzed using Razumikhim theorem. It is shown that the established cooperative controller work well even in the presence of time delay. Numerical simulations are performed on models of car-like mobile robots to show the effectiveness of the proposed cooperative state and output-feedback controllers.     

Nonlinear servocompensator for fault-tolerant control of a wave energy converter

This paper addresses the problem of controlling a wave energy converter (WEC) susceptible to faults in its braking subsystems, characterized through nonlinear damping. By considering the necessity of robust trajectory tracking related to the sea waves for maximizing the converted energy, one aims to preserve such a trajectory in the presence of faults to avoid physical damage in the structure of the WEC. To achieve this objective, this paper proposes a fault-tolerant control (FTC) that combines two systems: (i) a novel nonlinear servocompensator (NSC) and (ii) a fault diagnosis subsystem (FD). The NSC is based on a variable structure control that generalizes the internal model principle for robust tracking. The reference signal is computed from real-time measurements of the irregular sea waves. The FD subsystem estimates the faults related to the wear of the brakes via an unknown input observer. Due to its independent performance from the FD, the global scheme can be considered as a passive FTC. By considering the faulty model of a WEC based on the Archimedes wave swing prototype, theoretical formulation and the convergence proof are given for the NSC and the FD. The performance of the proposed design is verified with numerical simulations of the WEC with the incidence of irregular sea waves under different fault scenarios in the upper and lower brakes.     

Event-triggered adaptive neural control for state-constrained switched nonlinear systems based on nonlinear shifting function technique

This paper addresses the event-triggered tracking control design for state-constrained switched nonstrict feedback nonlinear systems. With the help of a time-varying nonlinear shifting function (TVNSF) introduced into the switched nonlinear system, the proposed solution is seen as a unified tool regardless of whether the constraint conditions are state constraints, output constraint, or even no constraint. Also, by allowing the triggering error to vary with the switching signal in time, the negative effects of the mismatch between the individual controller and the subsystem on system performance are trumped. Moreover, by using constructed individual Lyapunov function that depends on the lower bound of the control gain function of individual subsystem, a novel switching signal satisfying the average dwell time (ADT) is provided to ensure the boundedness of all variables in the closed-loop system. Finally, the proposed theory is carried over into a mass-spring-damper system to verify its effectiveness.     

Decentralized adaptive output-feedback control of interconnected nonlinear time-delay systems using minimal neural networks

This paper presents a minimal-neural-networks-based design approach for the decentralized output-feedback tracking of uncertain interconnected strict-feedback nonlinear systems with unknown time-varying delayed interactions unmatched in control inputs. Compared with existing approximation-based decentralized output-feedback designs using multiple neural networks for each subsystem in lower triangular form, the main contribution of this paper is to provide a new recursive backstepping strategy for a local memoryless output-feedback controller design using only one neural network for each subsystem regardless of the order of subsystems, unmeasurable states, and unknown unmatched and delayed nonlinear interactions. In the proposed strategy, error surfaces are designed using unmeasurable states instead of measurable states and virtual controllers are regarded as intermediate signals for designing a local control law at the last step. Using Lyapunov stability theorem and the performance function technique, it is shown that all signals of the total controlled closed-loop system are bounded and the transient and steady-state performance bounds of local tracking errors can be preselected by adjusting design parameters independent of delayed interactions.     

Barrier Lyapunov function-based adaptive fuzzy attitude tracking control for rigid satellite with input delay and output constraint

This paper investigates the adaptive attitude tracking problem for the rigid satellite involving output constraint, input saturation, input time delay, and external disturbance by integrating barrier Lyapunov function (BLF) and prescribed performance control (PPC). In contrast to the existing approaches, the input delay is addressed by Pade approximation, and the actual control input concerning saturation is obtained by utilizing an auxiliary variable that simplifies the controller design with respect to mean value methods or Nussbaum function-based strategies. Due to the implementation of the BLF control, together with an interval notion-based PPC strategy, not only the system output but also the transformed error produced by PPC are constrained. An adaptive fuzzy controller is then constructed and the predesigned constraints for system output and the transformed error will not be violated. In addition, a smooth switch term is imported into the controller such that the finite time convergence for all error variables is guaranteed for a certain case while the singularity problem is avoided. Finally, simulations are provided to show the effectiveness and potential of the proposed new design techniques.     

