Revised barrier function-based adaptive finite-and fixed-time convergence super-twisting control

This paper presents an adaptive gain,finite-and fixedtime convergence super-twisting-like algorithm based on a revised barrier function,which is robust to perturbations with unknown bounds.It is shown that this algorithm can ensure a finite-and fixed-time convergence of the sliding variable to the equilibrium,no matter what the initial conditions of the system states are,and maintain it there in a predefined vicinity of the origin without violation.Also,the proposed method avoids the problem of overestimation of the control gain that exists in the current fixed-time adaptive control.Moreover,it shows that the revised barrier function can effectively reduce the computation load by obviating the need of increasing the magnitude of sampling step compared with the conventional barrier function.This feature will be beneficial when the algorithm is implemented in practice.After that,the estimation of the fixed convergence time of the proposed method is derived and the impractical requirement of the preceding fixed-time adaptive control that the adaptive gains must be large enough to engender the sliding mode at time t=0 is discarded.Finally,the outperformance of the proposed method over the existing counterpart method is demonstrated with a numerical simulation.

The Non-Singular Fast Terminal Sliding Mode Control of Interior Permanent Magnet Synchronous Motor Based on Deep Flux Weakening Switching Point Tracking

This paper presents a novel non-singular fast terminal sliding mode control(NFTSMC)based on the deep flux weakening switching point tracking method in order to improve the control performance of permanent interior magnet synchronous motor(IPMSM)drive systems.The mathematical model of flux weakening(FW)control is established,and the deep flux weakening switching point is calculated accurately by analyzing the relationship between the torque curve and voltage decline curve.Next,a second-order NFTSMC is designed for the speed loop controller to ensure that the system converges to the equilibrium state in finite time.Then,an extended sliding mode disturbance observer(ESMDO)is designed to estimate the uncertainty of the system.Finally,compared with both the PI control and sliding mode control(SMC)by simulations and experiments with different working conditions,the method proposed has the merits of accelerating convergence,improving steady-state accuracy,and minimizing the current and torque pulsation.

Sliding mode fault tolerant consensus control for multi-agent systems based on super-twisting observer

The fault-tolerant consensus problem for leader-following nonlinear multi-agent systems with actuator faults is mainly investigated.A new super-twisting sliding mode observer is constructed to estimate the velocity and undetectable fault information simultaneously.The time-varying gain is introduced to solve the initial error problem and peak value problem,which makes the observation more accurate and faster.Then,based on the estimated results,an improved sliding mode fault-tolerant consensus control algorithm is designed to compensate the actuator faults.The protocol can guarantee the finite-time consensus control of multi-agent systems and suppress chattering.Finally,the effectiveness and the superiority of the observer and control algorithm are proved by some simulation examples of the multi-aircraft system.

Non-Negative Adaptive Mechanism-Based Sliding Mode Control for Parallel Manipulators with Uncertainties

In this paper,a non-negative adaptive mechanism based on an adaptive nonsingular fast terminal sliding mode control strategy is proposed to have finite time and high-speed trajectory tracking for parallel manipulators with the existence of unknown bounded complex uncertainties and external disturbances.The proposed approach is a hybrid scheme of the online non-negative adaptive mechanism,tracking differentiator,and nonsingular fast terminal sliding mode control(NFTSMC).Based on the online non-negative adaptive mechanism,the proposed control can remove the assumption that the uncertainties and disturbances must be bounded for the NFTSMC controllers.The proposed controller has several advantages such as simple structure,easy implementation,rapid response,chattering-free,high precision,robustness,singularity avoidance,and finite-time convergence.Since all control parameters are online updated via tracking differentiator and non-negative adaptive law,the tracking control performance at high-speed motions can be better in real-time requirement and disturbance rejection ability.Finally,simulation results validate the effectiveness of the proposed method.

Nonsingular Fast Terminal Sliding Mode Control Based on Nonlinear Disturbance Observer for a Quadrotor

Given external disturbances and system uncertainties,a nonsingular fast terminal sliding mode control(NFTSMC)method integrated a nonlinear disturbance observer(NDO)is put forward for quadrotor aircraft.First,a NDO is proposed to estimate the actual values of uncertainties and disturbances.Second,the NFTSM controller based on the reaching law is designed for the attitude subsystem(inner loop),and the control strategy can ensure Euler angles’fast convergence and stability of the attitude subsystem.Moreover,the NFTSMC strategy combined with backstepping is proposed for the position subsystem(outer loop),which can ensure subsystem tracking performance.Finally,comparative simulations show the trajectory tracking performance of the proposed method is superior to that of the traditional sliding mode control(SMC)and the SM integral backstepping control under uncertainties and disturbances.

