基于复合执行机构的再入弹头自适应反演控制

为了提高再入弹头命中精度和机动突防能力, 将质量滑块和单框架控制力矩陀螺(SGCMG) 配合使用, 以在弹头再入全过程中产生足够的姿态控制力矩. 针对再入系统物理参数及外界环境干扰的不确定性, 利用反演方法设计再入弹头姿态自适应控制器. 该控制器可以对转动惯量不确定性进行自适应补偿, 并且有效抑制力矩干扰对姿态控制系统的影响. 对某型再入弹头的仿真研究表明, 所提出的控制器可以实现姿态角的良好跟踪.

     

Chaos-PSO-based Motion Planning and Accurate Tracking for Position-posture Control of a Planar Underactuated Manipulator with Disturbance

Unlike a fully-actuated manipulator, the position-posture control of a planar underactuated manipulator (PUM) is more difficult, but the research on it is significant due to the wide practical applications. The existing control methods consider no external disturbance and are involved in the staged control idea, bringing the problems of nonsmooth control torque and time-consuming. A novel one-stage control approach is proposed in this paper for the position-posture control of a three-link PUM with the first free joint under the external disturbance. By analyzing the coupling relationship between its active joints and free joint, the position-posture control is transformed into the trajectory tracking control. Unlike the general trajectory planning, the trajectories of the active joints are planned to include several parameters. Meanwhile, the parameters are solved using a chaos particle swarm optimization algorithm to guarantee that all joint angles can reach to their desired angles. Then, to obtain the high trajectory tracking accuracy at every moment under the external disturbance, the nonlinear disturbance observer is constructed and a nonlinear fast terminal sliding mode tracking controller is designed. Finally, the feasibility and superiority of this strategy are verified via two simulations.

     

基于模糊控制的分布式电动车辆横摆力矩研究

为提高多轮分布式电驱动车辆在不同工况下的操纵稳定性,设计了一种基于直接横摆力矩控制的分层控制策略。上层以横摆角速度和质心侧偏角为控制变量,采用模糊控制进行目标运动状态跟踪,决策出所需要的横摆力矩。下层按设计的规则进行转矩分配。应用TruckSim和Matlab/Simulink建立车辆和控制器模型,分别在高、低附着等工况下进行联合仿真。仿真结果表明,设计的模糊控制方法能对车辆目标状态进行良好跟踪,相较于无控制状态能够提高车辆的操纵稳定性。     

机器人系统输出反馈重复学习轨迹跟踪控制

针对高度非线性多关节机器人的轨迹跟踪问题,提出一类输出反馈重复学习控制算法,使得在只有位置信息可测以及模型信息不确定的条件下即能获得良好的控制品质.非线性滤波器的引入解决了现实中速度信号较难获得的问题,重复学习控制策略实现了对周期性参考输入的渐近稳定跟踪.应用Lyapunov直接稳定性理论证明了闭环系统的全局渐近稳定性.三自由度机器人系统数值仿真结果表明了所提出的输出反馈重复学习控制的有效性.     

Neural Approximation-based Model Predictive Tracking Control of Non-holonomic Wheel-legged Robots

This paper proposes a neural approximation based model predictive control approach for tracking control of a nonholonomic wheel-legged robot in complex environments, which features mechanical model uncertainty and unknown disturbances. In order to guarantee the tracking performance of wheel-legged robots in an uncertain environment, effective approaches for reliable tracking control should be investigated with the consideration of the disturbances, including internal-robot friction and external physical interactions in the robot’s dynamical system. In this paper, a radial basis function neural network (RBFNN) approximation based model predictive controller (NMPC) is designed and employed to improve the tracking performance for nonholonomic wheel-legged robots. Some demonstrations using a BIT-NAZA robot are performed to illustrate the performance of the proposed hybrid control strategy. The results indicate that the proposed methodology can achieve promising tracking performance in terms of accuracy and stability.