Robust fault tolerant tracking controller design for a VTOL aircraft

This paper deals with the fault tolerant control (FTC) design for a Vertical Takeoff and Landing (VTOL) aircraft subject to external disturbances and actuator faults. The aim is to synthesize a fault tolerant controller ensuring trajectory tracking for the nonlinear uncertain system represented by a Takagi–Sugeno (T–S) model. In order to design the FTC law, a proportional integral observer (PIO) is adopted which estimate both of the faults and the faulty system states. Based on the Lyapunov theory and ?₂ optimization, the trajectory tracking performance and the stability of the closed loop system are analyzed. Sufficient conditions are obtained in terms of linear matrix inequalities (LMI). Simulation results show that the proposed controller is robust with respect to uncertainties on the mechanical parameters that characterize the model and secures global convergence.     

Robust sliding mode guidance and control for soft landing on small bodies

The variable structure control (VSC) with sliding mode is presented to design a tracking control law to ensure the fast and accurate response and robustness of guidance law in this paper. First, the small body dynamic equation is deduced in the landing site coordinate system. Second, the desired trajectory is planned in the condition of safe soft landing constraints. Third, the guidance law based on VSC is designed to track the desired trajectory and succeed in landing on the surface of small body. Finally, the guidance and control algorithm is formed and the effectiveness of algorithm is verified by numerical Monte Carlo simulations.     

Distributed adaptive observer-based prescribed finite-time control of constrained multi-agent systems

This work considers a distributed adaptive output feedback control problem for nonlinear constrained multi-agent systems (MAS) in the prescribed finite time. To begin with, a state observer is constructed to estimate the unmeasurable state. Then, we develop a novel observer based distributed adaptive prescribed finite time output feedback control algorithm by incorporating the prescribed finite-time control technique into the backstepping design method. Through Lyapunov stability theory, it can be shown that all signals of MASs are bounded, the tracking errors converge to the adjustable regions around the origin within the pre-given error accuracy and settling time, and all states keep in the prescribed constraint regions. Finally, a simulation example verifies the efficacy of the obtained theoretical results.     

Neural network-based sensor fault estimation and active fault-tolerant control for uncertain nonlinear systems

In this work, we developed a novel active fault-tolerant control (FTC) design scheme for a class of nonlinear dynamic systems subjected simultaneously to modelling imperfections, parametric uncertainties and sensor faults. Modelling imperfections and parametric uncertainties are dealt with using an adaptive radial basis function neural network (RBFNN) that estimates the uncertain part of the system dynamics. For sensor fault estimation (FE), a nonlinear observer based on the estimated dynamics is designed. A scheme to estimate sensor faults in real-time using the nonlinear observer and an additional RBFNN is developed. The convergence properties of the RBFNN, used in the fault FE part, are improved by using a sliding surface function. For FTC design, a sliding surface is designed that incorporates the real-time sensor FE. The resulting sliding mode control (SMC) technique-based FTC law uses the estimated dynamics and real-time sensor FE. A double power-reaching law is adopted to design the switching part of the control law to improve the convergence and mitigate the chattering associated with the SMC. The FTC works well in the presence and absence of sensor faults without the requirement for controller reconfiguration. The stability of the proposed active FTC law is proved using the Lyapunov method. The developed scheme is implemented on a nonlinear simulation of an unmanned aerial vehicle (UAV). The results show good performance of the proposed unified FE and the FTC framework.     