Fuzzy Fractional-Order Fast Terminal Sliding Mode Control for Some Chaotic Microcomponents

In this paper, we propose a novel fractional-order fast terminal sliding mode control method, based on an integer-order scheme, to stabilize the chaotic motion of two typical microcomponents. We apply the fractional Lyapunov stability theorem to analytically guarantee the asymptotic stability of a system characterized by uncertainties and external disturbances. To reduce chattering, we design a fuzzy logic algorithm to replace the traditional signum function in the switching law. Lastly, we perform numerical simulations with both the fractional-order and integer-order control laws. Results show that the proposed control law is effective in suppressing chaos. © 2017, Tianjin University and Springer-Verlag Berlin Heidelberg.

Grey Wolf Optimization Based Tuning of Terminal Sliding Mode Controllers for a Quadrotor

The research on Unmanned Aerial Vehicles(UAV)has intensified considerably thanks to the recent growth in the fields of advanced automatic control,artificial intelligence,and miniaturization.In this paper,a Grey Wolf Optimization(GWO)algorithm is proposed and successfully applied to tune all effective parameters of Fast Terminal Sliding Mode(FTSM)controllers for a quadrotor UAV.A full control scheme is first established to deal with the coupled and underactuated dynamics of the drone.Controllers for altitude,attitude,and position dynamics become separately designed and tuned.To work around the repetitive and time-consuming trial-error-based procedures,all FTSM controllers’parameters for only altitude and attitude dynamics are systematically tuned thanks to the proposed GWO metaheuristic.Such a hard and complex tuning task is formulated as a nonlinear optimization problem under operational constraints.The performance and robustness of the GWO-based control strategy are compared to those based on homologous metaheuristics and standard terminal sliding mode approaches.Numerical simulations are carried out to show the effectiveness and superiority of the proposed GWO-tuned FTSM controllers for the altitude and attitude dynamics’stabilization and tracking.Nonparametric statistical analyses revealed that the GWO algorithm is more competitive with high performance in terms of fastness,non-premature convergence,and research exploration/exploitation capabilities.

Generalized reduced-order synchronization of chaotic system based on fast slide mode

A new kind of generalized reduced-order synchronization of different chaotic systems is proposed in this paper. It is shown that dynamical evolution of third-order oscillator can be synchronized with the canonical projection of a fourth-order chaotic system generated through nonsingular states transformation from a cell neural net chaotic system. In this sense, it is said that generalized synchronization is achieved in reduced-order. The synchronization discussed here expands the scope of reduced-order synchronization studied in relevant literatures. In this way, we can achieve generalized reduced-order synchronization between many famous chaotic systems such as the second-order Drifting system and the third-order Lorenz system by designing a fast slide mode controller. Simulation results are provided to verify the operation of the designed synchronization.

Modified grey wolf optimised adaptive super-twisting sliding mode control of rotary inverted pendulum system

This paper proposes a modified grey wolf optimiser-based adaptive super-twisting sliding mode control algorithm for the trajectory tracking and balancing of the rotary inverted pendulum system.The super-twisting sliding mode algorithm severely alleviates the chattering present in the classical sliding mode control.It provides robustness against model uncertainties and external disturbances with the knowledge of the upper bounds of the uncertainties and disturbances.The gains of the super-twisting sliding mode algorithm are selected through adaptive law.Parameters of the adaption law are tuned using a modified grey wolf optimisation algorithm,a meta-heuristic optimisation technique.Lyapunov stability analysis is carried out to analyse the overall control system stability.The performance of the proposed control algorithm is compared with two other sliding mode control strategies present in the literature,therein showing better performance of the proposed control scheme.

A sliding mode control algorithm based on improved super-twisting and its application to quadrotors

This paper presents a fast terminal sliding mode control strategy based on improved supertwistingalgorithm (IST-FTSMC) for quadrotors with external disturbances. First, the dynamicmodel of quadrotors is described. Then, a control strategy based on fast terminal sliding modewith improved super-twisting algorithm is proposed for attitude subsystem and position subsystem.Finally, some comparative results show superior tracking performance of the proposedmethod in this paper under external disturbances.

基于改进非线性滑模控制的轮式机器人轨迹跟踪

针对轮式机器人的轨迹跟踪控制存在的问题,设计了一种改进非线性快速终端滑模控制器(improved nonlinear fast terminal sliding mode controller,INFTSMC)的控制方案。首先,通过对轮式机器人运动学的分析建立了轨迹跟踪误差模型;其次,在设计滑模控制器阶段,针对非线性快速终端滑模控制器存在奇异点,采用一种新的滑模面幂指数时变策略来设计非奇异终端滑模控制器,解决了非线性快速终端滑模控制器奇异问题,通过构造Lyapunov函数进行稳定性分析证明了该策略的稳定性,并且进行收敛时间分析给出系统从任意初始状态收敛至平衡点所需要的时间;然后,在新的滑模面幂指数时变策略的基础上设计了轮式机器人线速度和角速度控制律,使得轮式机器人轨迹跟踪误差快速收敛至0,实现了移动机器人对期望轨迹的快速跟踪。通过仿真实验与非线性快速终端滑模控制器和传统滑模控制其进行对比,验证了改进非线性快速终端滑模控制器的优越性。