     

Back-stepping Robust Control for Flexible Air-breathing Hypersonic Vehicle via α-filter-based Uncertainty and Disturbance Estimator

In this paper, a robust control scheme using back-stepping and α-filter-based uncertainty and disturbance estimator (UDE) is designed for flexible air-breathing hypersonic vehicle (FAHV) in the presence of severe external disturbances. Firstly, with the aid of back-stepping technique, the longitudinal dynamics of FAHV is separated into velocity and altitude subsystems. Feedback linearization (FL) is utilized to design control laws for each subsystem. Secondly, to enhance robustness of the controller, α-filter-based UDEs are constructed to estimate the lumped disturbances, including aerodynamic parameter uncertainties, flexible effects and external disturbances. More importantly, the performance superiority of α-filter-based UDE is clarified via frequency response analysis and comparisons with an extended state observer (ESO). Furthermore, the issue of tuning design parameter α is analyzed. The stability of closed-loop system is proved by Lyapunov stability theory. Simulation results demonstrate the effectiveness of the proposed control strategy.

     

High-Precision Position Tracking Control of Electro-hydraulic Servo Systems Based on an Improved Structure and Desired Compensation

How to improve the position tracking accuracy of electro-hydraulic servo system is a hot issue today. Full state feedback control has received widespread attention for its ability to significantly improve control performance, however, its practical application range is limited in view of the large influence of measurement noise. In terms of this issue, we propose an adaptive robust controller based on improved structure and desired compensation. Firstly, to reduce the impact of measurement noise, the actual state value is substituted by the corresponding desired value in the controller design based on model compensation and the adaptive model compensator. Then, we introduce a new auxiliary variable into the controller to optimize its structure. In addition, nonlinear robust control laws are integrated in the controller to balance unstructured uncertainties. Simulation analysis shows that the proposed control strategy not only achieves the asymptotic tracking when parameter perturbation exists, but also ensures a specified transient response and final tracing precision under the combined influence of structured and unstructured uncertainties. The results indicate that the control strategy has good control accuracy as well as strong robustness.

     

姿态变化一致有界的姿态稳定控制器设计

针对航天器姿态稳定控制问题, 设计一种迭代学习姿态控制器. 将连续非周期运动的姿态跟踪过程分解为队列重复运动, 采用前一周期的姿态跟踪误差修正后一周期的控制输入, 分别对未知参数和干扰构建有界迭代学习律, 给出航天器姿态稳定控制器, 并从理论上分析了闭环系统的渐近稳定性和姿态跟踪误差的一致有界性. 通过在轨捕获非合作目标过程中航天器姿态跟踪控制问题的数值仿真, 验证了迭代学习控制器的鲁棒性和强抗干扰性.

     

基于改进主从控制结构的海洋机器人零航速减摇鳍系统

利用零航速减摇鳍系统实现对海洋机器人在近水面低速航行时的横摇姿态控制. 基于零航速减摇鳍的非线 性动态特性和海洋机器人横摇解耦模型, 提出具有主从结构的横摇减摇控制规律. 设计具有积分滑模面的变结构控 制规律, 估算系统期望横摇扶正力矩, 并进一步结合非线性跟踪控制理论和反馈线性化方法, 建立减摇鳍子系统模 型, 设计从属控制规律驱动减摇鳍产生实际横摇稳定力矩. 仿真结果和理论分析表明, 所设计的控制规律是稳定且有 效的.

     

Desired Compensation Adaptive Robust Control of Electrical-optical Gyro-stabilized Platform with Continuous Friction Compensation Using Modified LuGre Model

Continuous friction compensation along with other modeling uncertainties is concerned in this paper, to result in a continuous control input, which is more suitable for controller implementation. To accomplish this control task, a novel continuously differentiable nonlinear friction model is synthesized by modifying the traditional piecewise continuous LuGre model, then a desired compensation version of the adaptive robust controller is proposed for precise tracking control of electrical-optical gyro-stabilized platform systems. As a result, the adaptive compensation and the regressor in the proposed controller will depend on the desired trajectory and on-line parameter estimates only. Hence, the effect of measurement noise can be reduced and then high control performance can be expected. Furthermore, the proposed controller theoretically guarantees an asymptotic output tracking performance even in the presence of modeling uncertainties. Extensively comparative experimental results are obtained to verify the effectiveness of the proposed control strategy.

