舰船混沌运动的单输入自适应变结构控制

针对在舰船混沌运动控制中由模型不确定性及外部扰动无法确知所引起的控制结果无法保证的问题,采用自适应控制与滑模变结构控制相结合的方法,在设计切换函数时,将符号函数转移到控制输入的一阶导数当中,有效抑制了变结构控制中的抖振问题,并提出了一种单输入自适应滑模变结构控制方法.实验结果表明,与传统滑模变结构控制相比,新方法能够在系统模型具有不确定性及未知外部扰动的情况下实现舰船混沌运动的良好控制,为舰船混沌运动控制提供了一种可靠的工程实现途径.     

GBF-CMAC和滑模控制的柔性结构系统控制

针对一类不确定系统的跟踪控制,设计了一种将GBF-CMAC（cerebellar model articulation controller with Gauss basis function）与滑模控制相结合的控制系统。利用符号距离和分层结构减少了神经网络所需存储器的数量,并提出了一种神经网络参数的自适应学习律。将设计的控制器用于含有不确定性和欠驱动结构的高阶柔性直线结构系统的跟踪控制,并与一般滑模控制和积分滑模控制进行了比较。实验结果表明,所设计的控制器不仅具有较好的鲁棒性,而且改善了滑模控制存在的抖振问题。同时通过调整神经网络的参数对抖振进行控制,实现了抖振和跟踪性能之间的最优选择。     

基于滑模控制的折叠翼飞行器辅助机动研究

基于滑模控制策略,研究了折叠翼飞行器辅助机动问题.分析了系统折叠角与气动参数的关系,把机翼折叠角看成额外的控制输入,构造了包含折叠辅助机动的飞行器动力学模型.针对非线性系统,加入混合干扰,设计了非奇异动态终端滑模控制(NDTSMC)器,能够较好地抑制折叠翼飞行器的不确定性,同时完成姿态跟踪控制.仿真结果表明,NDTSMC改善了折叠翼飞行器的控制精度和鲁棒性能,具有较好的抖振消除效果.与传统飞行器相比,加入折叠辅助机动的折叠翼飞行器拥有更高的机动性和抗干扰能力.     

Adaptive Chattering Free Neural Network Based Sliding Mode Control for Trajectory Tracking of Redundant Parallel Manipulators

In this paper, an adaptive chattering free neural network‐based sliding mode control (ACFN‐SMC) method is proposed for tracking trajectories of redundant parallel manipulators. ACFN‐SMC combines adaptive chattering free radial basis function neural networks (RBFN), sliding mode control with online updating the robust term parameters, and a nonlinear compensation item for reducing tracking errors. The stability of the closed‐loop system with modeling uncertainties, frictional uncertainties, and external disturbances is ensured by using the Lyapunov method. The proposed controller has a simple structure and little computation time while securing dynamic performance with expected quality in tracking trajectories of redundant parallel manipulators. In addition, the ACFN‐SMC strategy does not need to know the upper bound of any uncertainties. From the simulation results, it is evident that the proposed control strategy not only has significantly higher robustness capability for uncertainties but also can achieve better chattering elimination when compared with those using existing intelligent control schemes.     

Robust control of a class of under-actuated mechanical systems with model uncertainty

Robust control of under-actuated mechanical systems (UMSs) with model uncertainty is still a challenging problem. For UMSs, the model parametric uncertainties make it difficult to precisely calculate the isolated equilibrium point corresponding to a fixed input. Without an accurate destination state, many set-point control methods cannot eliminate the positioning errors. An improved sliding mode control (ISMC) method is proposed to solve the robust control problem for a class of UMSs with model uncertainty and input disturbance. A balance variable is introduced in the sliding surface design to compensate for the disturbance caused by the inaccurate destination state, and the ISMC method is proposed to make the system state reach the sliding surface in finite time. Linear matrix inequality approach and particle swarm optimisation algorithm are applied to design the sliding mode surface parameters. The simulation results on an UMS are presented to show the effectiveness of the proposed scheme.     