全超导托卡马克核聚变发电装置快控电源的干扰抑制离散积分滑模电流控制

全超导托卡马克核聚变发电装置(EAST)快控电源的首要性能指标是快速跟踪参考信号,以输出电流实现负载线圈的励磁,对等离子体的垂直位移进行反馈控制。EAST快控电源负载线圈受装置内部部件和真空内等离子体的影响,线圈感值会出现小范围内慢时变波动以及线圈上存在互感电动势干扰,传统比例-积分(PI)控制方法在电流跟踪控制过程中存在不足。为了实现干扰的抑制和应对负载波动,提出一种带干扰抑制的离散积分滑模控制方法,根据系统状态方程设计离散积分滑模控制器,结合滑模干扰观测器实现集总干扰的观测,对集总干扰进行前馈补偿控制。为了抑制抖振和加快收敛速度,设计一种新型平滑饱和函数和增益自适应观测器,根据观测电流误差和跟踪电流误差自适应调整观测器增益。对比传统PI控制,仿真和实验验证了所提控制方法具有更加优良的电流跟踪特性,在输出电流超调更小的情况下动态响应更快,能够有效地抑制负载侧扰动,具有良好的鲁棒性。

PMSM无模型超螺旋快速积分终端滑模控制

针对永磁同步电机运行过程中因模型不确定、参数摄动和外部扰动等因素的影响,从而导致驱动系统性能下降的问题,提出一种新型控制策略。首先,为减少对系统数学模型的依赖,构建了一个新的超局部模型,用于描述永磁同步电机的转速环。其次,基于转速环的新型超局部模型,结合一种新型积分终端滑模面和改进超螺旋控制律来设计新型无模型超螺旋快速积分终端滑模控制器,实现了对转速的精确控制。再次,采用非奇异快速终端滑模面和双幂次趋近律设计改进扩展非奇异终端滑模扰动观测器,通过精确观测和前馈补偿未知扰动,有效地抑制参数摄动和外部扰动,增强了系统鲁棒性,提高系统的动态性能和稳态性能。最后,通过与传统控制方法的仿真和实验对比,证实所提算法转速抗超调能力提升为0.412 5%,转矩快速响应能力提升0.013 s。结果表明当存在未知扰动时,所提方法具有较强的鲁棒性和良好的抗干扰性。

非最小相位的单电感双输出Buck-Boost变换器的复合控制方法

单电感双输出Buck-Boost (SIDO Buck-Boost)变换器在电感电流连续模式(CCM)下工作存在交叉影响以及非最小相位特性的问题.为了解决上述问题,提出基于储能函数的扩张状态观测器(ESO)的改进非奇异快速终端滑模(NFTSM)和自抗扰控制(ADRC)相结合的控制策略.设计主路控制器,对系统的传递函数进行拟合得到ADRC范式,利用该范式对主路进行解耦控制.设计支路控制器,采用改进型ESO对储能函数进行观测,并将观测值反馈补偿到非奇异快速终端滑模控制律中,达到支路解耦的效果.为了抑制滑模控制的抖振问题,对趋近律进行改进.利用Lyapunov理论证明系统稳定性.基于硬件在环(HIL)实验平台进行实验验证.结果表明,所提控制策略与PI控制策略以及基于ESO的滑模控制策略相比,在超调量和响应时间上具有较好的效果.

基于干扰观测器与终端滑模的车辆纵向控制

为了消除未知干扰和不确定性对车辆纵向控制的影响,设计了基于干扰观测器和终端滑模控制的分层式车辆纵向控制系统.利用干扰观测器对系统干扰进行实时观测,实现对系统的反馈补偿,降低滑模控制的切换增益,从而抑制滑模控制的抖振.利用Lyapunov函数证明了控制系统的稳定性,并通过Carsim/Simulink进行了联合仿真试验.结果表明:在两种仿真工况条件下,控制器对参考速度跟踪效果良好,速度误差最大仅为0.22 m/s,干扰观测器对系统干扰能够准确快速估计,估计误差仅为0.003 14,切换逻辑执行器发挥良好;与传统滑模控制相比,所设计的控制器稳定性更好,抑制了滑模控制的抖振,实现了对车辆纵向速度的稳定跟踪.