Adaptive neural finite-time control for space circumnavigation mission with uncertain input constraints

This paper explores the design of an anti-saturation adaptive finite-time control strategy with the neural network (NN) technique for the space circumnavigation mission. Before executing the controller design, the analytical solutions of the desired angular velocity and its derivative of the active spacecraft are calculated. Since there are uncertain saturation constraints on control forces and moments in the actual propulsion system, an auxiliary system compensated by an adaptive NN is adopted. The modified auxiliary system no longer needs the precise output values of the actuators. Besides, the hyperbolic tangent function is introduced to design the weight update law for the NN compensator, so that the derivative of the weight estimator will not be amplified by the quadratic of states when the system states are large. It is proved that tracking errors of the system states can converge to a residual set of the origin in finite time. Simulation results show that the maximum amplitudes of the control signals are greatly reduced compared to the classical non-singular terminal sliding-mode control scheme, and that the neural-based compensator can significantly weaken the overshoot and chattering.     

Event-triggered asynchronous sliding mode control of CSTR based on Markov model

In this paper, an asynchronous sliding mode control design method based on the event-triggered strategy is proposed for the continuous stirred tank reactor (CSTR) under external disturbance. Firstly, with the purpose of appropriately modeling the multi-mode switching phenomenon in the CSTR caused by the fluctuation of temperature and concentration, the Markov process is applied. Secondly, the asynchronous switching characteristics are introduced to describe mismatch between the controller and the system, which caused by some factors such as signal transmission delay and packet dropout. In order to effectively estimate the system states that cannot be measured in real time, an observer based on the event-triggered strategy is proposed, which also can reduce the computational cost. In addition, a sliding mode controller is designed to ensure the dynamic stability and the sliding dynamics is reachable in a finite time. Finally, the effectiveness of the proposed method is verified by simulation experiments.     

Performance-oriented parallel distributed compensation

The main idea of the original parallel distributed compensation (PDC) method is to partition the dynamics of a nonlinear system into a number of linear subsystems, design a number of state feedback gains for each linear subsystem, and finally generate the overall state feedback gain by fuzzy blending of such gains. A new modification to the original PDC method is proposed here, so that, besides the stability issue, the closed-loop performance of the system can be considered at the design stage. For this purpose, the state feedback gains are not considered constant through the linearized subsystems, rather, based on some prescribed performance criteria, several feedback gains are associated to every subsystem, and the final gain for every subsystem is obtained by fuzzy blending of such gains. The advantage is that, for example, a faster response can be obtained, for a given bound on the control input. Asymptotic stability of the closed loop system is also guaranteed by using the Lyapunov method. To illustrate the effectiveness of the new method, control of a flexible joint robot (FJR) is investigated and superiority of the designed controller over other existing methods is demonstrated.     

Finite-time cooperative circumnavigation control of multiple second-order agents with desired formations

This paper investigates the finite-time cooperative circumnavigation control of multiple second-order agents, in which the agents should surround a moving target with desired formation and circular velocity based on local information. Firstly, the controller design is transformed into design control parameters such that the error system, including distance error, speed error and angle error, is finite-time consensus. The error system is viewed as a cascaded system containing two second-order subsystems, and then a distributed finite-time controller composed of two parts is delivered. The finite-time stability of the entire system is given by employing cascaded control theory. One significant advantage of the proposed controller is that it allows the agents to converge to desired trajectory in a finite time instead of asymptotically. Another merit is that the desired formation is an extensive case and unlimited, including different tracking radii and angular spacing. Furthermore, the proposed controller can be implemented by each agent in its local frame, utilizing only local information. These properties significantly extend the application scope of cooperative circumnavigation. Finally, simulations are carried out to validate the effectiveness of the proposed method.     

Fuzzy adaptive output-feedback tracking control for nonlinear strict-feedback systems in prescribed finite time

The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form. Under the situation of system states being unavailable, the system output is used to set up the state observer to estimate the real system states. Furthermore, the estimation states are employed to design controller. During the control design process, fuzzy logic systems (FLSs) are used to model the unknown nonlinearities. A novel observer-based finite-time tracking control scheme is proposed via fuzzy adaptive backstepping and barrier Lyapunov function approach. The suggested fuzzy adaptive output feedback controller can force the output tracking error to meet the pre-specified accuracy in a fixed time. Meanwhile, all the closed-loop variables are bounded. Compared to some existing finite-time output feedback control schemes, the developed control strategy guarantees that the settling time and the error accuracy are independent of the uncertainties and can be specified by the designer. At last, the effectiveness and feasibility of the proposed control scheme are demonstrated by two simulation examples.     

