一类非线性系统的次优控制研究

考虑一类关系度不确定且零动态稳定的非线性系统的控制器设计问题．利用预测控制概念,通过选用较为全面的二次型性能指标,对输出进行高阶泰勒级数展开,推导出一种非切换的解析次优控制律,进而得出了在该控制律下闭环系统局部稳定的充分条件．仿真例子验证了该控制算法具有较好的动态性能,与已有的近似线性化方法相比,显示了该控制策略的优越性．     

智能车辆路径跟踪控制方法

为了提高智能车辆路径跟踪控制器的可靠性和控制精度,提出一种基于误差动力学模型的路径跟踪控制方法.基于车辆运动学模型和动力学模型建立系统误差动力学模型,并在此基础上推导出车辆路径跟踪控制的稳态控制律,利用李雅普诺夫稳定性理论验证稳态控制律的正确性.为了减小外部干扰对控制性能的影响,提高控制器的可靠性,进一步设计基于车辆侧向位移误差的瞬态控制律,并利用李雅普诺夫稳定性理论验证闭环系统的稳定性.稳态控制律和瞬态控制律构成了非线性的路径跟踪控制器.通过与车辆路径跟踪常用的线性控制器和非线性控制器对比验证所提出控制方法的有效性,线性控制器选用LQR控制器,非线性控制器选用Stanley控制器.仿真结果表明,与LQR控制器相比,所提出控制方法的路径跟踪控制精度、抗干扰性和可靠性更好.与Stanley控制器相比,所提出控制方法具有更好的路径跟踪控制精度和控制收敛速度,且在大曲率路径跟踪过程中具有更好的可靠性.     

On a switching control scheme for nonlinear systems with ill-defined relative degree

This paper discusses the applicability of a switching control scheme for a nonlinear system with ill-defined relative degree. The control scheme switches between exact and approximate input–output linearisation control laws. Unlike a linear system under a switching control scheme, the equilibria of a nonlinear system may change with the switching. It is pointed out that this is not sufficient to cause instability. When the region of the approximate linearisation control law is attractive to the exact zero dynamics, it is possible that the closed-loop system under the switching control scheme is still stable. The results in this paper shows that the switching control scheme proposed in Tomlin and Sastry (Systems Control Lett. 35(3) (1998) 145) is applicable for a wider class of nonlinear systems.     

一类非线性系统非切换解析模型预测控制方法研究

针对关系度不确定非线性系统, 基于模型预测控制理论和切换解析非线性模型预测控制(Nonlinear model predictive control, NMPC) 提出了一种非切换的解析NMPC新方法. 论证了在非切换解析NMPC控制律下, 通过坐标变换可以将闭环系统分别在关系度确定和不确定的两个子空间近似为线性系统, 得出非切换解析NMPC使闭环系统稳定的必要条件. 通过仿真实验验证了非切换解析NMPC可以达到很好的响应特性, 无需切换的特征也扩大了其应用范围.     

基于滑模自抗扰的智能车路径跟踪控制

针对传统的基于精确数学模型的路径跟踪控制方法很难适应复杂多变驾驶环境的问题,提出一种基于终端滑模控制与自抗扰控制的路径跟踪控制方法.首先,通过构造一个期望偏航角函数能够满足当车辆的实际偏航角趋近于该期望偏航角时其侧向位移偏差趋近于零,从而简化路径跟踪控制;然后,采用扩张状态观测器实时估计系统的未建模动态,同时采用非奇异终端滑模来设计非线性误差反馈律,从而实现偏航角快速、准确地跟踪控制.仿真结果表明,所设计的控制器能够保证车辆稳定行驶的同时快速、精确地跟踪期望的路径.     

一类非线性系统的加速度规划输出跟踪动态控制

针对一类严格反馈形式的非线性二阶多输入多输出系统,提出一种带有加速度规划的输出跟踪动态控制策略.引入一个代替时间变量的路径参数用以规划路径跟踪时的加速度,回避了设计内环加速度控制回路的常规方法,简化了控制器的设计过程.对二阶系统的控制项求导进行系统扩维,基于新的增广系统,设计了使系统输出收敛于期望路径的反馈线性化动态控制律.再对加速度跟踪误差基于梯度法设计更新律使其渐近收敛于零,最后通过调节期望加速度实现定常速度控制.理论分析表明,误差闭环系统一致渐近稳定,速度误差有界.动力定位船舶循迹控制仿真结果表明了所提出控制器的有效性.     

