不确定性系统的自适应鲁棒跟踪控制

针对存在未知干扰和未建模动态等不确定性的系统的自适应鲁棒跟踪控制问题进行了 探讨.首选将l1优化控制器的有限拍设计方法结合给出了最优鲁棒稳态跟踪控制器的设计方法． 然后利用集员辨识的思想,将名义模型的参数和未建模动态及干扰的大小作为未知参数,提出了 一种递推参数估计方法.最后将上述研究结果结合起来提出了一种自适应鲁棒跟踪控制策略,证 明了自适应算法的全局收敛性并给出了鲁棒跟踪性能指标的一下较紧的上界.与现有的结果相 比,本文提出的自适应控制具有非保守的鲁棒稳定性,具有渐近最优的鲁棒跟踪性能.     

基于l_∞范数和l_1范数最小化的二自由度最优鲁棒跟踪控制

研究了具有乘摄动模型不确定性并存在未知干扰系统的最优鲁棒跟踪控制问题 .采用二自由度控制器结构Youla参数化方法将最优鲁棒跟踪控制问题转化为两个相互独立的优化问题 :跟踪问题和鲁棒设计问题 .跟踪问题以l∞ 范数为性能指标通过极小化跟踪误差的最大幅值实现最优跟踪控制 ;鲁棒性设计问题中 ,将模型不确定性视为一种外界干扰 ,通过极小化干扰到误差的灵敏度函数的l1范数使得干扰对跟踪误差的影响最小 .通过截断处理 ,上述两种优化问题均可化为标准线性规划问题 .给出了截断阶数与逼近误差之间的关系 .仿真结果表明新方法的有效性 .     

互质因子摄动下的最优鲁棒稳态跟踪控制器设计

研究了存在未知外部干扰时的互质因子摄动系统的鲁棒稳态追踪问题.利用Youla参数化方法，提出了一个最坏情况稳态绝对误差的精确计算公式.该公式使得最优稳态跟踪控制器设计问题等价于保证系统鲁棒稳定时e1的最优鲁棒控制器设计问题.     

硬盘驱动器准滑模自适应鲁棒控制方法

提出一种硬盘驱动器鲁棒自适应准滑模控制方法, 该方法在仿真和实验中有效地克服了跟踪扰动信号的影响, 极大地提高了硬盘驱动器的跟踪速度, 使系统稳态、动态性能和鲁棒性都得到很大的改善.     

基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统设计

为了保证机器人能够在保持稳定的情况下,按照规划轨迹执行工作任务,从硬件和软件两个方面,设计了基于Sigmoid函数的机器人鲁棒滑模跟踪控制系统。装设机器人传感器与状态观测器,改装机器人鲁棒滑模跟踪控制器,完成系统硬件设计;综合机器人结构、运动机理和动力机制3个方面,构建机器人数学模型;根据状态数据采集结果与规划轨迹之间的偏差,计算机器人跟踪控制量;依据滑模运动与切换方程,利用Sigmoid函数生成机器人鲁棒滑模控制律,将生成控制指令作用在机器人执行元件上,实现系统的鲁棒滑模跟踪控制功能;在系统测试与分析中,所设计控制系统的平均位置跟踪控制误差为0.93 mm,与设定轨迹目标基本重合,机器人姿态角跟踪控制误差为0.06 mm,具有较好的鲁棒滑模跟踪控制效果,能够有效提高机器人鲁棒滑模跟踪控制精度。     

基于单网络评判学习的非线性系统鲁棒跟踪控制

针对一类具有不确定性的连续时间非线性系统,提出一种基于单网络评判学习的鲁棒跟踪控制方法.首先建立由跟踪误差与参考轨迹构成的增广系统,将鲁棒跟踪控制问题转换为镇定设计问题.通过采用带有折扣因子和特殊效用项的代价函数,将鲁棒镇定问题转换为最优控制问题.然后,通过构建评判神经网络对最优代价函数进行估计,进而得到最优跟踪控制算法.为了放松该算法的初始容许控制条件,在评判神经网络权值更新律中增加一个额外项.利用Lyapunov方法证明闭环系统的稳定性及鲁棒跟踪性能.最后,通过仿真结果验证该方法的有效性和适用性.     

