Chaos synchronization of gyroscopes using an adaptive robust finite-time controller

The problem of robust finite-time chaos synchronization between two chaotic nonlinear gyroscopes with model uncertainties, external disturbances and unknown parameters is investigated. Appropriate adaptive laws are derived to tackle the unknown parameters. Based on the adaptive laws and the finite-time control technique, suitable adaptive control laws are designed to ensure the stability of the resulting synchronization error system in a given finite time. Numerical simulations and comparative examples are presented to illustrate the applicability and usefulness of the proposed finite-time control strategy.     

Finite-time master–slave synchronization and parameter identification for uncertain Lurie systems

This paper investigates the finite-time master–slave synchronization and parameter identification problem for uncertain Lurie systems based on the finite-time stability theory and the adaptive control method. The finite-time master–slave synchronization means that the state of a slave system follows with that of a master system in finite time, which is more reasonable than the asymptotical synchronization in applications. The uncertainties include the unknown parameters and noise disturbances. An adaptive controller and update laws which ensures the synchronization and parameter identification to be realized in finite time are constructed. Finally, two numerical examples are given to show the effectiveness of the proposed method.     

存在死区的双柔杆空间机器人有限时间控制与抑振

探讨了存在关节力矩输出死区情况下,基于有限时间的漂浮基双柔杆空间机器人系统的轨迹跟踪与柔性抑振问题。采用奇异摄动理论,将系统的动力学方程分解为慢变与快变子系统,分别表示刚性运动与柔性振动。针对模型存在不确定性和死区参数未知的慢变子系统,设计了死区预补偿器和一种基于名义模型的有限时间控制器。引入了具有有限时间收敛特性的积分式滑模面,它与传统渐近收敛控制方法相比,具有更快的收敛速度、更好的鲁棒性和抗干扰特性。对于快变子系统,采用线性二次最优控制方法主动抑制其振动,以保证系统良好的稳定性。结合有限时间稳定性引理,采用李雅普诺夫理论证明了所提控制算法能使跟踪误差在有限时间内收敛到原点。仿真算例验证了所提方法的有效性。     

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods.     

A new robust control for minirotorcraft unmanned aerial vehicles

This paper presents a new robust control based on finite-time Lyapunov stability controller and proved with backstepping method for the position and the attitude of a small rotorcraft unmanned aerial vehicle subjected to bounded uncertainties and disturbances. The dynamical motion equations are obtained by the Newton–Euler formalism. The proposed controller combines the advantage of the backstepping approach with finite-time convergence techniques to generate a control laws to guarantee the faster convergence of the state variables to their desired values in short time and compensate for the bounded disturbances. A formal proof of the closed-loop stability and finite-time convergence of tracking errors is derived using the Lyapunov function technique. Simulation results are presented to corroborate the effectiveness and the robustness of the proposed control method.     

Adaptive nonsingular fast terminal sliding-mode control for the tracking problem of uncertain dynamical systems

In this paper, robust and adaptive nonsingular fast terminal sliding-mode (NFTSM) control schemes for the trajectory tracking problem are proposed with known or unknown upper bound of the system uncertainty and external disturbances. The developed controllers take the advantage of the NFTSM theory to ensure fast convergence rate, singularity avoidance, and robustness against uncertainties and external disturbances. First, a robust NFTSM controller is proposed which guarantees that sliding surface and equilibrium point can be reached in a short finite-time from any initial state. Then, in order to cope with the unknown upper bound of the system uncertainty which may be occurring in practical applications, a new adaptive NFTSM algorithm is developed. One feature of the proposed control law is their adaptation techniques where the prior knowledge of parameters uncertainty and disturbances is not needed. However, the adaptive tuning law can estimate the upper bound of these uncertainties using only position and velocity measurements. Moreover, the proposed controller eliminates the chattering effect without losing the robustness property and the precision. Stability analysis is performed using the Lyapunov stability theory, and simulation studies are conducted to verify the effectiveness of the developed control schemes.     

