智能汽车轨迹跟踪MPC-RBF-SMC协同控制策略研究

针对自动驾驶车辆行驶过程中模型失配以及外部环境干扰导致车辆轨迹跟踪环节精确性不高的问题,提出了一种结合车辆运动学模型预测控制(MPC)、径向基(RBF)神经网络和滑模控制(SMC)的轨迹跟踪控制策略。通过建立车辆运动学MPC模型计算当前状态车辆期望横摆角速度,并将其与实际横摆角速度的偏差输入RBF-SMC控制器,利用RBF快速逼近非线性模型的特点,结合滑模控制输出前轮转角,实现车辆的横向轨迹跟踪控制。仿真结果表明,与传统的控制器相比,该方法轨迹跟踪精度显著提高,并在不同行驶工况下表现出较好的鲁棒性。

Asynchronous Learning-Based Output Feedback Sliding Mode Control for Semi-Markov Jump Systems: A Descriptor Approach

This paper presents an asynchronous output-feed-back control strategy of semi-Markovian systems via sliding mode-based learning technique.Compared with most literature results that require exact prior knowledge of system state and mode information,an asynchronous output-feedback sliding sur-face is adopted in the case of incompletely available state and non-synchronization phenomenon.The holonomic dynamics of the sliding mode are characterized by a descriptor system in which the switching surface is regarded as the fast subsystem and the system dynamics are viewed as the slow subsystem.Based upon the co-occurrence of two subsystems,the sufficient stochastic admissibility criterion of the holonomic dynamics is derived by utilizing the characteristics of cumulative distribution functions.Furthermore,a recursive learning controller is formulated to guarantee the reachability of the sliding manifold and realize the chattering reduction of the asynchronous switching and sliding motion.Finally,the proposed theoretical method is substantia-ted through two numerical simulations with the practical contin-uous stirred tank reactor and F-404 aircraft engine model,respectively.

Robust design of sliding mode control for airship trajectory tracking with uncertainty and disturbance estimation

The robotic airship can provide a promising aerostatic platform for many potential applications.These applications require a precise autonomous trajectory tracking control for airship.Airship has a nonlinear and uncertain dynamics.It is prone to wind disturbances that offer a challenge for a trajectory tracking control design.This paper addresses the airship trajectory tracking problem having time varying reference path.A lumped parameter estimation approach under model uncertainties and wind disturbances is opted against distributed parameters.It uses extended Kalman filter(EKF)for uncertainty and disturbance estimation.The estimated parameters are used by sliding mode controller(SMC)for ultimate control of airship trajectory tracking.This comprehensive algorithm,EKF based SMC(ESMC),is used as a robust solution to track airship trajectory.The proposed estimator provides the estimates of wind disturbances as well as model uncertainty due to the mass matrix variations and aerodynamic model inaccuracies.The stability and convergence of the proposed method are investigated using the Lyapunov stability analysis.The simulation results show that the proposed method efficiently tracks the desired trajectory.The method solves the stability,convergence,and chattering problem of SMC under model uncertainties and wind disturbances.

Sliding-Mode-Based Attitude Tracking Control of Spacecraft Under Reaction Wheel Uncertainties

The attitude tracking operations of an on-orbit spacecraft with degraded performance exhibited by potential actuator uncertainties(including failures and misalignments) can be extraordinarily challenging. Thus, the control law development for the attitude tracking task of spacecraft subject to actuator(namely reaction wheel) uncertainties is addressed in this paper. More specially, the attitude dynamics model of the spacecraft is firstly established under actuator failures and misalignment(without a small angle approximation operation). Then, a new non-singular sliding manifold with fixed time convergence and anti-unwinding properties is proposed, and an adaptive sliding mode control(SMC) strategy is introduced to handle actuator uncertainties, model uncertainties and external disturbances simultaneously. Among this, an explicit misalignment angles range that could be treated herein is offered. Lyapunov-based stability analyses are employed to verify that the reaching phase of the sliding manifold is completed in finite time, and the attitude tracking errors are ensured to converge to a small region of the closest equilibrium point in fixed time once the sliding manifold enters the reaching phase. Finally, the beneficial features of the designed controller are manifested via detailed numerical simulation tests.