Variable structure control with sliding mode prediction for discrete-time nonlinear systems

A new variable structure control algorithm based on sliding mode prediction for a class of discrete-time nonlinear systems is presented. By employing a special model to predict future sliding mode value, and combining feedback correction and receding horizon optimization methods which are extensively applied on predictive control strategy, a discrete-time variable structure control law is constructed. The closed-loop systems are proved to have robustness to uncertainties with unspecified boundaries. Numerical simulation and pendulum experiment results illustrate that the closed-loop systems possess desired performance, such as strong robustness, fast convergence and chattering elimination.     

基于RBF神经网络滑模控制的车辆横向控制研究

针对车辆横向控制系统中滑模控制器存在的抖振现象对转向机械结构带来的损耗问题,提出了一种基于RBF神经网络的滑模控制算法。利用RBF神经网络较强的自学习能力实时在线调节滑模控制器的切换项增益参数,增强系统的抗干扰能力与动态性能。将车辆实际参数代入仿真数学模型中,在Simulink仿真环境中进行对比仿真实验,仿真结果表明:该控制算法跟踪性能好,能够有效降低滑模控制器的抖振,满足车辆横向控制要求。     

Discussions on Smooth Modifications of Integral Sliding Mode Control

Sliding mode control (SMC) contains two phases, namely reaching and sliding phases, where the invariance of SMC is not guaranteed during the reaching phase. Integral SMC (ISMC) eliminates the reaching phase such that the invariance is guaranteed from the initial time instant. Several smoothing techniques have been applied to reduce chattering in the ISMC, including boundary layer, high-order SMC, low-pass filtering, etc. In this study, we discuss pros and cons of these techniques and suggest a simple and effective solution to attenuate chattering in the ISMC. In the suggested solution, the discontinuous part of the ISMC law is smoothed by a low-pass filter based on the equivalent control method. The resultant ISMC can not only avoid the trade-off among chattering, tracking accuracy, and robustness, but also act as a disturbance observer to exactly estimate and reject uncertainties. Numerical results have been provided to verify the arguments of this study.     

An adaptive integral sliding mode FTC scheme for dissimilar redundant actuation system of civil aircraft

ABSTRACT

This paper proposed a new adaptive integral sliding mode FTC scheme to deal with the actuator faults and failure. The scheme combines integral sliding mode control, control allocation scheme and adaptive strategy. The unknown actuator faults are handled by adaptive modulation gain of nonlinear ISMC law. To cope with complete failure, control allocation scheme is integrated with the baseline controller to provide tolerance. The proposed strategy relies on the estimate of actuator effectiveness. Therefore, an adaptive sliding mode observer based fault reconstruction scheme is proposed in this paper. The proposed scheme is implemented on dissimilar redundant actuation system driven by hydraulic and electro-hydraulic actuators. In nominal and faulty conditions, both actuators are contributing to achieving the desired control surface deflection. However, when the actuator failure occurs, the control signals are reallocated to the redundant actuator. The problem of dynamics mismatch is addressed using fractional order controller designed in an inner loop. The comparison with the existing literature is also conducted in the simulation to validate the dominant performance.     

永磁同步电动机混沌系统光滑二阶滑模控制

提出基于二阶滑模的控制方法控制永磁同步电动机（PMSM）中的混沌现象。利用Lyapunov函数构造了一种新的滑模面,能保证在滑模面上系统状态在有限时间内稳定到原点。控制器的设计采用了光滑二阶滑模方法,控制输入为光滑的函数,能有效消除抖振现象。仿真的结果也验证了控制方法的有效性。     