Adaptive-gain fast super-twisting sliding mode fault tolerant control for a reusable launch vehicle in reentry phase

In this paper, a novel adaptive-gain fast super-twisting (AGFST) sliding mode attitude control synthesis is carried out for a reusable launch vehicle subject to actuator faults and unknown disturbances. According to the fast nonsingular terminal sliding mode surface (FNTSMS) and adaptive-gain fast super-twisting algorithm, an adaptive fault tolerant control law for the attitude stabilization is derived to protect against the actuator faults and unknown uncertainties. Firstly, a second-order nonlinear control-oriented model for the RLV is established by feedback linearization method. And on the basis a fast nonsingular terminal sliding mode (FNTSM) manifold is designed, which provides fast finite-time global convergence and avoids singularity problem as well as chattering phenomenon. Based on the merits of the standard super-twisting (ST) algorithm and fast reaching law with adaption, a novel adaptive-gain fast super-twisting (AGFST) algorithm is proposed for the finite-time fault tolerant attitude control problem of the RLV without any knowledge of the bounds of uncertainties and actuator faults. The important feature of the AGFST algorithm includes non-overestimating the values of the control gains and faster convergence speed than the standard ST algorithm. A formal proof of the finite-time stability of the closed-loop system is derived using the Lyapunov function technique. An estimation of the convergence time and accurate expression of convergence region are also provided. Finally, simulations are presented to illustrate the effectiveness and superiority of the proposed control scheme.     

输入受限的非完整移动机器人的自适应模糊控制

提出了一种非完整移动机器人饱和自适应模糊轨迹跟踪控制方法,该方法基于反演技术分别设计了系统的运动学控制器和动力学控制器。运动学控制器通过引入分流控制技术解决了初始速度跳变引起的控制量突变问题,动力学控制器利用饱和函数和受限控制参数实现了其有界力矩控制。自适应模糊控制器将模糊逻辑系统与自适应方法相结合,有效消除了常规方法难以解决的系统未知不确定性对系统的影响。通过Lyapunov直接法证明了该系统是收敛且渐进稳定的。仿真结果验证了所设计控制器的良好控制性能和强鲁棒性。     

Dual-quaternion based fault-tolerant control for spacecraft formation flying with finite-time convergence

Study results of developing control system for spacecraft formation proximity operations between a target and a chaser are presented. In particular, a coupled model using dual quaternion is employed to describe the proximity problem of spacecraft formation, and a nonlinear adaptive fault-tolerant feedback control law is developed to enable the chaser spacecraft to track the position and attitude of the target even though its actuator occurs fault. Multiple-task capability of the proposed control system is further demonstrated in the presence of disturbances and parametric uncertainties as well. In addition, the practical finite-time stability feature of the closed-loop system is guaranteed theoretically under the designed control law. Numerical simulation of the proposed method is presented to demonstrate the advantages with respect to interference suppression, fast tracking, fault tolerant and practical finite-time stability.     

Sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage

The problem of sampled-data-based vibration control for structural systems with finite-time state constraint and sensor outage is investigated in this paper. The objective of designing controllers is to guarantee the stability and anti-disturbance performance of the closed-loop systems while some sensor outages happen. Firstly, based on matrix transformation, the state-space model of structural systems with sensor outages and uncertainties appearing in the mass, damping and stiffness matrices is established. Secondly, by considering most of those earthquakes or strong winds happen in a very short time, and it is often the peak values make the structures damaged, the finite-time stability analysis method is introduced to constrain the state responses in a given time interval, and the H-infinity stability is adopted in the controller design to make sure that the closed-loop system has a prescribed level of disturbance attenuation performance during the whole control process. Furthermore, all stabilization conditions are expressed in the forms of linear matrix inequalities (LMIs), whose feasibility can be easily checked by using the LMI Toolbox. Finally, numerical examples are given to demonstrate the effectiveness of the proposed theorems.     

