Nonlinear system compound inverse control method

A compound neural network is utilized to identify the dynamic nonlinear system. This network is composed of two parts： one is a linear neural network, and the other is a recurrent neural network. Based on the inverse theory a compound inverse control method is proposed. The controller has also two parts： a linear controller and a nonlinear neural network controller. The stability condition of the closed-loop neural network-based compound inverse control system is demonstrated .based on the Lyapunov theory. Simulation studies have shown that this scheme is simple and has good control accuracy and robustness.

Combined indirect and direct method for adaptive fuzzy output feedback control of nonlinear system

A novel control method for a general class of nonlinear systems using fuzzy logic systems （FLSs） is presertted. Indirect and direct methods are combined to design the adaptive fuzzy output feedback controller and a high-gain observer is used to estimate the derivatives of the system output. The closed-loop system is proven to be semiglobally uniformly ultimately bounded. In addition, it is shown that if the approximation accuracy of the fuzzy logic system is high enough and the observer gain is chosen sufficiently large, an arbitrarily small tracking error can be achieved. Simulation results verify the effectiveness of the newly designed scheme and the theoretical discussion.

Modified Projective Synchronization of a New Hyperchaotic System via Nonlinear Control

In this paper, a nonlinear control scheme of two identical hyperchaotic Chert systems is developed to realize their modified projective synchronization. We achieve modified projective synchronization between the two identical hyperchaotic systems by directing the scaling factor onto the desired value. With symbolic computation system Maple and Lyapunov stability theory, numerical simulations are given to perform the process of the synchronization.

Robust Absolute Stability of General Interval Lur'e Type Nonlinear Control Systems

In this paper, Lyapunov function method is used to study the robust absolute stability of general interval Lur'e type nonlinear control systems. As a result, algebraically sufficient conditions with interval matrix inequality form are obtained for the general interval Lur'e type nonlinear control systems, thus the relationship between the stability of symmetrical interval matrix and the robust absolute stability of general interval Lur'e type nonlinear control systems is established.

Design of Robust Controller for Flexible Joint Robot with Nonlinear Friction Characteristics

A robust controller method for flexible joint robot considering the effect caused by nonlinear friction was presented.The nonlinear friction was denoted as inverse additive output uncertainty relative to the nominal model in our work,based on which the describing function was analyzed in frequency domain,and the weighting function of nonlinear friction was further calculated as well. By combining the friction uncertainty,the mixed sensitivity H∞optimization was proposed as the benchmark for controller design, which also leaded to good performance of robustness. Furthermore,unstructured perturbation to the system was analyzed so that the stability was guaranteed. Simulation results show that the proposed controller can provide excellent tracking and regulation performance.

Nonlinear Backstepping Ship Course Controller

A ship, as an object of course control, is characterized by a nonlinear function describing the static maneuvering characteristics. The backstepping method is one of the methods that can be used during the designing process of a nonlinear course controller for ships. The method has been used for the purpose of designing two configurations of nonlinear controllers, which were then used to control the ship course. One of the configurations took dynamic characteristic of a steering gear into account during the designing stage. The parameters of the obtained nonlinear control structures have been tuned to optimise the operation of the control system. The optimisation process has been performed by means of genetic algorithms. The quality of operation of the designed control algorithms has been checked in simulation tests performed on the mathematical model of a tanker. The results of simulation experiments have been compared with the performance of the system containing a conventional proportional-derivative （PD） controller.

Study of Nonlinear Seismic Response and TMD Primary Control of the Cable-Stayed Bridge Section of the Third Macao-Taipa Bridge

The practical design of the cable-stayed bridge of the 3rd Macao-Taipa bridge is investigated by the finite element analysis program ANSYS, and 3-D elements BEAM188 and BEAM4 are adopted to create a dynamic calculation model. In order to analyze the material nonlinear seismic response of the cable-stayed bridge, the nonlinear behaviors of the ductile plastic hinges of the bridge towers are taken into account by employing the nonlinear rotational spring element COMBIN40. To simulate a major earthquake, three earthquake records were chosen using a wave-choosing program and input into the bridge structure along longitudinal and transversal directions. Comparisons of the linear and nonlinear seismic responses of the cable-stayed bridge are performed. In addition, a study of TMD primary control is carried out using element MASS21 and element COMBIN14, and it is indicated that the effects of mitigation monitoring are evident.

