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.     

Extended-state-observer-based output feedback adaptive control of hydraulic system with continuous friction compensation

This paper presents an extended state observer-based output feedback adaptive controller with a continuous LuGre friction compensation for a hydraulic servo control system. A continuous approximation of the LuGre friction model is employed, which preserves the main physical characteristics of the original model without increasing the complexity of the system stability analysis. By this way, continuous friction compensation is used to eliminate the majority of nonlinear dynamics in hydraulic servo system. Besides, with the development of a new parameter adaption law, the problems of parametric uncertainties are overcome so that more accurate friction compensation is realized. For another, the developed adaption law is driven by tracking errors and observation errors simultaneously. Thus, the burden of extended state observer to solve the remaining uncertainties is alleviated greatly and high gain feedback is avoided, which means better tracking performance and robustness are achieved. The designed controller handles not only matched uncertainties but also unmatched dynamics with requiring little system information, more importantly, it is based on output feedback method, in other words, the synthesized controller only relies on input signal and position output signal of the system, which greatly reduces the effects caused by signal pollution, measurement noise and other unexpected dynamics. Lyapunov-based analysis has proved this strategy presents a prescribed tracking transient performance and final tracking accuracy while obtaining asymptotic tracking performance in the presence of parametric uncertainties only. Finally, comparative experiments are conducted on a hydraulic servo platform to verify the high tracking performance of the proposed control strategy.     

Disturbance and state observer-based adaptive finite-time control for quantized nonlinear systems with unknown control directions

This paper concentrates on proposing a novel finite-time tracking control algorithm for a kind of nonlinear systems with input quantization and unknown control directions. The nonlinear functions in the system are approximated by the means of strong approximation capability of the fuzzy logic systems. Firstly, the nonlinear system with unknown control directions is transformed into an equivalent system with known control gains by coordinate transformation. Secondly, the unknown system states are estimated by a designed fuzzy state observer, and the disturbance observer is constructed to track the external disturbances. The command filtering method is proposed to approach the problem of “explosion of complexity” existed in the conventional backstepping design process. In this system, the difficulties caused by unknown control directions are solved via the Nussbaum gain approach. Finally, based on the fuzzy state observer, the controller of the original system is obtained via using the transformed system by the backstepping method. The boundedness of all signals and the convergence of tracking and observer errors at the origin are ensured for the closed-loop system, and demonstrated by the simulation result in this paper.     

Distributed finite-time adaptive consensus tracking control for multiple AUVs with state constraints

Aiming at the consensus tracking control problem of multiple autonomous underwater vehicles (AUVs) with state constraints, a new neural network (NN) and barrier Lyapunov function based finite-time command filtered backstepping control scheme is proposed. The finite-time command filter is utilized to filtering the virtual control signal, the error compensation signal is constructed to eliminate filtering error due to the use of filter, and the NN approximation technology is used to deal with the unknown nonlinear dynamics. The control scheme can guarantee that the consensus tracking errors of position states converge into the desired neighborhood of the origin in finite-time while not exceeding the predefined constraints. Finally, simulation studies prove the feasibility of proposed control algorithm.     

Command filter-based finite-time adaptive fuzzy control for nonlinear systems with uncertain disturbance

In this paper, a command filter-based adaptive fuzzy controller is constructed for a class of nonlinear systems with uncertain disturbance. By using the error compensation signals and fuzzy logic system, a command filter-based control strategy is presented to make that the tracking error converge to an any small neighborhood of zero and all closed-loop signals are bounded. In the design procedure, fuzzy logic system is employed to estimate unknown package nonlinear functions, which avoids excessive and burdensome computations. The control scheme not only resolves the explosion of complexity problem but also eliminates the filtering error in finite-time. An example has evaluated the validity of the control method.     

Multivariable uniform finite-time output feedback reentry attitude control for RLV with mismatched disturbance

A continuous multivariable uniform finite-time output feedback reentry attitude control scheme is developed for Reusable Launch Vehicle (RLV) with both matched and mismatched disturbances. A novel finite-time controller is derived using the bi-limit homogeneous technique, which ensures that the attitude tracking can be achieved in a uniformly bounded convergence time from any initial states. A multivariable uniform finite-time observer is designed based on an arbitrary order robust sliding mode differentiator to estimate the unknown states and the external disturbances, simultaneously. Then, an output feedback control scheme is established through the combination of the developed controller and the observer. A rigorous proof of the uniform finite-time stability of the closed-loop system is presented using Lyapunov and homogeneous techniques. Finally, numerical simulation is provided to demonstrate the efficiency of the proposed scheme.     