码垛机器人的幂次指数趋近律变结构控制

为提高码垛机器人的控制精度,并保证系统在存在建模误差及扰动时的鲁棒性,设计了一种基于幂次指数趋近律的变结构控制算法。建立了二连杆机械臂数学模型,分析了三种趋近律的缺点,比较并提出了幂次指数趋近律。提出了使用求解微分方程的办法分三个阶段来研究算法的鲁棒性。分析了有界综合扰动极限值与控制器参数之间的关系。使用新算法得出了机器人在不含扰动时的仿真结果,解出了变结构控制三个阶段的微分方程,得出了机械臂在存有建模误差及扰动时的仿真结果。幂次指数趋近律变结构控制算法提高了码垛机器人的控制精度,在系统存在各种误差及扰动条件下具有极强鲁棒性并依然可以保证很高的控制精度。

基于双环自适应滑模的移动机器人轨迹跟踪控制

为了提升移动机器人轨迹跟踪精度,针对传统双环控制内外环协调性差、抗扰性弱的问题,文章提出双环自适应滑模的控制方法。为消除传统滑模控制(sliding mode control, SMC)方法中的趋近阶段,设计新型时变积分终端滑模控制器以保证系统状态始终位于滑模面,并通过控制器参数调节实现内环姿态误差和外环位置误差的快速收敛;构建基于势垒函数的增益调控方法,保证在扰动上界未知的情况下有效地抑制状态抖振,提高轨迹跟踪系统的抗干扰能力。对所提方法进行的验证分析结果表明,相较于现有的双环控制方法,该文轨迹跟踪控制方法精度更高、鲁棒性更强。

音圈电机全局自适应非奇异快速终端滑模控制

为了改善音圈电机驱动系统的动态性能,课题组提出了一种全局自适应非奇异快速终端滑模控制策略。在非奇异快速终端滑模控制器的基础上,引入全局滑态因子,改善系统的瞬态响应;同时将自适应控制和非奇异快速终端滑模控制相结合,利用自适应控制可以根据系统的实时状态和外部干扰自动调整参数的特点,来减小扰动、提高系统的鲁棒性和抗干扰性;将控制律中的符号函数改为一种边界层的饱和函数来削弱振动;通过李亚普诺夫稳定性理论证明所提出的控制器的稳定性;最后,将全局自适应非奇异快速终端滑模控制与比例积分微分控制(proportional integral derivative,PID)和滑模控制(sliding mode control,SMC)进行仿真对比。结果表明:与PID控制和滑模控制相比,所提出的全局自适应非奇异快速终端滑模控制提高了系统的动态响应速度和控制精度,有效改善了系统的动态性能。

基于前馈+预测LQR的智能车循迹控制器设计

为提升智能车辆循迹性能,基于线性二次调节器(linear quadratic regulator,LQR)理论和滑模理论,提出了一种兼顾横纵向跟踪精度与转向稳定性的横纵向控制器。首先,构建了基于二自由度横向动力学模型的前馈LQR控制器。针对模型线性化后前馈LQR控制器转向稳定性降低的问题,结合恒定转弯率和速度(constant turn rate and velocity,CTRV)模型设计预测控制器,建立了基于实时车速-曲率模糊自适应预测时间的前馈LQR控制器。此外为提升纵向车速跟踪稳定性和跟踪精度,提出了一种基于滑模控制理论的纵向跟踪方法。并进行了联合仿真和硬件在环实验验证。结果表明:文中提出的横纵向控制器有效解决了跟踪精度与稳定性两者难以兼顾的问题,提升了智能车辆循迹性能。

SMC模式下RBCC发动机4 Ma工况性能仿真

为研究SMC模式下火箭混合比对RBCC发动机性能的影响规律,完成了氢/氧火箭推力室中心布局、二元定几何结构模型发动机飞行马赫数Ma_(0)=4、高度H=17 km弹道点流场仿真,获得了不同火箭混合比(MR=2、3、4、5、6、8)及燃烧室长度的推力、比冲性能。研究表明:在火箭燃气富燃条件下(MR<8),产生了正的火箭推力增益,且随着混合比的减小,火箭推力增益增加;二次燃烧过程受火箭射流与冲压主流剪切层掺混主导,在给定的基准燃烧室长度下,燃烧效率随着混合比的提高而增加,且火箭射流与冲压主流的超/超射流剪切层燃烧过程一直持续到喷管出口;通过增加燃烧室长度,火箭富燃燃气获得更为充分的燃烧,发动机性能显著提升,但在具体发动机设计中,燃烧室长度的选取需在燃烧效率与结构惩罚之间进行权衡。