空间三关节机器人模糊积分滑模控制

研究提高关节机器人轨迹跟踪控制的性能,由于关节机器人运动中产生振动,影响系统的稳定性能。为解决上述问题,提出了一种反馈线性化的自适应模糊积分滑模控制方法。在上述方法的基础上,对机器人非线性动力学模型反馈线性化。为了进一步提高滑模控制的精度,设计了一种积分滑模面的滑模控制器,可以减弱积分滑模控制的抖振。通过设计一个模糊控制器,根据积分滑模面的大小自适应地调节积分滑模控制的切换部分,达到削弱抖振的目的。利用李亚普诺夫定理证明了控制系统的稳定性。仿真结果表明,改进方法有效地提高了关节机器人跟踪控制性能。     

可逆冷带轧机速度张力系统的动态滑模解耦控制

为削弱可逆冷带轧机速度张力系统中各变量间的非线性耦合影响,本文提出了一种基于幂指数趋近律的微分几何动态滑模解耦控制方法.首先,应用微分几何理论,通过非线性状态反馈和坐标变换,实现了可逆冷带轧机速度张力非线性耦合系统的输入/输出动态解耦和线性化.其次,针对解耦后得到的各独立线性子系统,综合考虑可逆冷带轧机速度张力系统的负载扰动、参数摄动和未建模动态等不确定部分的影响,基于幂指数趋近律设计了动态滑模控制器.理论分析表明,所提出的控制方法能够保证闭环系统渐近稳定,并能有效削弱系统抖振.最后,对某1422mm可逆冷带轧机速度张力非线性耦合系统进行仿真,并同其他解耦控制方法相比较,结果验证了所提出方法的有效性.     

Motion Control of Rigid Robot Manipulators via First and Second Order Sliding Modes

A motion control strategy for rigid robot manipulators based on sliding mode control techniques and the compensated inverse dynamics method is presented in this paper. The motivation for using sliding mode mainly relies on its appreciable features, such as simplicity and robustness versus matched uncertainties and disturbances. Furthermore the proposed approach avoids the estimation of the time-varying inertia matrix. As a preliminary step a first order sliding mode control law is presented. Then a second order strategy is discussed. In both cases the problem of chattering, typical of sliding mode control, is suitably circumvented. Simulations results demonstrates the good tracking properties of the proposed control strategy.     

SLIDING MODE PREDICTION TRACKING CONTROL DESIGN FOR UNCERTAIN SYSTEMS

In this paper, a tracking control algorithm based on sliding mode prediction for a class of discrete‐time uncertain systems is presented. By creating a special model to predict the future sliding mode function value and by combining feedback correction and receding horizon optimization approaches, which are extensively applied in predictive control strategy, a discrete‐time sliding mode control law for tracking problem is constructed. With the designed control law, closed‐loop systems have strong robustness to matched or unmatched uncertainties as they eliminate chattering. Besides, in the robustness analysis, the boundary condition for uncertainties, which is a universal presupposition in sliding mode control method, is not required. Numerical simulation and cart‐pendulum experiment results illustrate the validity of the proposed algorithm.     

滑模预测离散变结构控制

研究了不确定离散时间系统的变结构控制设计问题,提出了基于滑模预测思想的离散变结构控制系统设计新思路.该方法综合考虑抖振、鲁棒性以及控制量约束等指标要求,利用当前及过去时刻的滑模信息预测未来时刻的滑模动态,实现了滚动优化求解.仿真结果表明,该方法可有效消除抖振现象,并能够保证闭环系统的鲁棒稳定性.     

Design of a chatter-free terminal sliding mode controller for nonlinear fractional-order dynamical systems

This paper investigates the problem of robust control of nonlinear fractional-order dynamical systems in the presence of uncertainties. First, a novel switching surface is proposed and its finite-time stability to the origin is proved. Subsequently, using the sliding mode theory, a robust fractional control law is proposed to ensure the existence of the sliding motion in finite time. We use a fractional Lyapunov stability theory to prove the stability of the system in a given finite time. In order to avoid the chattering, which is inherent in conventional sliding mode controllers, we transfer the sign function of the control input into the fractional derivative of the control signal. The proposed chattering-free sliding mode technique is then applied for stabilisation of a broad class of three-dimensional fractional-order chaotic systems via a single variable driving control input. Simulation results reveal that the proposed fractional sliding mode controller works well for chaos control of fractional-order hyperchaotic Chen, chaotic Lorenz and chaotic Arneodo systems with no-chatter control inputs.     

