TF/TA~2 trajectory tracking using nonlinear predictive control approach

1 .INTRODUCTIONThei mportance of terrain-following,terrain-avoid-ance ,andthreat-avoidance (TF/TA2) guidance forcruise missiles and aircraft is a well-recognized as-pect of military operations . Typically , the TF/TA2guidance system development consists of twomajor steps : (1) opti mal trajectory generationwithin maneuvering constraints considering ter-rain,obstacles and threats toincrease both surviv-ability and mission effectiveness ; (2) control lawdevelopment to followthe opti mal t…     

机器人轨迹跟踪连续预测控制

针对能够描述机械手动态特性的一类特殊仿射非线性系统 ,提出了一种非线性连续预测控制器。其预测模型通过对系统状态泰勒级数展开并做适当的截尾处理获得。此外 ,证明了非线性连续预测控制器的渐近跟踪特性 ,并给出了一种改进的预测控制方案。将非线性连续预测控制器应用于二自由度机械手轨迹跟踪控制。仿真结果证明了该控制器的有效性     

Transient Performance Improvement in Tracking Control for a Class of Nonlinear Systems with Input Saturation

This paper addresses the composite nonlinear feedback (CNF) control for a class of singleinput single-output nonlinear systems with input saturation to track a time varying reference target with good transient performance. The CNF control law consists of a tracking control law and a performance compensator. The tracking control law is designed to drive the output of the system to track the time varying reference target rapidly, while the performance compensator is used to reduce the overshoot caused by the tracking control law. The stability of the closed-loop system is established. The design procedure and the improvement of transient performance of the closed-loop system are illustrated with a numerical example and the controlled Van del Pol oscillator.     

Nonlinear Model Predictive Control-Based Guidance Algorithm for Quadrotor Trajectory Tracking with Obstacle Avoidance

This paper studies a novel trajectory tracking guidance law for a quadrotor unmanned aerial vehicle(UAV) with obstacle avoidance based on nonlinear model predictive control(NMPC)scheme. By augmenting a reference position trajectory to a reference dynamical system, the authors formulate the tracking problem as a standard NMPC design problem to generate constrained reference velocity commands for autopilots. However, concerning the closed-loop stability, it is difficult to find a local static state feedback to construct the terminal constraint in the design of NMPC-based guidance law. In order to circumvent this issue, the authors introduce a contraction constraint as a stability constraint, which borrows the ideas from the Lyapunov's direct method and the backstepping technique. To achieve the obstacle avoidance extension, the authors impose a well-designed potential field function-based penalty term on the performance index. Considering the practical application, the heavy computational burden caused by solving the NMPC optimization problem online is alleviated by using the dynamical adjustment of the prediction horizon for the real-time control. Finally, extensive simulations and the real experiment are given to demonstrate the effectiveness of the proposed NMPC scheme.     

基于H∞鲁棒动态逆的飞行器轨迹跟踪方法

利用非线性动态逆方法的精确线性化功能,结合H_∞控制理论,提出了一种阻力加速度能量标准轨迹的跟踪方法。通过动态逆将非线性的高超声速飞行器系统等效为线性对象,继而考虑非结构不确定性及参数不确定性,采用H_∞控制理论设计外回路鲁棒控制器,实现了标准轨迹的精确跟踪,同时给出了闭环系统的鲁棒稳定性证明。仿真结果验证了该方法的有效性。     

基于鲁棒模型预测的智能汽车轨迹跟踪控制研究

针对传统的基于跟踪误差模型轨迹跟踪控制器在复杂行驶环境下控制精度不高,鲁棒性差等问题,设计一种鲁棒模型预测轨迹跟踪控制策略。采用车辆凸多胞体动力学模型显式描述车辆动态特性,结合轨迹跟踪多目标约束设计鲁棒性目标函数,通过线性矩阵不等式优化方式求解状态反馈控制律;引入前馈控制消除稳态误差,提高跟踪精度。结果表明:在不同行驶工况下,该控制器在保证车辆跟踪精度基础上可有效提高行驶稳定性,具有较强的鲁棒性。     

多变量非线性系统的直接自适应模糊预测控制

对一类多变量非线性系统提出了直接自适应模糊预测控制方法,此方法首先对被控对象提出了线性时变子模型加非线性子模型的预测模型,然后直接利用模糊系统设计预测控制器,并基于时变增益自适应律对控制器中的未知向量和逼近误差估计值进行自适应调整。证明了此方法可使跟踪误差收敛到原点的一个邻域内,仿真结果验证了此方法的有效性。     