基于SMC的飞机仿真器航道罗盘伺服系统研究

建立了飞机仿真器航道罗盘伺服系统数学模型,选择直流电动机作为系统的执行元件,采用滑模控制(SMC)设计位置环控制器,重点讨论了控制参数的选取。仿真和实验结果表明,与直接采用LQR方法设计的控制器相比,结合变结构控制选取的控制器具有较强的鲁棒性能,能够满足系统的快速定位要求。

基于滑模交叉耦合的双永磁电机转速同步控制

为降低双永磁电机在动态过程和扰动情况下的速度同步误差,研究了一种基于电流参考切换和滑模交叉耦合控制的方法。首先,建立了交叉耦合控制下的系统模型,并分析交叉耦合控制的作用机理;通过频域分析证明其能够降低速度同步误差,并给出了交叉耦合控制器参数设计方法;然后,为提升扰动情况下的速度同步误差收敛时间,提出了基于滑模的交叉耦合控制方法;最后,使用电流参考切换解决动态过程中受最大电流限制造成的速度同步性能不佳问题。实验结果表明,基于电流参考切换的滑模交叉耦合控制能够使扰动下速度同步误差收敛更快,同时有效降低动态过程中的速度同步误差。

改进扩张状态观测器下永磁同步电动机滑模控制

为了提高永磁同步电动机(permanent magnet synchronous motor,PMSM)伺服系统的鲁棒性,提出了一种基于改进扩张状态观测器(expanded state observer,ESO)和滑模控制(sliding mode control,SMC)相结合的复合控制器。首先,提出了一种基于新型趋近律的SMC,该新型趋近律中引入系统状态变量,使趋近速度变得与系统状态相关,同时能够保证系统状态在有限时间到达滑模面并收敛到零;其次,利用ESO估计系统状态并抵消外部扰动,且针对传统的fal函数易引起系统抖振和误差较大时引起系统增益大的问题,提出了一种新的fal函数;最后,在Matlab/Simulink中进行仿真。仿真结果表明:相比于使用传统SMC的系统,使用了该新型控制器的系统其响应时间快0.042 s,加入负载扰动时有更好的抗扰动性能,故在使用新型控制器下的系统有更好动态性能和控制精度。

计及叶轮不平衡的差动调速风电机组变桨距控制

为保证差动调速型风电机组在全风速区间内运行的能量效率及稳定性,在考虑叶轮不平衡、风剪切及塔影效应的影响下,提出了一种基于径向基(RBF)神经网络的滑模变结构控制(SMVSC)方法,以完成差动调速型风力机桨距的准确、快速调节。该方法将滑模误差引入其控制的自适应率中,通过在线调整RBF神经网络的权值和中心值来有效地抑制抖振效应。搭建了1.5 MW差动调速型风电机组仿真模型,在利用物理试验平台对仿真模型进行原理验证后,对所提RBF-SMVSC方法的控制效果进行了对比验证。研究结果表明:相较于PI和传统滑模控制独立变桨方法,在不同的风速条件下,所提控制方法不仅可以更加快速、精确地调节风力机转速和功率输出,还可以有效提高机组的能量捕获效率,减小不平衡载荷。

基于线性扩张状态观测器的挖掘机电液系统滑模控制

无人驾驶挖掘机器人实际工作环境恶劣,为提高铲斗在负载扰动下的轨迹跟踪精度,建立了挖掘机电液系统非线性数学模型,设计了基于线性扩张状态观测器的滑模控制器(Sliding mode controller based on linear extended state observer,SMC-LESO)。根据铲斗油缸活塞杆位移信号,利用设计的线性扩张状态观测器对系统的速度、加速度及负载扰动和不确定因素进行估计,解决了系统参数难以测量的问题。在此基础上,设计了滑模控制器,并证明了该控制器的Lyapunov稳定性。为进一步验证该控制器的有效性,建立了挖掘机电液比例控制系统的联合仿真模型,并与PID控制器、滑模控制器的轨迹跟踪精度进行对比。仿真结果表明,该控制器可以有效抑制扰动,位移跟踪精度高、鲁棒性强。