基于阈值控制策略的Filippov Chay神经元动力学及其耦合同步

细胞内外带电离子的连续泵送和传递产生的电磁感应效应对神经元的电活动及模态转换会产生一定的影响,促使其展现出更加丰富的放电特性.文章基于电磁感应影响下的Chay神经元模型,引入了一种以膜电压为阈值的不连续控制策略,建立了相应的Filippov Chay神经元模型,探究了在阈值控制策略影响下的神经元放电节律转迁及相应的边界运动.首先,对系统的边界动力学及滑膜动力学进行了理论分析.其次,利用单双参数分岔图探究了系统多样的放电模式.再次,结合Matcont仿真及稳定性理论详细分析了系统的平衡点及其稳定性,并且利用快慢动力学分析法进一步研究了在阈值影响下所产生的滑膜动力学及各种边界运动的切换.最后,通过电突触耦合,对不同阈值条件下耦合神经元的同步问题进行了讨论.数值仿真结果表明,在阈值的调控下Filippov Chay系统会产生滑膜放电活动及相应的穿越运动和擦边运动,同时其放电周期数也会随着阈值呈现出不同的变化规律,且对于不同阈值下的电耦合情况而言,在系统实现完全同步后都会稳定在周期数较低的放电态.以上所得结果有助于更好地理解神经元滑膜的相关控制,对进一步探究生物神经系统中复杂放电活动和信息处理的动力学行为提供了一定的帮助.

永磁同步电机非线性增益非奇异快速终端滑模控制

为了研究传统滑模控制中系统误差在有限时间内无法收敛至0以及传统滑模控制中系统抖振与收敛速度互不兼容的问题,提出一种非奇异快速终端滑模控制与扰动观测器结合的速度控制器。通过将参数可变的非线性函数作为增益代替固定增益加入滑模控制策略中从而改善系统响应速度同时减小系统的抖振。针对转矩扰动对系统的影响,加入负载转矩扰动观测器并补偿到q轴电流中以进一步提高控制器抗负载扰动能力。根据李雅普诺夫稳定性理论对提出的新型滑模控制器进行稳定性证明,经过仿真和实验证明,电机在启动时响应快、无超调且抖振较小,在突加转矩时转速波动小且恢复时间迅速,证明了改进后的变增益非奇异终端滑模控制与传统非奇异快速终端滑模控制策略相比可以提高动态性能的同时抑制系统抖振、增强系统的鲁棒性。

基于有限时间干扰观测器的改进模型水下机器人自适应鲁棒容错控制

针对无人水下机器人(unmanned underwater vehicle,UUV)工作中存在的执行器故障,在系统不确定性与外界干扰下,提出一种基于有限时间扰动观测器(finite time disturbance observer,FTDO),并结合改进模型的自适应鲁棒容错控制方法。一方面,FTDO能在有限时间内对外界环境干扰进行估计;另一方面利用滑模控制加上径向基神经网络(radial basis function neyral network,RBF)的万能逼近特性,建立带有执行器故障的输入补偿;其中改进模型的引入解决了系统不确定性导致的输入饱和,提高了稳定性与鲁棒性;其次采用一种新型的双幂趋近律使滑模量在更短时间收敛到稳态误差界内;仿真与水池实验结果表明了所提方法相对于滑模控制有着更好的容错效果。

故障检测与重构下基于AFTSMO的ROV三维航迹跟踪控制

针对传统的滑模观测器在缆控水下机器人(ROV)系统状态估计与故障重构过程中存在渐近收敛、无法及时准确重构故障信号的问题,提出一种基于自适应快速终端滑模观测器(adaptive fast terminal sliding mode observer)的故障检测和控制优化方法。建立带有推进器故障、未知外界干扰和模型参数不确定性等复合干扰的ROV系统故障模型;设计具有自适应特性的快速终端滑模控制器,保证所有的状态估计误差在有限时间内收敛;通过等效输出误差注入法对推进器引起的故障进行估计重构。采用Lyapunov稳定性理论验证控制系统的稳定性,仿真结果表明,所设计的故障检测方法能够快速检测和重构故障,保证ROV系统较高的跟踪精度,并通过实验验证了所提算法的有效性。

弱电网下基于超螺旋滑模的LCL并网逆变器控制研究

针对LCL型滤波器的固有谐振、滤波器参数及弱电网下电网阻抗的波动会严重破坏并网系统稳定性的问题,提出了弱电网下基于超螺旋滑模的LCL并网逆变器控制策略。根据并网系统模型构建超螺旋滑模观测器,对滤波电容电压及逆变器侧输出电流进行估计,消除额外传感器需要,降低成本。采用具有非奇异快速终端滑模面控制(NFTSMC)的超螺旋滑模控制器来快速地跟踪参考给定电流及降低并网系统动稳态误差,且提高并网系统对外界干扰和参数不确定性的全局鲁棒性。仿真结果表明,当滤波参数摄动和电网阻抗变化时,系统表现出较强的鲁棒性,且并网电流的THD值保持在0.5%左右。