Adaptive neural integral sliding‐mode control for tracking control of fully actuated uncertain surface vessels

This paper develops a novel adaptive neural integral sliding‐mode control to enhance the tracking performance of fully actuated uncertain surface vessels. The proposed method is built based on an integrating between the benefits of the approximation capability of neural network (NN) and the high robustness and precision of the integral sliding‐mode control (ISMC). In this paper, the design of NN, which is used to approximate the unknown dynamics, is simplified such that just only one simple adaptive rule is needed. The ISMC, which can eliminate the reaching phase and offer higher tracking performance compared to the conventional sliding‐mode control, is designed such that the system robust against the approximation error and stabilize the whole system. The design procedure of the proposed controller is constructed according to the backstepping control technique so that the stability of the closed‐loop system is guaranteed based on Lyapunov criteria. The proposed method is then tested on a simulated vessel system using computer simulation and compared with other state‐of‐the‐art methods. The comparison results demonstrate the superior performance of the proposed approach.     

Trajectory Tracking Control of Multi-DOF Robot without Considering System Dynamics

In this study, two different control logics have been designed for the position control of a robot with five degrees of freedom (DOFs). First, a sliding mode control with a sliding perturbation observer (SMCSPO) has been proposed. The SMCSPO is robust against perturbation, which is the sum of nonlinearities, parametric uncertainties, and external disturbances. To implement the SMCSPO, linear parameters of the system are required; however, these are difficult to identify. Moreover, it is exigent to derive the equation of motion for the multi-DOF robot. Accordingly, an integral sliding mode control (ISMC) has been designed for the position control of this multi-DOF robot. The ISMC controller does not require a mathematical model of the system. The ISMC control input applies a switching gain to compensate for the perturbation and system dynamics. In comparison with the SMCSPO, the ISMC has improved the tracking performance of the system because of its unique characteristics. Both control schemes have been implemented in MATLAB/Simulink. It has been observed that the tracking error of each ISMC joint is lower than that of the SMCSPO.

     

可控励磁直线同步电动机的全局积分Terminal滑模控制

为提高可控励磁直线磁悬浮同步电动机进给系统的快速性与鲁棒性,提出全局积分Terminal滑模控制策略.构造新型的全局积分Terminal滑模面,对系统状态任意初值可在有限时间内收敛到零点,在趋近律中引入衰减因子,可减小系统抖振;在构造滑模面和趋近律的基础上设计全局积分Terminal滑模速度控制器;为进一步削弱滑模控制的抖振,减小切换增益,用径向基函数神经网络设计扰动观测器,并对扰动进行前馈补偿控制.仿真结果表明全局积分Terminal滑模控制策略能够明显改善系统的动态性能,缩短误差的收敛时间,提高系统抑制扰动的能力,削弱系统的抖振,增强系统的鲁棒性.     

电动汽车TCS滑模控制器设计

针对电动汽车在冰雪低附着极端工况极易出现的驱动轮过度滑转问题,以电动汽车驱动电机转矩为控制变量,设计了一种电动汽车驱动防滑防牵引力控制系统(Traction control system,TCS)滑模控制器,控制器通过调节驱动电机转矩,将滑转率控制在目标值附近,使汽车持续获得最大路面附着,防止车轮过度滑转,对应用滑模控制出现的抖振问题,设计了一种改进的指数型趋近律,用以削弱系统抖振。仿真结果表明,设计的TCS滑模控制器通过控制驱动电机转矩能将汽车的滑转率控制在目标值附近,使得汽车持续获得最大的路面附着,充分抑制汽车打滑,提高了汽车行驶稳定性,在整个控制过程中驱动电机转矩和状态变量收敛快速且十分平滑,抖振削弱效果良好。