Search results

The purpose of this paper is to investigate the time-varying finite-time formation tracking control problem for multiple unmanned aerial vehicle systems under switching topologies, where the states of the unmanned aerial vehicles need to form desired time-varying formations while tracking the trajectory of the virtual leader in finite time under jointly connected topologies.

A consensus-based formation control protocol is constructed to achieve the desired formation. In this paper, the time-varying formation is specified by a piecewise continuously differentiable vector, while the finite-time convergence is guaranteed by utilizing a non-linear function. Based on the graph theory, the finite-time stability of the close-loop system with the proposed control protocol under jointly connected topologies is proven by applying LaSalle’s invariance principle and the theory of homogeneity with dilation.

The effectiveness of the proposed protocol is verified by numerical simulations. Consequently, the proposed protocol can successfully achieve the predefined time-varying formation in finite time under jointly connected topologies while tracking the trajectory generated by the leader.

This paper proposes a solution to simultaneously solve the control problems of time-varying formation tracking, finite-time convergence, and switching topologies.

Quadrotors have been applied in various fields. However, because the quadrotor is subject to multiple disturbances, consisting of external disturbances, actuator faults and parameter uncertainties, it is difficult to control the unmanned aerial vehicle (UAV) to achieve high-precision tracking performance. This paper aims to design a safety controller that uses observer and neural network method to improve the tracking performance of UAV under multiple disturbances. The experiments prove that this method is effective.

First, to actively estimate and compensate the synthetic uncertainties of the system, a finite-time extended state observer is investigated, and the disturbances are transformed into the extended state of the system for estimation. Second, an adaptive neural network controller that does not accurately require the dynamic model knowledge is designed based on the estimated value, where the weights of the neural network can be dynamically adjusted by the adaptive law. Furthermore, the finite-time bounded convergence of the proposed observer and the stability of the system are proved through homogeneous theory and Lyapunov method.

The figure-“8” climbing flight simulation and real flight experiments illustrate that the proposed safety control strategy has good tracking performance.

This paper proposes the safety control structure of the UAV, which combines the extended state observer with the neural network method. Numerical simulation results and actual flight experiments demonstrate the effectiveness of the proposed control strategy.

This paper aims to present a control strategy that eliminates the longitudinal and lateral drifting movements of the coaxial ducted fan unmanned helicopter (UH) during autonomous take-off and landing and reduce the coupling characteristics between channels of the coaxial UH for its special model structure.

Unidirectional auxiliary surfaces (UAS) for terminal sliding mode controller (TSMC) are designed for the flight control system of the coaxial UH, and a hierarchical flight control strategy is proposed to improve the decoupling ability of the coaxial UH.

It is demonstrated that the proposed height control strategy can solve the longitudinal and lateral movements during autonomous take-off and landing phase. The proposed hierarchical controller can decouple vertical and heading coupling problem which exists in coaxial UH. Furthermore, the confronted UAS-TSMC method can guarantee finite-time convergence and meet the quick flight trim requirements during take-off and landing.

The designed flight control strategy has not implemented in real flight test yet, as all the tests are conducted in the numerical simulation and simulation with a hardware-in-the-loop (HIL) platform.

The designed flight control strategy can solve the common problem of coupling characteristics between channels for coaxial UH, and it has important theoretical basis and reference value for engineering application; the control strategy can meet the demands of engineering practice.

In consideration of the TSMC approach, which can increase the convergence speed of the system state effectively, and the high level of response speed requirements to UH flight trim, the UAS-TSMC method is first applied to the coaxial ducted fan UH flight control. The proposed control strategy is implemented on the UH flight control system, and the HIL simulation clearly demonstrates that a much better performance could be achieved.

The purpose of this paper is to design a global robust and continuous control scheme for the attitude tracking control problem of the reentry vehicle with parameter uncertainties and disturbances.

First, feedback linearization is applied to the model of reentry vehicle, resulting in three independent uncertain subsystems. Then a new second-order time-varying sliding function is proposed, based on which a continuous second-order time-varying sliding mode control (SOTVSMC) law is proposed for each subsystem. The global robustness and convergence performance of the closed-loop reentry vehicle control system under the proposed control law are proved.

Simulation is made for a reentry vehicle through the assumption that there is external disturbance to aerodynamic moment and the aerodynamic parameters as well as the atmospheric density are perturbed. The results verify the validity and robustness of the proposed strategy.

The SOTVSMC attitude controller based on feedback linearization is proposed for the reentry vehicle. The advantages of the proposed SOTVSMC are twofold. First, the global second order sliding mode is established, which implies that the closed-loop system is global robust against matched parameter uncertainties and disturbances in reentry. Second, the chattering problem is significantly alleviated.

This paper aims to solve the problems of the synchronization between branches and the uncertainties such as joint friction, load variation and external interference of a hybrid mechanism. The controller is used to improve the synchronization and robustness of the hybrid mechanism system and achieve both finite time convergence and chattering-free sliding mode.

First, the dynamic model of hybrid mechanism containing lumped uncertainties is formulated by the Lagrange method, and a composite error based on coupling synchronization error and the end-effector tracking error is set up in the task space. Then, by combining the finite time super twisting sliding mode control algorithm, a composite error-based finite time super twisting sliding mode synchronous control law is designed to make the end-effector tracking error and coupling synchronization error achieve better tracking performance and convergence performance. Finally, the Lyapunov stability of the control law and the finite-time convergence of the composite error are proved theoretically.