A novel neural approximate inverse control for unknown nonlinear discrete dynamical systems.

A novel neural approximate inverse control is proposed for general unknown single-input-single-output (SISO) and multi-input-multi-output (MIMO) nonlinear discrete dynamical systems. Based on an innovative input/output (I/O) approximation of neural network nonlinear models, the neural inverse control law can be derived directly and its implementation for an unknown process is straightforward. Only a general identification technique is involved in both model development and control design without extra training (online or offline) for the neural nonlinear inverse controller. With less approximation made on controller development, the control will be more robust to large variations in the operating region. The robustness of the stability and the performance of a closed-loop system can be rigorously established even if the nonlinear plant is of not well defined relative degree. Extensive simulations demonstrate the performance of the proposed neural inverse control.     

Direct adaptive control of partially known nonlinear systems.

A direct adaptive control strategy for a class of single-input/single-output nonlinear systems is presented. The major advantage of the proposed method is that a detailed dynamic nonlinear model is not required for controller design. The only information required about the plant is measurements of the state variables, the relative degree, and the sign of a Lie derivative which appears in the associated input-output linearizing control law. Unknown controller functions are approximated using locally supported radial basis functions that are introduced only in regions of the state space where the closed-loop system actually evolves. Lyapunov stability analysis is used to derive parameter update laws which ensure (under certain assumptions) the state vector remains bounded and the plant output asymptotically tracks the output of a linear reference model. The technique is successfully applied to a nonlinear biochemical reactor model.     

Robust fuzzy 3D path following for autonomous underwater vehicle subject to uncertainties

This paper addresses a three-dimensional (3D) path following control problem for underactuated autonomous underwater vehicle (AUV) subject to both internal and external uncertainties. A two-layered framework synthesizing the 3D guidance law and heuristic fuzzy control is proposed to achieve robust adaptive following along a predefined path. In the first layer, a 3D guidance controller for underactuated AUV is presented to guarantee the stability of path following in the kinematics stage. In the second layer, a heuristic adaptive fuzzy algorithm based on the guidance command and feedback linearization Proportional-Integral-Derivative (PID) controller is developed in the dynamics stage to account for the nonlinear dynamics and system uncertainties, including inaccuracy modelling parameters and time-varying environmental disturbances. Furthermore, the sensitivity analysis of the heuristic fuzzy controller is presented. Against most existing methods for 3D path following, the proposed robust fuzzy control scheme reduces the design and implementation costs of complicated dynamics controller, and relaxes the knowledge of the accuracy dynamics modelling and environmental disturbances. Finally, numerical simulation results validate the effectiveness of the proposed control framework and illustrate the outperformance of the proposed controller as well.     

任意相对阶下非线性切换系统的事件触发漏斗控制

针对一类具有任意相对阶且带有部分非输入到状态稳定逆动态的非线性切换系统, 提出一种动态事件触 发漏斗跟踪控制方案. 首先, 引入一个虚拟输出将任意相对阶的非线性切换系统转换为相对阶为一的非线性切换系 统. 其次, 设计各子系统的事件触发漏斗控制器和切换的动态事件触发机制, 解决候选事件触发漏斗控制器和子系 统之间的异步切换问题, 所提方案消除已有文献中为所有子系统设计共同控制器带来的保守性. 在一类具有平均驻 留时间切换信号的作用下, 保证切换闭环系统的所有信号都是有界的, 且跟踪误差一直在预设的漏斗内演化, 并排 除采样中的奇诺现象. 最后, 一个仿真例子验证方案的实用性和有效性.     