Output Tracking for One-Dimensional Wave Equation with Non-Collocated Control and Output Configuration

This paper considers output tracking for a one-dimensional wave equation with general disturbance which includes both internal nonlinear uncertainty and external disturbance. The performance output is non-collocated to the control. The disturbance is estimated by an essentially extended state observer from active disturbance rejection control and the difficulty caused by the non-collocated configuration of control and output is overcome by a proper trajectory planning. An output feedback law is proposed to make the tracking error be convergent to zero exponentially as time goes to infinity.At the same time, all states of the closed-loop system are shown to be uniformly bounded. Numerical simulation is also presented to validate the theoretical results.     

基于NDO的飞机轨迹跟踪抗干扰控制律设计

针对飞机纵向欠驱动耦合动力学模型设计鲁棒轨迹跟踪滑模控制律。首先,通过引入虚拟状态变量进行状态变换实现模型控制解耦。其次,考虑由系统建模误差和大气干扰组成的复合不确定性,设计非线性干扰观测器(nonlinear disturbance observer, NDO)进行观测补偿。然后,建立飞机极短距起降中攻角变化轨迹曲线,设计滑模控制律实现对虚拟状态变量和攻角轨迹指令的稳定跟踪。仿真结果表明,NDO可以实现对系统不确定性的精确观测和补偿,滑模控制律具有对系统建模误差和大气风切变的鲁棒性和抗干扰性。     

飞行器抗饱和鲁棒自适应非线性模型预测控制

针对巡航飞行器同时存在较大外部干扰和模型参数不确定性时自适应预测控制性能下降的问题,设计了带有模糊干扰观测器(fuzzy disturbance observer, FDO)补偿的鲁棒自适应非线性模型预测控制(robust adaptive nonlinear model predictive control, RANMPC)方法(简记为FDO-RANMPC方法)。首先,利用具有未知参数限制条件的递推最小二乘方法在线辨识模型参数;其次,利用模糊干扰观测器输出值抵消幅值较大的复合干扰,再利用Tube鲁棒预测控制策略设计了飞行器底层姿态系统具有稳定保障的FDO-RANMPC控制器;最后,在考虑复合不确定性情况下对指令姿态角跟踪的仿真中验证了控制器的有效性及其渐进稳定性。     

基于零化视线角速率的非线性预测制导律

利用非线性预测控制理论设计了一种零化视线角速率的预测制导律. 首先, 以弹目视线角速率为反馈项, 最小化预测误差为性能指标, 基于非线性预测控制理论和最优化理论推导出非线性预测制导律, 并对闭环回路的稳定性进行了证明. 其次, 针对制导律中含有的目标机动项信息, 设计了一种基于时间延迟控制理论的滤波算法, 并应用于预测制导律, 最后仿真考虑到导弹的延迟环节, 采用三阶自动驾驶仪模型, 验证了设计的制导律能够有效拦截机动目标, 与传统比例导引相比, 视线角速率变化平稳, 克服了末端视线角速率变化过快而导致过载饱和的情况, 降低了对执行机构的要求.     

Adaptive functional link network control of near-space vehicles with dynamical uncertainties

The control law design for a near-space hypersonic vehicle (NHV) is highly challenging due to its inherent nonlinearity, plant uncertainties and sensitivity to disturbances. This paper presents a novel functional link network (FLN) control method for an NHV with dynamical thrust and parameter uncertainties. The approach devises a new partially-feedback-functional-link-network (PFFLN) adaptive law and combines it with the nonlinear generalized predictive control (NGPC) algorithm. The PFFLN is employed for approximating uncertainties in flight. Its weights are online tuned based on Lyapunov stability theorem for the first time. The learning process does not need any offline training phase. Additionally, a robust controller with an adaptive gain is designed to offset the approximation error. Finally, simulation results show a satisfactory performance for the NHV attitude tracking, and also illustrate the controller's robustness.     

