离散线性时滞系统的次优控制:逐次逼近法

A successive approximation approach for designing optimal controllers is presented for discrete linear time-delay systems with a quadratic performance index. By using the successive approximation approach, the original optimal control problem is transformed into a sequence of nonhomogeneous linear two-point boundary value (TPBV) problems without time-delay and time-advance terms. The optimal control law obtained consists of an accurate feedback terms and a time-delay compensation term which is the limit of the solution sequence of the adjoint equations. By using a finite-step iteration of the time-delay compensation term of the optimal solution sequence, a suboptimal control law is obtained. Simulation examples are employed to test the validity of the proposed approach.     

一种新的非线性离散时间系统迭代学习控制的前馈－反馈机制

This paper presents a new feedback-feedforward configuration for the iterative learning control (ILC) design withfeedback, which consists of a feedback and a feedforward component. The feedback integral controller stabilizes the system,and takes the dominant role during the operation, and the feed-forward ILC compensates for the repeatable nonlinear/unknowntime-varying dynamics and disturbances, thereby enhancing the performance achieved by feedback control alone. As the mostfavorable point of this control strategy, the feedforward ILC and the feedback control can work either independently or jointlywithout making efforts to recongurate or retune the feedforward/feedback gains. With rigorous analysis, the proposedlearning control scheme guarantees the asymptotic convergences along the iteration axis.     

一类前馈系统的鲁棒镇定

Two kinds of saturated controllers are designed for a class of feedforward systems and the closed-loop resulted is locally input-to-state stable and input-to-state stable, respectively. By the word "locally", it is meant that there are restrictions on the amplitude of inputs. At first, under the guidance of suitable energy functions, two kinds of saturated controllers are designed as locally input-to-state stabilizers for a class of perturbed linear systems, from which explicit gain estimations can be obtained for the subsequent design. Then under the conditions that two subsystems of the feedforward system are respectively of locally input-to-state stability and input-to-state stability, the small gain theory is used to determine saturated degrees for corresponding robust stabilizers. The stability proofs are given by using a new characterization of input-to-state stability that is based on the concept of ultimate boundedness. As an application, saturated controllers are designed for the partial dynamics of a certain inverted pendulum.     

一类非线性时滞系统的状态反馈镇定

The problem of global stabilization by state feedback for a class of time-delay nonlinear system is considered. By constructing the appropriate Lyapunov-Krasovskii functionals (LKF) and using the backstepping design, a linear state feedback controller making the closed-loop system globally asymptotically stable is constructed.     

时变机器人系统的重复学习控制: 一种混合学习方案

Repetitive learning control is presented for finite-time-trajectory tracking of uncertain time-varying robotic systems. A hybrid learning scheme is given to cope with the constant and time-varying unknowns in system dynamics, where the time functions are learned in an iterative learning way, without the aid of Taylor expression, while the conventional differential learning method is suggested for estimating the constant ones. It is distinct that the presented repetitive learning control avoids the requirement for initial repositioning at the beginning of each cycle, and the time-varying unknowns are not necessary to be periodic. It is shown that with the adoption of hybrid learning, the boundedness of state variables of the closed-loop system is guaranteed and the tracking error is ensured to converge to zero as iteration increases. The effectiveness of the proposed scheme is demonstrated through numerical simulation.     

非线性系统的间接自适应模糊输出反馈监督控制

In this paper, an indirect adaptive fuzzy output feedback controller with supervisory mode for a class of unknown nonlinear systems is developed. The proposed approach does not need the availability of the state variables, moreover, a supervisory controller is appended to the adaptive fuzzy controller to force the state to be within the constraint set. Therefore, if the adaptive fuzzy controller cannot maintain the stability, the supervisory controller starts to work to guarantee stability. On the other hand, if the adaptive fuzzy controller works well, the supervisory controller will be deactivated. The overall adaptive fuzzy control scheme guarantees the stability of the whole closed-loop systems. The simulation results confirm the effectiveness of the proposed method.     

虚拟控制增益函数未知的随机非线性系统模糊自适应控制

The problem of track control is studied for a class of strict-feedback stochastic nonlinear systems in which unknown virtual control gain function is the main feature. First, the so-called stochastic LaSalle theory is extended to some extent, and accordingly, the results of global ultimate boundedness for stochastic nonlinear systems are developed. Next, a new design scheme of fuzzy adaptive control is proposed. The advantage of it is that it does not require priori knowledge of virtual control gain function sign, which is usually demanded in many designs. At the same time, the track performance of closed-loop systems is improved by adaptive modifying the estimated error upper bound. By theoretical analysis, the signals of closed-loop systems are globally ultimately bounded in probability and the track error converges to a small residual set around the origin in 4th-power expectation.     