To verify the effectiveness of the proposed control method, simulations and experiments for the prototype system of the hybrid mechanism are conducted. The results show that the proposed control method can achieve better tracking performance and convergence performance.

This is a new innovation for a hybrid mechanism containing lumped uncertainties to improve the robustness, convergence performance, tracking performance and synchronization of the system.

The purpose of this paper, is to solve the problem of finite-time fault-tolerant attitude synchronization and tracking control of multiple rigid bodies in presence of model uncertainty, external disturbances, actuator faults and saturation. It is assumed that the rigid bodies in the formation may encounter loss of effectiveness and/or bias actuator faults.

For the purpose, adaptive terminal sliding mode control and neural network structure are used, and a new sliding surface is proposed to guarantee known finite-time convergence not only at the reaching phase but also on the sliding surface. The sliding surface is then modified using a proposed auxiliary system to maintain stability under actuator saturation.

Assuming that the communication topology between the rigid bodies is governed by an undirected connected graph and the upper bounds on the actuators’ faults, estimation error of model uncertainty and external disturbance are unknown, not only the attitudes of the rigid bodies in the formation are synchronized but also they track the time-varying attitude of a virtual leader. Using Lyapunov stability approach, finite-time stability of the proposed control algorithms demonstrated on the sliding phase as well as the reaching phase. The effectiveness of the proposed algorithm is also validated by simulation.

The proposed controller has the advantage that the need for any fault detection and diagnosis mechanism and the upper bounds information on estimation error and external disturbance is eliminated.

The purpose of this paper is to develop a method for the existence, uniqueness and globally robust stability of the equilibrium point for Cohen–Grossberg neural networks with time-varying delays, continuous distributed delays and a kind of discontinuous activation functions.

Based on the Leray–Schauder alternative theorem and chain rule, by using a novel integral inequality dealing with monotone non-decreasing function, the authors obtain a delay-dependent sufficient condition with less conservativeness for robust stability of considered neural networks.

It turns out that the authors’ delay-dependent sufficient condition can be formed in terms of linear matrix inequalities conditions. Two examples show the effectiveness of the obtained results.

The novelty of the proposed approach lies in dealing with a new kind of discontinuous activation functions by using the Leray–Schauder alternative theorem, chain rule and a novel integral inequality on monotone non-decreasing function.

The purpose of this paper is to design a disturbance observer-based finite-time global sliding mode control scheme for the attitude tracking control problem of the reentry vehicle with parameter uncertainties and disturbances.

Feedback linearization is first introduced to transform vehicle model into three independent second order uncertain subsystems. Then a finite-time controller (FTC) is proposed for the nominal system on the basis of the homogeneity theory. Thereafter the integral sliding mode method is introduced for the vehicle with disturbances. The finite time convergence is achieved and global robustness is also assured by the combination of finite time control method and integral sliding mode strategy. Furthermore, to improve the attitude angle tracking accuracy a novel finite time disturbance observer (DO) is constructed.

Simulation is made for the reentry vehicle with disturbances involved. And the results show the finite-time convergence, tracking accuracy and robustness of the proposed strategy.

The proposed control strategy has three advantages. First of all it can achieve finite time convergence and avoid singularity. Moreover, it can also realize global robustness. Finally, a new kind of DO is introduced to improve the tracking accuracy.

The purpose of this paper is to develop some interesting results in the field of chaotic synchronization with a new finite-time controller to reduce the time of convergence.

This article proposes a finite-time controller for the synchronization of hyper(chaotic) systems in a given time. The chaotic systems are perturbed by the model uncertainties and external disturbances. The designed controller achieves finite-time synchronization convergence to the steady-state error without oscillation and elimination of the nonlinear terms from the closed-loop system. The finite-time synchronization convergence reduces the hacking duration and recovers the embedded message in chaotic signals within a given preassigned limited time. The free oscillation convergence keeps the energy consumption low and alleviates failure chances of the actuator. The proposed finite-time controller is a combination of linear and nonlinear parts. The linear part keeps the stability of the closed-loop, the nonlinear part increases the rate of convergence to the origin. A generalized form of analytical stability proof is derived for the synchronization of chaotic and hyper-chaotic systems. The simulation results provide the validation of the accomplish synchronization for the Lu chaotic and hyper-chaotic systems.

The designed controller not only reduces the time of convergence without oscillation of the trajectories which can run the system for a given time domain.

This work is originally written by the author.

The purpose of this paper is to present a sliding mode attitude controller for reusable launch vehicle (RLV) which is nonlinear, coupling, and includes uncertain parameters and external disturbances.

A smooth second-order nonsingular terminal sliding mode (NTSM) controller is proposed for RLV in reentry phase. First, a NTSM manifold is proposed for finite-time convergence. Then a smooth second sliding mode controller is designed to establish the sliding mode. An observer is utilized to estimate the lumped disturbance and the estimation result is used for feedforward compensation in the controller.

It is mathematically proved that the proposed sliding mode technique makes the attitude tracking errors converge to zero in finite time and the convergence time is estimated. Simulations are made for RLV through the assumption that aerodynamic parameters and atmospheric density are perturbed. Simulation results demonstrate that the proposed control strategy is effective, leading to promising performance and robustness.

By the proposed controller, the second-order sliding mode is established. The attitude tracking error converges to zero in a finite time. Meanwhile, the chattering is alleviated and a smooth control input is obtained.