Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking

This paper develops a novel hierarchical control strategy for improving the trajectory tracking capability of aerial robots under parameter uncertainties.The hierarchical control strategy is composed of an adaptive sliding mode controller and a model-free iterative sliding mode controller(MFISMC).A position controller is designed based on adaptive sliding mode control(SMC)to safely drive the aerial robot and ensure fast state convergence under external disturbances.Additionally,the MFISMC acts as an attitude controller to estimate the unmodeled dynamics without detailed knowledge of aerial robots.Then,the adaption laws are derived with the Lyapunov theory to guarantee the asymptotic tracking of the system state.Finally,to demonstrate the performance and robustness of the proposed control strategy,numerical simulations are carried out,which are also compared with other conventional strategies,such as proportional-integralderivative(PID),backstepping(BS),and SMC.The simulation results indicate that the proposed hierarchical control strategy can fulfill zero steady-state error and achieve faster convergence compared with conventional strategies.

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.

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.

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.

Fuzzy super-twisting sliding mode control for municipal wastewater nitrification process

A fuzzy super-twisting algorithm sliding mode controller is developed for the dissolved oxygen concentration in municipal wastewater nitrification process. First, a fuzzy neural network(FNN) model is designed to approach the oxygen dynamics with unmeasurable disturbances, then the established model consists of the nominal system model and the modelling error. Second,based on the FNN model, a super-twisting sliding mode controller is employed to stabilize the nominal system and to suppress the modelling error. Moreover, the stability of the system is investigated and an adaption law is applied to ensure the robustness of the closed-loop system. Finally, the comparison experiments on benchmark simulation model no. 2(BSM2) of wastewater treatment show the advantages of the proposed method in multiple-units oxygen concentration control.

基于滑模自适应迭代学习的四旋翼无人机轨迹跟踪

针对四旋翼无人机轨迹跟踪问题,在考虑外部扰动的情况下,提出一种滑模自适应迭代学习的控制算法。所设计的控制器由两部分组成:第一部分是滑模子控制器,作为四旋翼无人机系统的反馈控制器;第二部分是迭代学习子控制器,作为无人机系统的前馈控制器。在迭代学习过程中,迭代学习子控制器的增益可以根据轨迹跟踪误差自适应改变,能够提高四旋翼无人机的轨迹跟踪效果。最后通过软件仿真对所提出的四旋翼无人机轨迹跟踪算法的有效性进行验证。

基于迭代学习的机械臂神经网络滑模控制

针对机械臂末端载荷变化引起机械臂抖动的情况,提出了将神经网络、滑模控制和迭代学习控制相结合的控制方法。首先,利用神经网络的逼近特性,逼近建模误差和外部干扰,使逼近值作为滑模控制器中新的增益,避免滑模控制器本身的抖振。然后,引入迭代学习控制,发挥滑模控制和迭代学习控制各自的优势,得到精度高、鲁棒性强的控制方法。最后,仿真结果表明,对于械臂末端载荷变化引起的不同范围的外部干扰,所提控制方法只需较少的迭代次数就可以达到较高的轨迹跟踪精度。利用迭代过程中误差最小的控制力矩对机械臂进行控制,可以使机械臂准确到达所需位置。

Saturated super-twisting sliding mode missile guidance

This paper concentrates on developing a missile terminal guidance law against a highly maneuvering target whose maneuvering acceleration is very close to that of the missile or even exceeds the missile normal acceleration in a finite period of time.A new saturated super-twisting algorithm is proposed and applied to the design of missile guidance law.The proposed algorithm has the advantages of simple structure,easy parameter tuning rules and a full utilization of the limit control input.The designed saturated super-twisting sliding mode guidance law is then employed in a missile guidance system.Simulation and its superior performance against strong maneuvering targets is demonstrated.