Distributed fault-tolerant tracking control for heterogeneous nonlinear multi-agent systems under sampled intermittent communications

This paper studies the distributed fault-tolerant control (FTC) problem for heterogeneous nonlinear multi-agent systems (MASs) under sampled intermittent communications. First, in order to estimate the state of leader under sampled intermittent communications, the distributed intermittent observer for each follower is constructed. By using the tool from switching system theory, the estimation error converges to zero exponentially if the communication rate is larger than a threshold value even under the impact of sampled intermittent communications. Then, by applying model reference adaptive tracking technique, a robust FTC protocol is developed to track the distributed intermittent observer. Two algorithms are presented to choose the feedback gain of the distributed intermittent observer and the tracking feedback gain of the fault-tolerant tracking controller. It is proved that the global consensus tracking error is bounded under the developed distributed control protocol. Finally, an example with the coupled pendulums is provided to verify the efficiency of the designed method.     

Distributed containment control for multiple ocean bottom flying nodes with velocity error constraint and input saturation

This paper uses the directed communication topology to investigate the finite-time error constraint containment control for multiple Ocean Bottom Flying Node (OBFN) systems with thruster faults. The OBFN is a benthic Autonomous Underwater Vehicle (AUV), which has been used to explore submarine resources. The model uncertainties, velocity error constraint, external disturbances, and thruster faults of OBFNs motivate the design of containment controller. Moreover, some followers could obtain the states of leader OBFNs. We designed the command filter and the input signal is a hyperbolic tangent function. The virtual velocity error command is generated to follow the velocity error. Then the novel velocity error constraint distributed control algorithm is developed. Furthermore, for the problem of input saturation, by designing a stable anti-saturation compensator, an improved containment algorithm is proposed. It is proved that both the proposed approaches can converge the containment errors towards zero through Lyapunov theory in finite time, which means the followers can reach the convex hull formed by leaders in finite time. Finally, simulation results demonstrate the effectiveness of the two strategies.     

Finite-time tracking using sliding mode control

Finite-time stability involves dynamical systems whose trajectories converge to an equilibrium state in finite time. In this paper, we consider a general class of fully actuated mechanical systems described by Euler–Lagrange dynamics and the class of underactuated systems represented by mobile robot dynamics that are required to reach and maintain the desired trajectory in finite time. An approach known as the terminal sliding mode control (TSMC) involves non-smooth sliding surfaces such that, while on the sliding surface, the error states converge to the origin in finite time thus ensuring finite-time tracking. The main advantage of this control scheme is in fast converging times without excessive control effort. Such controllers are known to have singularities in some parts of the state space and, in this paper, we propose a method of partitioning the state space into two regions where the TSMC is bounded and its complement. We show that the region of bounded TSMC is invariant and design an auxiliary sliding mode controller predicated on linear smooth sliding surface for the initial conditions outside this region. Furthermore, we extend these results to address TSMC for underactuated systems characterized by the mobile robot dynamics. We demonstrate the efficacy of our approach by implementing it for a scenario when multiple dynamic agents are required to move in a fixed formation with respect to the formation leader. Finally, we validate our results experimentally using a wheeled mobile robot platform.     

Hyperbolic tangent function-based fixed-time event-triggered control for quadrotor aircraft with prescribed performance

In this paper, the prescribed performance trajectory tracking problem of quadrotor aircraft with six degrees of freedom is addressed. Firstly, for the sake of facilitating the construction of controller, the aircraft is decomposed into position loop and attitude loop through time scale decomposition method. A fixed-time sliding mode controller is proposed to guarantee the convergence time of the aircraft system regardless of initial states. After that, to enhance security of control system, the hyperbolic tangent performance function is designed as performance index function to maintain the error within a prescribed range. Then, the event-triggered strategy is adopted to attitude subsystem which can significantly save communication resources, and the stability of control system is analyzed by Lyapunov method. In addition, the Zeno phenomenon is avoided which can be proved by ensuring the two consecutive trigger events have a positive lower limit. Finally, the validity of the constructed controller is confirmed by simulation results.