AN EFFICIENT PARALLEL PROCESSING OPTIMAL CONTROL SCHEME FOR A CLASS OF NONLINEAR COMPOSITE SYSTEMS

This article presents an efficient parallel processing approach for solving the opti- mal control problem of nonlinear composite systems. In this approach, the original high-order coupled nonlinear two-point boundary value problem （TPBVP） derived from the Pontrya- gin＇s maximum principle is first transformed into a sequence of lower-order deeoupled linear time-invariant TPBVPs. Then, an optimal control law which consists of both feedback and forward terms is achieved by using the modal series method for the derived sequence. The feedback term specified by local states of each subsystem is determined by solving a ma- trix Riccati differential equation. The forward term for each subsystem derived from its local information is an infinite sum of adjoint vectors. The convergence analysis and parallel processing capability of the proposed approach are also provided. To achieve an accurate feedforward-feedbaek suboptimal control, we apply a fast iterative algorithm with low com- putational effort. Finally, some comparative results are included to illustrate the effectiveness of the proposed approach.

EXACT BOUNDARY CONTROLLABILITY OF 1-D NONLINEAR SCHRDINGER EQUATION

In this paper, the boundary control problem of a distributed parameter system described by the Schrodinger equation posed on finite interval α≤x≤β：{ iyt ＋yzz＋｜y｜^2y = 0, y（α, t） = h1 （t）, y（β, t）=h2（t） for t〉0 （S）is considered. It is shown that by choosing appropriate control inputs （hi）, （j = 1, 2） one can always guide the system （S） from a given initial state φ∈H^S（α,β）, （s ∈ R） to a terminal state φ∈ H^s（α,β）, in the time period [0, T]. The exact boundary controllability is obtained by considering a related initial value control problem of SchrSdinger equation posed on the whole line R. The discovered smoothing properties of Schrodinger equation have played important roles in our approach; this may be the first step to prove the results on boundary controllability of （semi-linear） nonlinear Schrodinger equation.

Nonlinear integral resonant controller for vibration reduction in nonlinear systems

A new nonlinear integral resonant controller（NIRC） is introduced in this paper to suppress vibration in nonlinear oscillatory smart structures. The NIRC consists of a first-order resonant integrator that provides additional damping in a closed-loop system response to reduce highamplitude nonlinear vibration around the fundamental resonance frequency. The method of multiple scales is used to obtain an approximate solution for the closed-loop system.Then closed-loop system stability is investigated using the resulting modulation equation. Finally, the effects of different control system parameters are illustrated and an approximate solution response is verified via numerical simulation results.The advantages and disadvantages of the proposed controller are presented and extensively discussed in the results. The controlled system via the NIRC shows no high-amplitude peaks in the neighboring frequencies of the resonant mode,unlike conventional second-order compensation methods.This makes the NIRC controlled system robust to excitation frequency variations.

Symplectic Numerical Approach for Nonlinear Optimal Control of Systems with Inequality Constraints

This paper proposes a system representation for unifying control design and numerical calculation in nonlinear optimal control problems with inequality constraints in terms of the symplectic structure. The symplectic structure is derived from Hamiltonian systems that are equivalent to Hamilton-Jacobi equations. In the representation, the constraints can be described as an input-state transformation of the system. Therefore, it can be seamlessly applied to the stable manifold method that is a precise numerical solver of the Hamilton-Jacobi equations. In conventional methods, e.g., the penalty method or the barrier method, it is difficult to systematically assign the weights of penalty functions that are used for realizing the constraints. In the proposed method, we can separate the adjustment of weights with respect to objective functions from that of penalty functions. Furthermore, the proposed method can extend the region of computable solutions in a state space. The validity of the method is shown by a numerical example of the optimal control of a vehicle model with steering limitations.