基于神经网络的模型跟随鲁棒自适应控制

针对一类复杂非线性动力学系统,提出一种基于神经网络动态补偿的模型跟随非线 性鲁棒自适应控制策略.采用神经网络在线补偿控制器以克服系统的未建模动力学和非线性 耦合因素的影响,从而提高了模型跟随控制的动态性能和稳态精度;当系统存在模型不确定 性和外部扰动时,其输出仍能精确地跟踪期望参考模型的输出.同时给出了闭环误差系统鲁 棒稳定性的证明.应用示例表明,所提方法可保证闭环系统具有良好的跟踪性能和鲁棒性,且 算法简单,易于在线控制.     

不确定Markov 跳跃线性系统的鲁棒跟踪与模型跟随

讨论一类带wiener过程的不确定Markov跳跃线性系统的鲁棒跟踪和模型跟随问题．通过构造一组非线性鲁棒状态反馈跟踪控制器来跟踪给定的动态信号，该控制器确保系统当时间趋于无穷时是以扰动衰减系数鲁棒随机稳定的，且跟踪误差有界．最后给出了算例，说明所设计的鲁棒跟踪控制器具有较好的跟踪性能．     

不确定性线性系统的鲁棒渐近跟踪控制

对于线性不确定系统，本文给出了一种鲁棒渐近跟踪控制的设计方法，通过选取矩阵φ，构造广义匹配条件，利用Riccati方程正解给出了设计鲁棒渐近跟踪有效方法，对于匹配系统和不匹配系统均可使输出渐近跟踪某一参考输入，算例表明了该方法的有效性。     

运用区间算法的约束非线性系统鲁棒模型预测控制

针对一类具有输入和状态约束的干扰有界非线性系统,提出了基于区间分析的约束非线性鲁棒模型预测控制,以降低计算量并扩大系统吸引域.首先,在集合运算的基础上,利用区间运算和函数区间扩展,给出了一种计算效能更好、保守性更低的非线性系统鲁棒一步集计算方法;其次,构造重叠的多面体控制不变集序列并以此计算约束非线性系统的鲁棒多步集,并通过设计基于集合的在线优化策略,提出了基于鲁棒一步集的单步优化非线性模型预测控制,有效降低了非线性优化的在线计算量;最后,仿真实例验证了算法的有效性.     

An optimal control approach to robust tracking of linear systems

In our early work, we show that one way to solve a robust control problem of an uncertain system is to translate the robust control problem into an optimal control problem. If the system is linear, then the optimal control problem becomes a linear quadratic regulator (LQR) problem, which can be solved by solving an algebraic Riccati equation. In this article, we extend the optimal control approach to robust tracking of linear systems. We assume that the control objective is not simply to drive the state to zero but rather to track a non-zero reference signal. We assume that the reference signal to be tracked is a polynomial function of time. We first investigated the tracking problem under the conditions that all state variables are available for feedback and show that the robust tracking problem can be solved by solving an algebraic Riccati equation. Because the state feedback is not always available in practice, we also investigated the output feedback. We show that if we place the poles of the observer sufficiently left of the imaginary axis, the robust tracking problem can be solved. As in the case of the state feedback, the observer and feedback can be obtained by solving two algebraic Riccati equations.     

基于线性矩阵不等式的分散鲁棒跟踪控制器设计

应用线性矩阵不等式（ＬＭＩ）方法研究不确定性关联大系统的分散鲁棒输出跟踪控制问题。系统中不确定项具有数值界,可不满足匹配条件。基于不确定基项的表达形式,给出了存在分散控制鲁棒跟踪控制器的ＬＭＩ条件。在此基础上,通过建立求解受ＬＭＩｓ约束的凸优化问题,提出了具有较小反馈增益ＬＭＩ设计方法,使受控系统渐近跟踪给定的参考输入。ＬＭＩ方法求解简单,最后用示例说明了该方法的应用。     

Approximate causal output tracking for linear perturbed systems via sliding mode control

ABSTRACT

A new approach to the solution of what is termed causal output tracking problem for linear time-invariant systems in the presence of both matched and unmatched unmodelled disturbances is presented. The proposed solution is addressed through the design of a dynamic steady state estimator based on the desired system structure and an observer, considering the reference as the system output. The unmatched disturbance is estimated and used in the steady state estimator to achieve invariance, while the matched disturbance robustness is provided via sliding mode control using the super-twisting algorithm. A useful application of the presented techniques is output tracking for non-minimum phase systems; thus, the performed simulation results confirm the effectiveness of the proposed control scheme for this kind of systems.     