基于反演设计的机械臂非奇异终端神经滑模控制

针对具有建模误差和不确定干扰的多关节机械臂的轨迹跟踪问题,设计反演非奇异终端神经滑模控制。该方案是采用能有限时间收敛的非奇异终端滑模面,根据滑模控制原理和反演方法设计反演滑模控制器;对于反演滑模控制系统中由于建模误差和不确定干扰造成的不确定因素的上界,设计径向基(Radial basis function, RBF)神经网络自适应律,在线估计不确定因素的上界;利用李亚普诺夫定理证明了系统的稳定性。仿真结果表明,该方法具有良好的轨迹跟踪性能,提高对于建模误差和不确定干扰等因素的鲁棒性,削弱了抖动。     

积分切换面自适应滑模控制及其在并联机器人中的应用

针对交流伺服电机作为驱动装置的2-DOF并联机器人,设计出一种带有积分切换面的自适应滑模控制器。首先,带有积分运算切换面的变结构控制器使系统具有对未知参数变化和外部干扰不敏感的特性。其次,通过设计一种自适应律,实现对系统不确定量的在线辨识估计,以辨识结果实时调整控制器参数,以削弱系统抖动,提高了控制系统的实用性。仿真结果表明所设计控制器抗干扰能力强,能较好地实现2-DOF并联机器人各支路的运动控制,具有较好的稳定性和鲁棒性能。     

Attitude output feedback control for rigid spacecraft with finite-time convergence

The main problem addressed is the quaternion-based attitude stabilization control of rigid spacecraft without angular velocity measurements in the presence of external disturbances and reaction wheel friction as well. As a stepping stone, an angular velocity observer is proposed for the attitude control of a rigid body in the absence of angular velocity measurements. The observer design ensures finite-time convergence of angular velocity state estimation errors irrespective of the control torque or the initial attitude state of the spacecraft. Then, a novel finite-time control law is employed as the controller in which the estimate of the angular velocity is used directly. It is then shown that the observer and the controlled system form a cascaded structure, which allows the application of the finite-time stability theory of cascaded systems to prove the finite-time stability of the closed-loop system. A rigorous analysis of the proposed formulation is provided and numerical simulation studies are presented to help illustrate the effectiveness of the angular-velocity observer for rigid spacecraft attitude control.     

Finite-time resilient decentralized control for interconnected impulsive switched systems with neutral delay

This paper is concerned with the problem of finite-time control for a class of interconnected impulsive switched systems with neutral delay in which the time-varying delay appears in both the state and the state derivative. The concepts of finite-time boundedness and finite-time stability are respectively extended to interconnected impulsive switched systems with neutral delay for the first time. By applying the average dwell time method, sufficient conditions are first derived to cope with the problem of finite-time boundedness and finite-time stability for interconnected impulsive switched systems with neutral delay. In addition, the purpose of finite-time resilient decentralized control is to construct a resilient decentralized state-feedback controller such that the closed-loop system is finite-time bounded and finite-time stable. All the conditions are formulated in terms of linear matrix inequalities to ensure finite-time boundedness and finite-time stability of the given system. Finally, an example is presented to illustrate the effectiveness of the proposed approach.     

Adaptive output-feedback control with prescribed performance for trajectory tracking of underactuated surface vessels

In this paper, we address the problem of trajectory tracking control of underactuated surface vessels in a quantitative method with only position and attitude available. Combined with high-gain observer, parameter compression algorithm and performance function, an adaptive control scheme with prescribed performance is proposed. The high-gain observer is constructed to estimate the velocities, and the parameter compression algorithm is adopted to address persistent perturbations and model uncertainties in a more concise way. By prescribed performance function, the controller can be designed with prescribed performance. The results about system stability is given and proved by using the Lyapunov direct method. The signals concerning with all the errors converge to a bounded set. Compared with the existing methods, the developed scheme can reduce the number of tuning parameters, and guarantee the tracking errors bounded within the prescribed performance constraints in the transformed coordinate, which means the steady errors, convergence rates and maximum overshoots can be guaranteed by the performance function. Comparison and numerical simulations are given to demonstrate the effectiveness of the proposed scheme.     