Design of Variable Structure Control by Using the L_2 Gain Method

The robust stabilization problem for a family of nonlinear plants with mismatch uncertainties is addressed, and a solution is presented based on variable structure control theory and H∞ control theory. A kind of boundary layer is built near the ideal switch surface which can eliminate chattering in the switch surface. The proposed control method with L2 gain can guarantee exponential stability of a system state with no parameter uncertainty and exter- nal disturbance, while it can guarantee state ultimate boundness if parameter uncertainty and external disturbance exist. In the proposed design method, stability of the closed-loop system is analyzed by adopting the Lyapurtov func- tion approach. Finally the numerical simulation results show that the proposed smooth variable structure controller has good pelformance without chattering in the switch surface.

计算最优控制辛数值方法

针对最优控制问题(OCP)的辛数值方法研究及应用进行综述。主要涉及内容包括,动力学系统为常微分方程描述的一般无约束、含不等式约束和状态时滞的最优控制问题,微分代数方程描述的一般无约束、含不等式约束和含切换系统的最优控制问题,以及闭环最优控制问题。从间接法和直接法两个求解框架出发,重点介绍本课题组在保辛算法方面的研究工作。在间接法框架下,首先基于生成函数和变分原理,将OCP保辛离散为非线性方程组,再数值求解方程组。在直接法框架下,将OCP保辛离散为有限维的非线性规划问题(NLP),再数值求解。针对闭环最优控制问题,提出了保辛模型预测控制、滚动时域估计和瞬时最优控制算法。研究表明,保辛算法具有高精度和高效率的特点,在航空航天和机器人等领域有着广泛应用前景和价值。

混联Ⅱ型惯容非线性能量阱的动力学特性研究

分别使用非线性恢复力、非线性阻尼替代惯容减振系统中的线性恢复力、线性阻尼,并考虑摩擦力的影响,提出了混联Ⅱ型惯容非线性能量阱.建立了主系统的动力学方程,利用谐波平衡法求解系统在简谐激励下的幅频响应曲线.采用弧长算法和数值法相结合的方法研究了系统的惯质比、非线性阻尼、非线性刚度和摩擦力单个参数对其减振性能的影响.发现非线性刚度和非线性阻尼数值的增大会使峰值先减小后增大,不同的是,前者幅频响应曲线逐渐向右上方向弯曲,后者产生峰值的位置向低频段转移.分析了惯质比、非线性阻尼、非线性刚度3种参数两两组合下对系统减振效果的影响.研究表明,在激励幅值为0.005 m时,惯质比和阻尼同时变化减振效果最好:当ε=0.1时,系统主结构位移峰值的最小值约为0.01 m;而在参数ε=0.001时,整体取值范围内其最大值约为0.061 m;当惯质比取得最佳值0.1时,非线性阻尼和非线性刚度κ_(21)的取值范围变大.在摩擦力的作用下,系统的最大幅值都有不同程度的增加.上述研究可为振动系统减振的研究提供参考.

Stewart平台神经网络非奇异终端滑模控制

针对Stewart平台的六自由度(six degrees of freedom,6-DOF)轨迹跟踪问题,提出一种基于神经网络的非奇异终端滑模控制方法并应用于Stewart平台的位置姿态控制中。通过分析Stewart平台的位置反解和速度反解,建立运动学方程,利用牛顿-欧拉方程建立动力学方程,并结合加速度反解得到了平台的状态空间表达式;基于非奇异滑模面函数,设计非奇异终端滑模控制律。考虑到径向基函数(radial Basis function,RBF)神经网络的逼近特性,采用RBF神经网络对模型未知部分进行自适应逼近,并利用Lyapunov第二法设计了自适应律;通过仿真证明控制器设计的有效性。仿真结果表明,相比于比例积分微分(proportional integral derivative,PID)控制器,提出的RBF神经网络非奇异终端滑模控制器具有更好的轨迹跟踪精度和动态特性。

Control and Synchronization with Known and Unknown Parameters

In this paper, we consider the chaos control for 4D hyperchaotic system by two cases, known & unknown parameters based on Lyapunov stability theory via nonlinear control. We find that there are two cofactors that have an effect on determining any case to achieve the control, the two cofactors are proposed in the control and the matrix that produce from the time derivative of Lyapunov function. In adding, we find some weakness cases in Lyapunov stability theory. For this reason, we design with only one controller and perform a simple change in this control in order to recognize the difference between these cases although all of the controllers are almost similar.