自治飞艇直接自适应模糊路径跟踪控制

针对具有模型不确定和未知外部干扰的自治飞艇, 提出了直接自适应模糊路径跟踪控制方法. 该方法由路径跟踪控制和自适应模糊控制两部分组成. 首先基于飞艇的平面运动模型设计路径跟踪控制律, 包括制导律计算、偏航角跟踪和速度控制3 部分; 然后构造直接自适应模糊控制器逼近路径跟踪控制律中的不确定项. 稳定性分析证明所设计的控制律能使飞艇跟踪给定的期望路径, 跟踪误差收敛到原点的小邻域内. 仿真结果验证了所提出方法的有效性.

     

Discrete-time optimal control for stochastic nonlinear polynomial systems

This paper presents a solution to the discrete-time optimal control problem for stochastic nonlinear polynomial systems over linear observations and a quadratic criterion. The solution is obtained in two steps: the optimal control algorithm is developed for nonlinear polynomial systems by considering complete information when generating a control law. Then, the state estimate equations for discrete-time stochastic nonlinear polynomial system over linear observations are employed. The closed-form solution is finally obtained substituting the state estimates into the obtained control law. The designed optimal control algorithm can be applied to both distributed and lumped systems. To show effectiveness of the proposed controller, an illustrative example is presented for a second degree polynomial system. The obtained results are compared to the optimal control for the linearized system.     

Adaptive actuator compensation control with feedback linearization

An adaptive inverse controller is developed for feedback linearizable nonlinear systems with nonsmooth actuator nonlinearities. The use of an actuator nonlinearity inverse and a feedback linearizing controller leads to an error equation suitable for deriving an adaptive update law for the inverse parameters. Closed-loop signal boundedness is proved analytically, and system performance improvement is shown by simulation results. Such adaptive control schemes are also developed for multivariable nonlinear systems with actuator nonlinearities. For nonlinear systems that do not possess a relative degree, dynamic extension is employed to realize adaptive inverse compensation designs for actuator nonlinearities. These adaptive designs ensure closed-loop stability in the presence of uncertain actuator nonlinearities     

Optimal two-degree-of-freedom fuzzy control for locomotion control of a hydraulically actuated hexapod robot

Locomotion control of legged robots is a very challenging task because very accurate foot trajectory tracking control is necessary for stable walking. An electro-hydraulically actuated walking robot has sufficient power to walk on rough terrain and carry a heavier payload. However, electro-hydraulic servo systems suffer from various shortcomings such as a high degree of nonlinearity, uncertainty due to changing hydraulic properties, delay due to oil flow and dead-zone of the proportional electromagnetic control valves. These shortcomings lead to inaccurate analytical system model, therefore, application of classical control techniques result into large tracking error. Fuzzy logic is capable of modeling mathematically complex or ill-defined systems. Therefore, fuzzy logic is becoming popular for synthesis of control systems for complex and nonlinear plants. In this investigation, a two-degree-of-freedom fuzzy controller, consisting of a one-step-ahead fuzzy prefilter in the feed-forward loop and a PI-like fuzzy controller in the feedback loop, has been proposed for foot trajectory tracking control of a hydraulically actuated hexapod robot. The fuzzy prefilter has been designed by a genetic algorithm (GA) based optimization. The prefilter overcomes the flattery delay caused by the hydraulic dead-zone of the electromagnetic proportional control valve and thus helps to achieve better tracking. The feedback fuzzy controller ensures the stability of the overall system in the face of model uncertainty associated with hydraulically actuated robotic mechanisms. Experimental results exhibit that the proposed controller manifests better foot trajectory tracking performance compared to single-degree-of-freedom (SDF) fuzzy controller or optimal classical controller like state feedback LQR controller.     

基于非线性干扰观测器的翼伞鲁棒反步跟踪控制

针对干扰条件下的无人翼伞飞行器路径跟踪控制问题,提出一种基于非线性干扰观测器的反馈增益鲁棒反步控制方法.采用二阶跟踪-微分器设计干扰观测器对系统复合干扰进行估计和补偿,设计了反馈增益反步跟踪控制律,通过合理设计增益参数,消除了部分复杂非线性项,避免了虚拟量高阶导数问题,简化了控制器形式.根据Lyapunov理论设计鲁棒反馈补偿项,在保证稳定性的同时提高了系统的鲁棒性.仿真实验结果验证了所提出方法的有效性.     