Adaptive control of output feedback nonlinear systems with unmodeled dynamics and output constraint

This paper is concerned with the adaptive control problem of a class of output feedback nonlinear systems with unmodeled dynamics and output constraint. Two dynamic surface control design approaches based on integral barrier Lyapunov function are proposed to design controller ensuring both desired tracking performance and constraint satisfaction. The radial basis function neural networks are utilized to approximate unknown nonlinear continuous functions. K-filters and dynamic signal are introduced to estimate the unmeasured states and deal with the dynamic uncertainties, respectively. By theoretical analysis, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded, while the output constraint is never violated. Simulation results demonstrate the effectiveness of the proposed approaches.     

Distributed event-triggered adaptive finite-time consensus control for second-order multi-agent systems with connectivity preservation

In this paper, we consider the robust finite-time consensus problem for second-order multi-agent systems (MASs) with limited sensing range and weak communication ability. As a stepping stone, a novel distributed finite-time sliding mode manifold is developed for MASs. Then, by combining artificial potential function technique with the presented sliding mode manifold, a robust distributed control scheme is proposed to enable the finite-time consensus of MASs while preserving the prescribed communication connectivity. Furthermore, the sampling frequency and implementation burden of the proposed controller can be reduced with resort to the event-triggered methodology. Finally, numerical examples are given to show the effectiveness of the proposed method.     

Practical finite-time command filtered backstepping control of MPCVD reactor systems with uncertainties

A practical finite-time command filtered backstepping control method is proposed in this paper for a microwave plasma chemical vapor deposition (MPCVD) reactor system. The MPCVD reactor system is modeled as a coupled nonlinear system with unknown control direction functions and unknown nonlinearities. To address the unknown nonlinearities, novel practical finite-time command filters are proposed to construct the estimations of such nonlinearities. On the other hand, an equivalent augmented system of the reactor system is proposed to address the design challenges that posed by the system unknown control direction functions. Additionally, it can be concluded that the proposed control method ensures practical finite-time stability of the reactor system tracking errors by using the practical finite-time Lyapunov stability criterion. Finally, the effectiveness of the approach is demonstrated through the simulation results.     

Robust adaptive finite-time stabilization control for a class of nonlinear switched systems based on finite-time disturbance observer

The problem of adaptive global finite-time stabilization control for a class of nonlinear switched systems in the presence of external perturbations and arbitrary switchings has been addressed in this research study. The proposed scheme has been designed based on a finite-time estimation technique in which during the control procedure, unknown imposed perturbations are accurately estimated by means of the designed finite-time disturbance observer (FTDO). Due to the exact estimation of the external disturbances within a given finite time, the encountered complications and adversities from loss of information in the Lyapunov parameter estimation (LPE) methods have been solved which are caused by the persistent switchings in the system. Furthermore, a new solution for the problem of chattering phenomenon in nonlinear switched systems has been presented by utilizing the designed FTDO, which can counteract the malfunctioning responses of the system caused by external disturbances and unmodeled dynamics. In this paper, an acknowledged class of nonlinear switched systems has been taken into account which is in the general form of canonical structure. In addition, the established design strategy is formulated for the control of perturbed nonlinear switched systems with one and only input and assures that the system states through the finite-time convergence characteristic, reach the equilibrium point of origin. Finally, numerical simulations are carried out on a mass-spring-damper (MSD) dynamical system to indicate advantages and superior efficiency of the suggested method.     

Event-triggered adaptive NN practical finite-time control with its application to MPCVD reactors

The practical finite-time control problem of uncertain nonlinear systems is investigated in this paper. To address the uncertain nonlinearities of the system, neural networks are introduced to approximate the lumped nonlinearities containing the system unknown functions. On the other hand, to alleviate the signal transmission pressure of the system, an improved event-triggered mechanism is presented to reduce the controller update frequency without degrading the control performance of the system. By using practical finite-time stability, it is obtained that the system tracking errors are practical finite-time stable without Zeno behavior. Finally, the effectiveness of the proposed method is verified by the simulation results of its application to a microwave plasma chemical vapor deposition (MPCVD) reactor system.     