Adaptive second-order fast nonsingular terminal sliding mode control for robotic manipulators

This paper presents an adaptive chattering-free sliding mode controller for trajectory tracking of robotic manipulators in the presence of external disturbances and inertia uncertainties. To achieve fast convergence and desirable tracking precision, a second-order fast nonsingular terminal sliding mode (SOFNTSM) controller is designed to guarantee system performance and robust stability. Chattering is eliminated using continuous control law due to high-frequency switching terms contained in the first derivative of actual control signals. Meanwhile, uncertainties are compensated by introducing the adaptive technique, whose prior knowledge about upper bound is not required. Finally, simulation results validate the effectiveness of the proposed control scheme.     

Learning from adaptive neural network output feedback control of a unicycle-type mobile robot

This paper studies learning from adaptive neural network (NN) output feedback control of nonholonomic unicycle-type mobile robots. The major difficulties are caused by the unknown robot system dynamics and the unmeasurable states. To overcome these difficulties, a new adaptive control scheme is proposed including designing a new adaptive NN output feedback controller and two high-gain observers. It is shown that the stability of the closed-loop robot system and the convergence of tracking errors are guaranteed. The unknown robot system dynamics can be approximated by radial basis function NNs. When repeating same or similar control tasks, the learned knowledge can be recalled and reused to achieve guaranteed stability and better control performance, thereby avoiding the tremendous repeated training process of NNs.     

Finite-time sliding mode controller for perturbed second-order systems

This paper presents a novel finite-time sliding mode controller applied to perturbed second order systems. The proposed scheme employs a disturbance observer that can identify growing in time disturbances. Then, the observer is combined with a sliding mode controller to achieve finite-time stabilization of the second-order system. The convergence of the observer as well as the finite-time stability of the closed-loop system is theoretically demonstrated. Besides, it is also shown that the finite-time convergence properties of a given controller can be enhanced when using a compensation term based on the disturbance observer. The proposed controller is compared with a twisting algorithm and a finite-time sliding mode controller with disturbance estimation. Also, a conventional proportional integral derivative (PID) controller is combined with the proposed disturbance observer in a trajectory tracking task. Numerical simulations indicate that the proposed controller attains finite-time stabilization of the second order system by requiring a less amount of power than that demanded by the other control schemes and without being affected by the peaking phenomenon. Besides, the performance of the PID technique is enhanced by applying the proposed control methodology.     

Adaptive backstepping sliding mode control with fuzzy monitoring strategy for a kind of mechanical system

A novel adaptive backstepping sliding mode control (ABSMC) law with fuzzy monitoring strategy is proposed for the tracking-control of a kind of nonlinear mechanical system. The proposed ABSMC scheme combining the sliding mode control and backstepping technique ensure that the occurrence of the sliding motion in finite-time and the trajectory of tracking-error converge to equilibrium point. To obtain a better perturbation rejection property, an adaptive control law is employed to compensate the lumped perturbation. Furthermore, we introduce fuzzy monitoring strategy to improve adaptive capacity and soften the control signal. The convergence and stability of the proposed control scheme are proved by using Lyaponov′s method. Finally, numerical simulations demonstrate the effectiveness of the proposed control scheme.     

Temporally local recurrent radial basis function network for modeling and adaptive control of nonlinear systems

In this paper, a novel temporally local recurrent radial basis function network for modeling and adaptive control of nonlinear systems is proposed. The proposed structure consists of recurrent hidden neurons having weighted self-feedback loops and a weighted linear feed-through from the input layer directly to the output layer neuron(s). The dynamic back-propagation algorithm is developed and used for updating the parameters of the proposed structure. To improve the performance of learning algorithm, discrete Lyapunov stability method is used to develop an adaptive learning rate scheme. This scheme ensures the faster convergence of the parameters and maintains the stability of the system. A total of 5 complex nonlinear systems are used to test and compare the performance of the proposed network with other neural network structures. The disturbance rejection tests are also carried out to check whether the proposed scheme is able to handle the external disturbance/noise signals effects or not. The obtained results show the efficacy of the proposed method.