不完全驱动船舶航迹控制输入输出线性化设计

针对船舶航迹保持控制系统模型中存在的非线性 ,建立了不完全驱动水面船舶直线航迹控制系统的非线性数学模型 ;基于输入输出线性化技术 ,采用重定义输出变量思想 ,提出了一种状态反馈控制律。该控制律克服了转首角速度不能为零及重定义输出变量中组成元素的收敛性不能保证的局限 ,使得偏航船舶能够渐近镇定于直线参考航迹 ,并以实习船为例 ,利用MatlabSimulink工具箱进行了计算机仿真研究 ,并对所提出的控制器进行了验证。结果表明 ,所提出的控制器具有比较理想的控制效果和良好的瞬态性能。     

具有不可微输入信号的改进型重复变结构控制

针对一类具有结构不确定性和周期性外部扰动的非线性系统,提出了一种改进型重复变结构控制（modified repetitive variable structure control, MRVSC）算法。在传统积分滑模面的基础上构造了改进型积分滑模面（modified integral sliding mode surface, MISMS）。基于MISMS,采用Lyapunov方法设计的MRVSC算法保证了非线性系统的运动轨迹在有限时间内到达MISMS并保持在MISMS上,并且使得滑模动力学系统变为重复控制系统。根据重复控制系统的稳定性条件及灵敏度函数选择MISMS的参数。仿真结果显示,与传统积分滑模控制算法进行比较,MRVSC算法使得非线性系统具有更好的跟踪性能。     

基于模糊辨识的混合鲁棒自适应控制

针对一类多输入多输出不确定非线性系统,提出一种基于模糊辨识的混合鲁棒自适应控制方法。该方法探讨了自适应模糊控制器的参数自适应律由跟踪误差和逼近误差共同进行调节,并从理论分析和仿真角度证明了该方法比参数自适应律仅用跟踪误差进行调节的控制器具有更好的跟踪效果,该方法加快了系统跟踪误差的收敛速度。将该算法用于两连杆机械手轨迹跟踪,仿真结果表明该算法具有跟踪精度高,收敛速度快的优点。     

基于能量最优的无人驾驶汽车路径跟踪控制

动力总成控制对无人驾驶汽车的动态性能和经济性起着重要的作用。为了提高车辆在路径跟踪过程中的动力性和经济性,提出了一种基于能量最优化的路径跟踪控制策略。控制策略分为两部分,在上层控制器中使用非线性模型预测控制来计算所需要的动力参数和前轮转角。下层控制器采用基于电机能耗数值最优的方法进行设计。该方法可以确保电机一直运行在效率最优状态,并可根据电机状态动态调节无级变速器以满足车辆动力需求。仿真结果表明,控制方案具有良好的跟踪性能和节能潜力。     

Constrained predictive control of nonlinear stochastic systems

The receding horizon control (RHC) problem is considered for nonlinear Markov jump systems which can be represented by Takagi-Sugeno fuzzy models subject to constraints both on control inputs and on observe outputs. In the given receding horizon, for each mode sequence of the T-S modeled nonlinear system with Markov jump parameter, the cost function is optimized by constraints on state trajectories, so that the optimization control input sequences are obtained in order to make the state into a terminal invariant set. Out of the receding horizon, the stability is guaranteed by searching a state feedback control law. Based on such stability analysis, a linear matrix inequality approach for designing receding horizon predictive controller for nonlinear systems subject to constraints both on the inputs and on the outputs is developed. The simulation shows the validity of this method.         

具有性能预设的多机编队目标跟踪控制

针对无人机编队目标跟踪中性能不可控的问题,提出了一种具有性能预设的分布式多机编队目标跟踪控制方法.首先提出一种基于运动参数组的编队队形描述与目标跟踪方法,实现了编队的相位预设与队形控制;其次利用误差变换方法将有性能约束的误差问题转换为无约束误差控制问题,并给出了一致性预设性能控制律;然后分别设计了指数型和预设时间型性能...     

高精度陀螺稳定跟踪系统神经网络预测控制

针对高精度陀螺稳定跟踪系统，提出了一种基于小波基函数神经网络的非线性系统的一步超前预测控制算法。该方法利用小波网络学习非线性系统，利用小波神经网络模型作为系统的预测模型，控制信号直接通过极小化期望输出值与预测输出值之间的偏差来获得。通过对陀螺稳定跟踪控制系统的仿真，表明该算法具有优良的控制品质。     

Tracking controller for robot manipulators via composite nonlinear feedback law

A composite nonlinear feedback tracking controller for motion control of robot manipulators is de-scribed. The structure of the controller is composed of a composite nonlinear feedback law plus full robot nonlinear dynamics compensation. The stability is carried out in the presence of friction. The controller takes advantage of varying damping ratios induced by the composite nonlinear feedback control, so the transient performance of the closed-loop is remarkably improved. Simulation results demonstrate the feasibility of the proposed method.