不确定性时滞大系统的分散鲁棒跟踪控制器设计

研究不确定性关联时滞大系统的分散鲁棒输出跟踪控制问题,系统中不确定项具有数值界,可满足匹配条件,基于不确定项的表达形式,给出了存在分散分散鲁棒跟踪控制器的线性矩阵不等式（LMI）条件,在此基础上,通过建立求解受LMIs约束的凸优化问题,提出了具有较小反馈增益LMI设计方法,使受控系统渐近跟踪给定的参考输入,LMI方法求解简单,便于计算。     

Adaptive control with optimal tracking performance

This paper provides a way to optimise the steady-state tracking performance of the adaptive control system in the presence of unknown external disturbances. A-priori knowledge of the dynamic model of the reference signal to be tracked is not completely known. Especially, the updatable non-empty admissible model set, which is consistent to the a-priori knowledge of the plant parameter and the online measurements, is computed. Treating the overall system performance as the criteria, the nominal model is optimally chosen within the admissible model set. The optimal nominal model is subsequently used to synthesise the optimal closed-loop controller that minimises the steady-state absolute value of the tracking error. Combining the above two aspects, an optimal adaptive control scheme is proposed. Because of the consistency of the identification criteria and control object, the adaptive control scheme proposed in this paper can achieve the overall optimal steady-state tracking performance, and the effect of the interplay between the identification and control of the adaptive system can be handled effectively. In addition, the computable optimal performance is also provided.     

Quadratic robust tracking control — A Polynomial Matrix Approach

A quadratic robust tracking problem is solved using a polynomial matrix approach. Because of the possibly unstable mode of the control sequence we propose a new quadratic cost function of error and control sequences to facilitate the optimization. The optimal controller makes the plant output track the reference sequence robustly and minimizes the proposed quadratic cost function. We also present the parametrized set of suboptimal controllers which yield finite costs so that there exists the central optimal controller in the set when the parameter is set to zero. The usefulness of our proposed cost function is demonstrated by simulation examples. Our design procedure has advantages over two other possible approaches: the LQ state-space approach and the Wiener–Hopf approach which may be tried to tackle the same problem. Our approach obviates the need to construct a dynamic observer compared to the state-space approach and it is computationally attractive compared to the Wiener–Hopf approach.     

Path following algorithm for skid-steering mobile robot based on adaptive discontinuous posture control

The kinematic model of a skid-steering mobile robot (SSMR) is manipulated using signed polar transformation which represents a discontinuous state transformation. The influence of relative position between the instantaneous center of rotation (ICR) and SSMR center of mass is considered. Then, adaptive state feedback controller is designed and stability regions are studied. Subsequently, a point-to-point tracking algorithm is introduced to track a trajectory that is defined by a set of way-points, which is the more realistic case of dangerous exploration or landmine detection purposes. The closed-loop system is simulated using MATLAB environment and experimentally validated using a modified TURTLEBOT3 Burger. Results show that the proposed controller reaches almost zero steady state error with smooth paths for point stabilization, moreover, good tracking capabilities are demonstrated. The proposed control system integrates both posture and tracking algorithm, thus achieve trajectory tacking which is defined by a set of way-points.     

时滞大系统分散鲁棒跟踪控制器设计: LMI 方法

针对一类满足匹配条件的不确定性关联时滞系统,导出了分散鲁棒输出跟踪控制器存在的充分条件。基于不确定项的表达形式,给出了存在分散鲁棒跟踪控制器的线性矩阵不等式（LMI）条件。通过建立求解受LMIs约束的凸优化问题,提出了具有较小反馈增益LMI设计方法,使受控系统渐近跟踪给定的参考输入。仿真示例说明了该方法的应用。     

微手系统的鲁棒无源跟踪控制

近年来, 微手系统作为机器人技术的一个热门研究领域, 受到了越来越多的关注. 由于微手系统是复杂且具有非线性的, 因此在实际应用当中很难达到精确跟踪的性能. 为了解决微手系统的精准控制问题, 本文讨论了微手系统的鲁棒无源跟踪控制. 首先, 运用基于演算子理论的鲁棒右互质分解方法, 建立了微手系统的动态模型. 然后, 通过结合无源补偿算子, 设计了无源鲁棒控制器, 保证了系统的鲁棒稳定性和无源性. 进而提出了基于双Bezout恒等式的鲁棒跟踪控制方案, 使整个非线性系统具有较强的鲁棒性和良好的跟踪性能. 最后, 通过仿真进一步验证了所提出方法的有效性