机械臂的P型闭环时变滑模迭代学习控制

针对周期运动的机械臂轨迹跟踪控制问题,在任意迭代初始值背景下,提出一种P型闭环滑模迭代学习控制算法。结合滑模控制原理,提出一种带遗忘因子的P型闭环滑模迭代学习控制策略,使处于任意初始位置的状态变量先迭代收敛到滑模面内,再在滑模面内收敛到期望位置,有效解决了任意迭代初始值的控制问题。从理论上证明了P型闭环滑模迭代学习控制算法的收敛性,给出了迭代收敛的条件。机械臂轨迹跟踪控制的仿真结果表明,当迭代初始值远离期望初始值时,机械臂的实际位置能精确跟踪期望位置,大的外部干扰不影响机械臂的轨迹跟踪性能。

基于迭代学习的工业机械臂抗干扰控制方法

为了克服工业机械臂的未知负载力矩和摩擦等干扰因素的影响,采用迭代学习算法设计了滑模控制律。首先建立了工业机械臂数学模型,然后设计了二阶非奇异快速终端滑模面,同时提出了滑模控制律,最后利用迭代学习方法来改善滑模控制律的抖振现象,并进行了收敛性分析。仿真结果表明:设计的基于迭代学习的滑模控制律能够有效消除各种干扰因素的影响,实现对工业机械臂运动轨迹的精确控制,最大跟踪误差仅为0.3mm,在实测验证中的最大跟踪误差也仅为0.17mm,平均运行时长仅为1.73s,大幅提升了对工业机械臂的控制精准度。

基于迭代和扰动观测的间隙实时补偿控制研究

针对电动伺服加载系统中传动间隙对加载力的影响,提出了一种基于迭代学习和非线性扰动观测器的滑模控制策略(SMC-ILC&NDOB)。通过迭代算法对传动间隙进行估计,同时利用扰动观测器对间隙的估计值进行补偿,在此基础上设计滑模控制器实现间隙的在线补偿,并根据Lyapunov稳定性定理证明了整个闭环控制系统的稳定性。借助MATLAB/Simulink软件对电动伺服加载系统和控制器进行仿真实验,对PID算法和基于迭代算法和扰动观测器的滑模控制方法进行对比。结果显示基于迭代学习和扰动观测器的滑模控制方法对传动间隙有着不错的补偿效果并拥有较好的鲁棒性。

基于指数增益迭代学习的机械臂二阶滑模控制方法

机械臂系统具有非线性和不确定性,针对其精确跟踪控制问题,提出基于指数增益迭代学习的二阶滑模控制算法。首先,采用滑模控制增强系统对外界非重复干扰的鲁棒性,采用二阶滑模方法使控制器产生连续的控制信号,以减轻传统滑模控制的抖振问题;其次,结合指数增益迭代学习控制逼近由摩擦力等周期性扰动引起的有界重复性扰动,通过设置指数增益系数以提高迭代的收敛速度,该方法既能减小系统的跟踪误差又能保证系统的全局渐近稳定性,提高系统的动态性能;最后,分析算法收敛的充分条件,以二自由度机械臂为例对所提方法进行理论数值仿真。仿真结果表明:所提控制方法可以保证系统的稳定运行,输出跟踪误差收敛到接近零的邻域,提高了系统的控制精度,对干扰保持了良好的鲁棒性。

Sliding Mode Formation Control of Nonlinear Multi-Agent Systems with Local Lipschitz Continuous Dynamics

In this paper, the multi-agent formation problem of networked nonlinear multi-agent systems with local Lipschitz continuous dynamics under directed interaction topology, is investigated. Based on the nonlinear dynamics satisfying locally Lipschitz continuous conditions, three kinds of sliding mode controllers are proposed to solve the problem of multi-agent formation control. Using integral sliding mode controller in first-order system, formation shape is achieved within finite time. For second-order system, on the one hand, non-singular terminal sliding mode function is adopted to accomplish the system asymptotic convergence. Furthermore, super-twisting algorithm is proposed to make multi-agent achieve the desired formation within finite time. Lyapunov functions are applied in the whole paper to ensure the system stability. Numerical simulation examples are provided to demonstrate the effectiveness of the proposed sliding mode control methods.

非线性动力学模型中的分步式超扭曲/终端滑模协议:在气垫船等混沌系统的应用

Fractional terminal and super-twisting as two types of fractional sliding mode controller are addressed in the present paper.The proposed methodologies are planned for both the nonlinear fractional-order chaotic systems and the nonlinear factional model of Hovercraft.The suggested procedure guarantees the asymptotic stability of fractional-order chaotic systems based on Lyapunov stability theorem,by presenting a set of fractional-order laws.Compared to the previous studies that concentrate on sliding mode controllers with unwanted chattering phenomena,the proposed methodologies deal with chattering reduction of terminal sliding mode controller/super twisting to converge to desired value in finite time,consequently.The main advantages of the offered controllers are 1)closed-loop system stability,2)robustness against external disturbances and uncertainties,3)finite time zero-convergence of the output tracking error,and 4)chattering phenomena reduction.Finally,the simulation results show the performance of the approaches both on the chaotic and Hovercraft models.