     

Greenhouse climate fuzzy adaptive control considering energy saving

This paper proposes a fuzzy adaptive control approach to solve greenhouse climate control problem. The aim is to ensure the controlled environmental variables to track their desired trajectories so as to create a favorable environment for crop growth. In this method, a feedback linearization technique is first introduced to derive the control laws of heating, fogging and CO2 injection, then to compensate for the saturation of the actuators, a fuzzy logic system (FLS) is used to approximate the differences between controller outputs and actuator outputs due to actuator constraints. A robust control term is introduced to eliminate the impact of external disturbances and model uncertainty, and finally, Lyapunov stability analysis is performed to guarantee the convergence of the closed-loop system. Taking into account the fact that the crop is usually insensitive to the change of the environment inside the greenhouse during a short time interval, a certain amount of tracking error of the environmental variables is usually acceptable, which means that the environmental variables need only be driven into the corresponding target intervals. In this case, an energy-saving management mechanism is designed to reduce the energy consumption as much as possible. The simulation results illustrate the effectiveness of the proposed control scheme.

     

Four Wheel Independent Drive Electric Vehicle Lateral Stability Control Strategy

In this paper, a kind of lateral stability control strategy is put forward about the four wheel independent drive electric vehicle. The design of control system adopts hierarchical structure. Unlike the previous control strategy, this paper introduces a method which is the combination of sliding mode control and optimal allocation algorithm. According to the driver’s operation commands (steering angle and speed), the steady state responses of the sideslip angle and yaw rate are obtained. Based on this, the reference model is built. Upper controller adopts the sliding mode control principle to obtain the desired yawing moment demand. Lower controller is designed to satisfy the desired yawing moment demand by optimal allocation of the tire longitudinal forces. Firstly, the optimization goal is built to minimize the actuator cost. Secondly, the weighted least-square method is used to design the tire longitudinal forces optimization distribution strategy under the constraint conditions of actuator and the friction oval. Beyond that, when the optimal allocation algorithm is not applied, a method of axial load ratio distribution is adopted. Finally, CarSim associated with Simulink simulation experiments are designed under the conditions of different velocities and different pavements. The simulation results show that the control strategy designed in this paper has a good following effect comparing with the reference model and the sideslip angle \begin{document}$\,\beta$\end{document} is controlled within a small rang at the same time. Beyond that, based on the optimal distribution mode, the electromagnetic torque phase of each wheel can follow the trend of the vertical force of the tire, which shows the effectiveness of the optimal distribution algorithm.     

基于多LPV 模型的调度离线鲁棒预测控制

针对一类具有大工作区域和快时变特性的约束非线性系统, 采用多个线性参数时变(LPV) 模型近似描述原非线性系统. 对于各LPV 模型, 设计基于参数独立Lyapunov 函数的局部离线预测控制器. 构造各局部控制器间的切换策略, 在保证切换稳定性的同时, 使相互重叠的稳定域覆盖期望的工作区域. 仿真结果表明, 相比于已有的调度预测控制方法, 所提出的方法不仅能够保证控制输入在给定的约束范围内, 而且在局部控制器切换次数少的情况下, 获得良好的控制性能.

     

不确定扰动下双起升桥吊双吊具鲁棒自适应滑模同步协调控制

双起升桥吊双吊具存在的参数摄动和不确定干扰问题严重影响了双吊具同步协调运行的效果. 鉴于此, 分析桥吊双吊具不同工作模式的运行特性, 采用交叉耦合策略, 提出一种基于参数自整定的双吊具鲁棒自适应滑模同步协调控制方法. 采用变边界层技术解决滑膜控制需折中稳态误差和抖振平滑的难题, 利用自整定切换函数增益消除不确定扰动, 并利用Lyapunov 理论证明控制器的渐近稳定性. 桥吊控制实验表明了所提出方法的有效性.