非线性互联大系统的最优控制:逐次逼近法

The optimal control problem for nonlinear interconnected large-scale dynamic systems is considered. A successive approximation approach for designing the optimal controller is proposed with respect to quadratic performance indexes. By using the approach, the high order, coupling, nonlinear two-point boundary value (TPBV) problem is transformed into a sequence of linear decoupling TPBV problems. It is proven that the TPBV problem sequence uniformly converges to the optimal control for nonlinear interconnected large-scale systems. A suboptimal control law is obtained by using a finite iterative result of the optimal control sequence.     

离散时间扰动脉冲切换系统鲁棒指数稳定性

The robust exponential stability of a class of discrete time impulsive switched systems with structure perturbations is studied. Based on the average dwell time concept and by dividing the total activation time into the time with stable subsystems and the time with unstable subsystems, it is shown that if the average dwell time and the activation time ratio are properly large, the given switched system is robustly exponentially stable with a desired stability degree. Compared with the traditional Lyapunov methods, our layout is more clear and easy to carry out. Simulation results validate the correctness and effectiveness of the proposed algorithm.     

同时镇定一族带有不确定参数的多输入非线性系统

Simultaneous stabilization for a collection of multi-input nonlinear systems with uncertain parameters is dealt with in this paper. A systematic method for obtaining a control Lyapunov function (CLF) is presented by solving the Lyapunov equation. A sufficient condition that a quadratic CLF is a common CLF for these systems is acquired. A continuous state feedback is designed to simultaneously stabilize these systems. Finally, the effectiveness of the proposed scheme is illustrated by a simulation example.     

大系统的分布式控制

本文根据分布式计算机系统的几种典型结构的特点,定义了几种新的大系统分布式控制信息结构.分布式控制规律用于分布式计算机控制系统时,既可提高系统的综合性能及整体最优性,又使各子系统间的通信次数很少,具有广阔的应用前景.     

随机大系统利用变结构控制的分散镇定*

本文研究了随机大系统的变结构控制问题。并证明了所构造的滑动流形的可达性和均方渐近稳定性。     

二能级量子系统的构造控制稳定性研究

由于量子态在Hilbert空间中的酉演化性质,经典稳定性概念在量子动力学中几乎没有意义。利用两个量子态保真度衰减的线性响应近似形式,提出一种分析量子系统构造控制稳定性的方法。对二能级量子构造控制系统在静态干扰下的保真度摄动分析表明,当有较多控制脉冲的径向坐标等于π/2时,控制系统取得较大的稳定性。两种不同的构造控制酉分解方法的数值仿真结果证明了理论分析的正确性。该分析方法有助于设计高稳定性的量子控制系统。     

大系统的动态递阶伺服控制

本文针对大系统的伺服控制问题,提出了动态递阶伺服控制这一新的伺服控制方案,给出了动态递阶伺服控制器的结构及动态递阶伺服控制问题可解的条件。研究结果表明,这种伺服控制方案可用来解决有不稳定分散固定模的大系统的伺服控制问题。     

线性大系统递阶控制的一种新型逼近方法

将文[1]提出的按段多重契比雪夫多项式系(PMCP)应用于线性大系统递阶控制算法的逼近计算,将动态递阶控制转化为静态递阶优化,获得了一种新型逼近算法.仿真结果表明了该算法的有效性.     

线性滞后互联大系统的分散智能镇定

讨论了线性滞后互联大系统的分散镇定问题,给出了分散镇定控制器设计的思想和方法,而后将人工神经网络技术引入该研究领域,给出了一般线性定常系统闭环极点配置的智能方法,同时实现了线性滞后互联大系统分散镇定控制器的智能设计.最后给出了一数值仿真例子,进而验证了该设计方法的可行性及有效性.     

大规模不确定离散动态系统的分散控制

本文讨论一类大规模不确定离散动态系统的稳定控制问题.利用Lyapunov方法,推出分散鲁棒反馈控制器的存在条件,并导出分散鲁棒反馈控制策略.     

非线性大系统的分散镇定

本文研究具有强耦合互联非线性系统的反馈镇定问题，给出了能用几乎光滑反馈镇定的Ｌｙａｐｕｎｏｖ条件和新的几乎光滑反馈律。     

线性多级动态结构大系统的反馈镇定

本文研究一类由Ｎ个子系统组成的具有多级动态结构线性大系统的多级反馈镇定问题，这类系统的多级反馈可镇定性与相应地导出系统分散反馈可镇定性等价。利用这种等价性以及系统本身的结构特征，给出了这类大系统可多级反馈镇定的充分条件。对于给定系统，应用本文的结论判别其多级反馈可镇定性是比较容易的。