Second-order Sliding Mode Approaches for the Control of a Class of Underactuated Systems

In this paper, first-order and second-order sliding mode controllers for underactuated manipulators are proposed. Sliding mode control(SMC) is considered as an effective tool in different studies for control systems. However, the associated chattering phenomenon degrades the system performance. To overcome this phenomenon and track a desired trajectory, a twisting, a supertwisting and a modified super-twisting algorithms are presented respectively. The stability analysis is performed using a Lyapunov function for the proposed controllers. Further, the four different controllers are compared with each other. As an illustration, an example of an inverted pendulum is considered. Simulation results are given to demonstrate the effectiveness of the proposed approaches.

High-order sliding mode control of a doubly salient permanent magnet machine driving marine current turbine

Due to the harsh and changeable marine environment,one low speed stator-permanent magnet machine named doubly salient permanent magnet machine with toothed pole is applied for marine current energy conversion system.Indeed,this machine has simple structure,intriguing fault tolerance,and higher power density,which could adequately satisfy the different complicated operation conditions.However,its permanent magnet flux-linkage has the same variation period as the inductance which leads to a strong nonlinear coupling system.Moreover,the torque ripple caused by this special characteristics,uncertainty of system parameters and disturbance of load greatly increases the difficulty of control in this strongly coupling system.Consequently,the classical linear PI controller is difficult to meet the system requirement.In this paper,the high-order sliding mode control strategy based on the super-twisting algorithm for this system is creatively utilized for the first time.The stability of the system within a limited time is also proved with a quadratic Lyapunov function.The relative simulation results demonstrate convincingly that,the high-order sliding mode control has little chattering,high control accuracy and strong robustness.

基于自适应迭代优化FSMO的PMSM无感控制

针对磁链滑模观测器(flux sliding mode observer,FSMO)中存在的抖振以及转子位置估计精度的问题,提出了一种自适应迭代磁链滑模观测器(adaptive iterative flux sliding mode observer,AIFSMO)。首先,构建了以电流和磁链为状态变量的FSMO模型;其次,为了减少计算FSMO最优增益的迭代次数,构建了带有速度和电流的误差准则函数对其进行自适应调整,减少了系统的抖振;最后,与转子速度自适应辨识相结合,设计了改进转子位置估计器,在稳态、转速突变和负载突变3种工况下进行仿真测试。测试结果表明,与基于PLL(phase locked loop,PLL)的FSMO相比,消除了系统的抖振,提高了转子速度和位置的估计精度,在转速和负载突变时使系统的动态性能得到加强,减小了相位延迟。

迭代滑模增量反馈及在船舶航向控制中的应用

针对一类不确定非线性受扰动系统,提出一种基于非线性迭代滑模变结构的增量反馈控制算法.通过对系统输出迭代设计非线性滑动模态,并利用增量反馈控制,无需对不确定项的估计,在系统输入增益符号已知的条件下可自动寻找使系统稳定的控制量,避免了变结构控制的抖振以及输出反馈控制的稳态误差与超调问题,强化了变结构控制的不变性特点.对不同船型及舵机模型的船舶航向控制进行了仿真,结果表明,系统阶跃响应超调得到有效抑制,定常干扰下的静态误差得到消除,且控制器对模型摄动及干扰变化不敏感、设计参数易于调节.

风帆助航船舶运动的模糊自适应迭代滑模控制

针对风帆助航船舶运动模型的不确定性和高度非线性特点,设计了一种自适应非线性滑模控制器。该控制器利用非线性双曲正切函数对系统输出进行迭代滑动模态设计,应用滑模面反馈控制方法,无需对系统的不确定项和外界干扰进行估计,根据双曲正切函数的严格有界性和控制输入约束条件证明了控制器稳定性,同时引入模糊系统对迭代滑模参数进行优化,增强控制器的自适应性。以"文竹海"号76000DWT散货船为目标进行控制仿真,结果表明,所设计控制器对系统模型不确定参数摄动及风浪作用不敏感,具有强鲁棒性,且与迭代滑模控制器相比所得控制量输出更加合理有效。