     

Lane-keeping assistance control algorithm using differential braking to prevent unintended lane departures

This paper describes a hierarchical lane keeping assistance control algorithm for a vehicle. The proposed control strategy consists of a supervisor, an upper-level controller and a lower-level controller. The supervisor determines whether lane departure is intended or not, and whether the proposed algorithm is activated or not. To detect driver′s lane change intention, the steering behavior index has been developed incorporating vehicle speed and road curvature. To validate the detection performance on the lane change intention, full-scale simulator tests on a virtual test track (VTT) are conducted under various driving situations. The upper-level controller is designed to compute the desired yaw rate for the lane departure prevention, and for the guidance with ride comfort. The lower-level controller is designed to compute the desired yaw moment in order to track the desired yaw rate, and to distribute it into each tire′s braking force in order to track the desired yaw moment. The control allocation method is adopted to distribute braking forces under the actuator’s control input limitation. The proposed lane keeping assistance control algorithm is evaluated with human driver model-in-the-loop simulation and experiments on a real vehicle.     

无刷双馈电机自抗扰控制方法

针对无刷双馈电机非线性强耦合特性, 提出一种实现其高性能控制的自抗扰控制方法. 在控制电机同步坐标系下, 设计磁链自抗扰控制器和转速自抗扰控制器, 对系统内部的耦合影响和系统外部扰动进行观测和补偿, 实现非线性系统线性化控制. 该控制器具有较强的鲁棒性, 且不依赖电机模型. 仿真对比结果表明, 自抗扰控制器能够准确地估计和补偿系统的内外扰动, 控制精度高, 抗扰能力强, 能够实现磁链和电磁转矩的解耦, 进而实现磁链和转速相互独立控制, 是一种简单有效的高性能控制方法.

     

基于微分观测器的飞行模拟转台伺服系统非线性控制

飞行模拟器转台伺服系统是导弹飞行的重要模拟设备,用于获取实验数据。针对飞行模拟转台伺服系统在跟踪控制过程中存在参数不确定性、非线性摩擦等不确定性问题,提出了一种基于微分观测器的飞行模拟转台伺服系统非线性控制方法;考虑系统在跟踪控制过程中存在不确定性问题,设计了微分观测器来估计复合不确定扰动;设计非线性控制器来控制飞行模拟转台伺服系统,使得系统可以收敛到期望位置转角信号;通过李雅普洛夫稳定性证明控制器作用在系统条件下的鲁棒性;通过MATLAB/Simulink仿真试验平台验证了文中提出的控制策略能够使系统有效跟踪期望位置转角,具有一定工程应用价值;     

导弹姿态的自抗扰有限时间控制

针对导弹模型同时具有不确定性和执行机构饱和受限的问题, 首先针对模型不确定性, 将质心运动方程的非线性影响、耦合影响、外部环境干扰视为总干扰, 并设计扩展状态观测器对其进行实时估计; 然后针对舵偏角和角速度存在饱和受限的问题, 设计辅助系统和限幅微分器; 最后结合反演和有限时间稳定系统理论, 设计有限时间控制器, 以保证整个闭环系统在受限条件下能收敛到参考信号. 数值仿真结果表明, 所设计的控制器与理论分析结果一致, 是可行而有效的.

     

四旋翼无人机抗干扰轨迹跟踪控制

针对四旋翼无人机轨迹跟踪过程中存在的参数不确定与外界干扰问题,设计一种双闭环自适应控制策略.为了降低控制器设计复杂度,根据四旋翼无人机系统的欠驱动特性将系统分成姿态内环和位置外环.在扰动观测器的基础上,利用积分型反步控制算法完成无人机位置信息在外界干扰下的稳定跟踪控制.在扰动观测器的基础上,利用自适应滑模控制算法完成无...     

基于Backstepping 的非线性系统预设性能鲁棒控制器设计

针对一类具有外界扰动的严格反馈非线性系统,将Backstepping技术、预设性能控制和鲁棒控制相结合,提出一种预设性能鲁棒控制器设计方法.通过误差转换,建立系统等效误差模型,利用Backstepping和鲁棒控制逐步递推选择适当的Lyapunov函数设计预设性能鲁棒控制器.该控制策略兼顾系统的暂态和稳态性能,仿真实例表明了所提出设计方法的有效性.