Active control for flexible mechanical systems with mixed deadzone-saturation input nonlinearities and output constraint

There exist mixed deadzone-saturation input nonlinearities and output constraint in the practical implementation environment for flexible mechanical systems, and they have crucial influences on the performance of flexible systems. In this paper, two class of flexible structures are investigated and analyzed by designing the active boundary vibration control with auxiliary systems. Based on the infinite dimensional dynamic model of flexible mechanical systems, the barrier logarithmic terms are brought into the Lyapunov function and boundary vibration control laws for maintaining the output signals within the constrained region. Besides, the auxiliary terms are designed in the control laws to compensate for mixed nonlinear inputs which integrate the deadzone and saturation characteristics. With the simulation results, the theoretical analysis for the flexible mechanical systems is verified to be correct and the designed control laws are effective.     

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.     

Fault-tolerant practical tracking control for uncertain robotic system with general reference trajectory and output constraint

This paper is devoted to the fault-tolerant tracking control for a class of uncertain robotic systems under time-varying output constraints. Notably, both actuator fault and the disturbances are present while all the dynamic matrices are not necessarily to be parameterized by unknown parameters or have known nominal parts, and moreover, the reference trajectories as well as the output constraints functions are not necessarily twice continuously differentiable without any time derivatives of them being available for feedback. These remarkable characteristics greatly relax the corresponding assumptions of the related literature and in turn to bring the ineffectiveness of the traditional schemes on this topic. For this, a powerful adaptive control methodology is established by incorporating adaptive dynamic compensation technique into the backstepping framework based on Barrier Lyapunov functions. Then, an adaptive state feedback controller with the smart choices of adaptive law and virtual controls is designed which guarantees that all the states of the closed-loop system are bounded and the system output practically tracks the reference trajectory while not violates the output constraints.     

Funnel-based adaptive fuzzy finite-time control for non-affine nonlinear systems preceded by unknown actuators

In this paper, an adaptive finite-time funnel control for non-affine strict-feedback nonlinear systems preceded by unknown non-smooth input nonlinearities is proposed. The input nonlinearities include backlash-like hysteresis and dead-zone. Unknown nonlinear functions are handled using fuzzy logic systems (FLS), based on the universal approximation theorem. An improved funnel error surface is utilized to guarantee the steady-state and transient predetermined performances while the differentiability problem in the controller design is averted. Using the Lyapunov approach, all the adaptive laws are extracted. In addition, an adaptive continuous robust term is added to the control input to relax the assumption of knowing the bounds of uncertainties. All the signals in the closed-loop system are shown to be semi-globally practically finite-time bounded with predetermined performance for output tracking error. Finally, comparative numerical and practical examples are provided to authenticate the efficacy and applicability of the proposed scheme.     

Terminal angle constraint finite-time guidance law with input saturation and autopilot dynamics

This paper proposes a finite-time command filtered backstepping guidance law (FCFBGL) with the terminal angle constraint while accounting for the input saturation and the autopilot dynamics. To eliminate the adverse effect induced by the filtering errors and the acceleration saturation, a new finite-time error compensation mechanism is integrated in the guidance law design. The proposed FCFBGL not only guarantees the the line-of-sight (LOS) angle error to converge to a small neighborhood of the origin in finite time but also achieves the continuity of the input signal. in finite time. Moreover, with the aid of the fractional power extended state observer (FPESO), the proposed FCFBGL requires no information on the target acceleration and the acceleration derivative of the missile, which is preferable in the practical application. The finite-time stability of the proposed guidance law is derived with the Lyapunov methodology. Simulation results illustrate the effectiveness and superiority of the proposed guidance law.     

Flatness-based adaptive fuzzy output tracking excitation control for power system generators

In this paper, a novel approach for the design of an indirect adaptive fuzzy output tracking excitation control of power system generators is proposed. The method is developed based on the concept of differentially flat systems through which the nonlinear system can be written in canonical form. The flatness-based adaptive fuzzy control methodology is used to design the excitation control signal of a single machine power system in order to track a reference trajectory for the generator angle. The considered power system can be written in the canonical form and the resulting excitation control signal is shown to be nonlinear. In case of unknown power system parameters due to abnormalities, the nonlinear functions appearing in the control signal are approximated using adaptive fuzzy systems. Simulation results show that the proposed controller can enhance the transient stability of the power system under a three-phase to ground fault occurring near the generator terminals.