Event-triggered-based finite-time cooperative path following control for underactuated multiple marine surface vehicles

This paper develops an event-triggered-based finite-time cooperative path following (CPF) control scheme for underactuated marine surface vehicles (MSVs) with model parameter uncertainties and unknown ocean disturbances. First, a finite-time extended state observer (FTESO) is proposed, in which the FTESO can estimate the velocities and compound disturbances in finite time. Then, the finite-time LOS guidance law based on velocity estimation values is designed to obtain the desired surge velocity and the desired yaw rate. In order to realize the cooperative control of multiple paths in finite time, the cooperative control law for the path variable is designed. In addition, the relative threshold event-triggered control (ETC) mechanism is incorporated into the formation control algorithm, and an event-triggered-based finite-time CPF controller is designed, which not only effectively reduces the update frequency of controller and the mechanical loss of actuator but also improves the control performance of system. Furthermore, by using homogeneous method, Lyapunov theory, and finite-time stability theory, it is proved that under the proposed finite-time CPF control scheme, the formation errors can converge to a small neighborhood around origin in finite time. Finally, numerical simulation results illustrate the effectiveness of the proposed control scheme.     

励磁输入动态不确定的同步发电机鲁棒控制

非线性励磁控制如果没有考虑励磁输入存在的不确定性,可能影响其实际的控制效果。为了减小励磁输入动态不确定对发电机系统的影响,利用积分反推方法设计名义系统的虚控制,并加入非线性动态阻尼项对虚控制进行再设计,得到系统的鲁棒非线性控制率。控制率的设计未采用任何线性化方法,充分利用了系统的非线性特性。通过仿真试验,证实了该方法在输入动态不确定子系统满足最小相位、相对阶为零的条件下,可以保证发电机的功角、输出电压稳定。     

基于模糊混合控制的自治水下机器人路径跟踪控制

基于模糊混合控制策略,本文提出了一种用于非线性欠驱动自治水下机器人的鲁棒路径跟踪控制方法.利用Sugeno型模糊推理系统,将PD滑模控制器与非奇异终端滑模控制器光滑连接,构造了模糊混合控制器.它能充分融合这两类控制器的优势,无论系统远离平衡点还是在其附近,都能取得快速收敛的效果.如果,借助于非时间参考量,将该混合控制器用于自治水下机器人路径跟踪控制,将有利于提高它在不确定环境中的跟踪能力.最后,通过仿真计算结果验证了该控制策略的有效性.     

可反馈线性化系统的鲁棒自适应容错控制设计

针对存在不确定执行器故障和未知不匹配干扰的可反馈线性化非线性系统, 提出一种鲁棒自适应容错控 制策略. 首先分别给出系统输入和扰动关于系统输出的相对阶, 针对两种相对阶之间的不同关系设计鲁棒控制器, 抑制干扰对系统输出的影响; 然后针对各故障情况分别设计容错控制器; 最后将各控制器进行融合得到一个综合 故障补偿控制器, 从而有效解决故障模式、类型、大小、时间和外界干扰等多重不确定性, 保证闭环系统稳定和渐近 输出跟踪性能. 仿真结果验证了所设计控制方案的可行性与有效性.     

Nonlinear sliding mode control of an unmanned agricultural tractor in the presence of sliding and control saturation

The paper considers the problem of automatic path tracking by autonomous farming vehicles subject to wheel slips, which are characteristic for agricultural applications. Two guidance laws are proposed to solve this problem, and both explicitly take into account the constraints on the steering angle and ensure tracking an arbitrarily curved path. The first law is implemented by the pure sliding-mode controller, whereas the second one combines the sliding mode approach with a smooth nonlinear control law and requests control chattering at the reduced amplitude as compared with the first law. Mathematically rigorous proofs of global convergence and robust stability of the proposed guidance laws are presented. In doing so, the slipping effects are treated as bounded uncertainties. Simulation results and real world experiments confirm the applicability and performance of the proposed guidance approach.