一种新型3-RRPU并联机构的运动学及鲁棒控制研究

针对现有的三平移并联机构大多正解不唯一、较难实现精确稳定运动控制的问题,提出了一种新的3-RRPU型三平移并联机构,同时研究了机构的运动学、动力学及轨迹跟踪控制方法。首先,运用螺旋理论分析了该机构三平移的原理,进行了驱动输入的选取与论证,对机构平台奇异性、驱动奇异性和支链奇异性进行了分析;其次,运用运动学理论建立了运动学模型,推导了位置正、逆解析解;再次,运用拉格朗日动力学理论建立了机构操作空间的刚体动力学模型;最后,提出了一种基于非线性反馈解耦的自适应滑模轨迹跟踪控制方法,以证明其控制稳定性,并基于动力学模型对空间轨迹跟踪精度和控制力矩进行了仿真分析。研究结果表明:3-RRPU并联机构的位置正解在一般位形下具有唯一性,机构的平台奇异位形和驱动奇异位形少且无支链奇异。该轨迹控制方法可使机构在载荷20 kg、速度0.18 m/s、加速度0.12 m/s 2下,实现0.002 m以内的高精度复杂轨迹跟踪;基于Sigmoid函数的轨迹控制方法还能有效削弱控制力矩的抖振,为实现工业领域高速、高精度、高性能的三平移运动提供了新方法。

Stability Analysis, Chaos Control of Fractional Order Vallis and El-Nino Systems and Their Synchronization

In this article the authors have studied the stability analysis and chaos control of the fractional order Vallis and El-Nino systems. The chaos control of these systems is studied using nonlinear control method with the help of a new lemma for Caputo derivative and Lyapunov stability theory.The synchronization between the systems for different fractional order cases and numerical simulation through graphical plots for different particular cases clearly exhibit that the method is easy to implement and reliable for synchronization of fractional order chaotic systems. The comparison of time of synchronization when the systems pair approaches from standard order to fractional order is the key feature of the article.

基于干扰观测器的复杂非线性系统优化控制方法

为了提高具有未知干扰的复杂非线性系统的控制性能和运行性能,提出了一种基于干扰观测器的复杂非线性系统优化控制方法(IOCM).该方法设计了一个基于模糊神经网络的模型逼近器来捕捉系统的非线性动力学,并利用干扰观测器来描述系统的未知干扰,以获得更准确的系统预测模型.然后,在多目标模型预测控制的框架下,提出了一种具有协同成本函数和多梯度算法的优化控制结构,以综合求解设定点和控制律.采用城市污水处理过程基准仿真平台(BSM1)验证所提方法的有效性.实验结果表明:暴雨天气条件下平均出水水质(EQ)为6711 mg/L、平均运行能耗(EC)为3805 kW·h;对比其他分步实现的优化控制方法,IOCM具有较好的鲁棒性,能够提高非线性系统的优化控制性能.

基于参数辨识的电液伺服非线性模型预测控制

针对电液伺服系统存在的非线性、模型不确定性和约束问题,提出了一种基于参数辨识的非线性模型预测控制方法。利用递推最小二乘法辨识电液伺服系统模型参数,以克服模型不确定性;基于模型参数辨识结果,考虑负载流量非线性、控制量约束和状态约束需求,构建性能指标函数,设计了非线性模型预测控制方法,并进行闭环稳定性分析。仿真结果表明,辨识方法可以较快估计出模型参数,最大估计误差为1.802%,相比于PID控制,控制算法的最大轨迹跟踪误差减小了88.66%。所提方法能有效处理系统约束与非线性,具有较好的控制效果。