不同重力条件下含铰间间隙空间机械臂PD~μ-SMC轨迹跟踪控制

研究了重力对含铰间间隙空间机械臂的轨迹跟踪控制的影响。针对空间机械臂在安装、调试阶段处于地面重力环境,在应用过程中处于空间微重力环境,重力环境的改变会使得在地面设计、装配、调试好的控制器在空间应用时达不到良好的控制精度和效果的问题,设计了不需被控对象模型的分数阶PD滑模控制器(PDμ-SMC)对含铰间间隙空间机械臂进行控制,并基于李亚普诺夫理论证明了渐近稳定性。仿真结果表明该控制策略能有效地抑制外部干扰,实现含铰间间隙空间机械臂在不同重力环境及存在外部扰动情况下仍然能对期望轨迹进行准确快速跟踪。

基于SLADRC的三相交错并联DC-DC变换器稳压控制

针对三相交错并联型DC-DC变换器在输出侧负载和输入侧母线电压数值改变以及其他扰动影响下而出现的输出电压波动现象,提出一种滑模线性自抗扰控制策略。首先,建立三相交错并联DC-DC变换器在s域下的数学模型,并分析能量传输不平衡原理;然后,根据系统模型,设计合适的观测器和线性自抗扰控制器;进一步,为提高系统对输出电压波动的抑制能力,引入滑模控制,形成滑模线性自抗扰控制,提高系统的抗扰性和快速性;最后,设计多种工况对新型控制策略进行仿真验证和半实物仿真实验验证。结果表明:与传统控制策略相比,滑模线性自抗扰控制不仅具备优异的电压波动抑制能力,而且具有优越的稳态运行能力和暂态穿越能力,保证了系统能量传输间的平衡。

基于SMC的四旋翼无人机抗风扰研究

四旋翼无人机控制系统复杂、鲁棒性差、易受外界干扰,为了提高四旋翼无人机的控制精度,采取滑模变结构的控制方法。搭建四旋翼无人机的动态数学模型、电机模型和风场扰动模型,借助Matlab搭建SMC控制器,选择适当的参数和消除抖振方法,对四旋翼无人机的高度和姿态进行控制。实验结果证明,SMC控制器具有较好的动态性能和抗扰性。

Backstepping sliding mode control for uncertain strict-feedback nonlinear systems using neural-network-based adaptive gain scheduling

A neural-network-based adaptive gain scheduling backstepping sliding mode control（NNAGS-BSMC） approach for a class of uncertain strict-feedback nonlinear system is proposed.First, the control problem of uncertain strict-feedback nonlinear systems is formulated. Second, the detailed design of NNAGSBSMC is described. The sliding mode control（SMC） law is designed to track a referenced output via backstepping technique.To decrease chattering result from SMC, a radial basis function neural network（RBFNN） is employed to construct the NNAGSBSMC to facilitate adaptive gain scheduling, in which the gains are scheduled adaptively via neural network（NN）, with sliding surface and its differential as NN inputs and the gains as NN outputs. Finally, the verification example is given to show the effectiveness and robustness of the proposed approach. Contrasting simulation results indicate that the NNAGS-BSMC decreases the chattering effectively and has better control performance against the BSMC.

Robust H_∞ Load Frequency Control of Multi-area Power System With Time Delay:A Sliding Mode Control Approach

This paper is devoted to investigate the robust H∞sliding mode load frequency control(SMLFC) of multi-area power system with time delay. By taking into account stochastic disturbances induced by the integration of renewable energies,a new sliding surface function is constructed to guarantee the fast response and robust performance, then the sliding mode control law is designed to guarantee the reach ability of the sliding surface in a finite-time interval. The sufficient robust frequency stabilization result for multi-area power system with time delay is presented in terms of linear matrix inequalities(LMIs). Finally,a two-area power system is provided to illustrate the usefulness and effectiveness of the obtained results.

Neural network based adaptive sliding mode control of uncertain nonlinear systems

The purpose of this paper is the design of neural network-based adaptive sliding mode controller for uncertain unknown nonlinear systems. A special architecture adaptive neural network, with hyperbolic tangent activation functions, is used to emulate the equivalent and switching control terms of the classic sliding mode control （SMC）. Lyapunov stability theory is used to guarantee a uniform ultimate boundedness property for the tracking error, as well as of all other signals in the closed loop. In addition to keeping the stability and robustness properties of the SMC, the neural network-based adaptive sliding mode controller exhibits perfect rejection of faults arising during the system operating. Simulation studies are used to illustrate and clarify the theoretical results.