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1.
杨国华 《科技通报》2003,19(6):470-472
利用神经网络离散建模算法,给出了非线性离散系统的一种新颖的迭代学习控制方法.该迭代学习控制方法允许控制初始状态误差的存在且保证仅经过几次迭代就可使系统达到很高的控制精度.  相似文献   

2.
介绍了迭代学习控制原理和技术方法,根据伺服系统的特点,以电液位置伺服系统为例,针对以往PID控制的不足提出将迭代学习控制方法应用在伺服系统中,并用Matlab做出仿真进行效果分析。  相似文献   

3.
针对纯滞后、非线性、时变的胶黏剂生产过程,引入迭代学习控制方法,对反应液温度进行控制。仿真结果表明:与PID控制方法相比,迭代学习PID控制性能更好。  相似文献   

4.
针对两轴伺服系统的研究轮廓误差控制问题,提出了一种串级型迭代学习交叉耦合轮廓误差控制方法,设计了控制器结构并且给出了两轴迭代学习交叉耦合控制算法的收敛条件.仿真结果表明此方法可以实现跟踪误差和轮廓误差的有效补偿.  相似文献   

5.
基于逆系统的变轨迹迭代学习控制   总被引:1,自引:0,他引:1  
王晔  刘山 《科技通报》2010,26(1):120-124
针对一类未知非线性时变系统,本文提出一种不同次迭代运行过程中期望轨迹可变的迭代学习控制算法。该算法利用高斯径向基网络逼近系统逆的未知参数,并采用迭代学习的方式修正网络逼近的系数,然后结合变结构技术设计控制律。收敛性分析表明,随着迭代次数的增加,逼近系数与最佳系数的差异逐渐减小。最后,在机械臂上的仿真验证了算法的有效性。  相似文献   

6.
研究采用Bcklund变换的双线性化常微分方程非凸松弛解分析问题,双线性化常微分方程非凸松弛解是保证模型平稳分布和存在性的重要因素,从而提高许多模型在不同边界条件下的稳定特性。把双线性化常微分方程的非凸松弛解算子进行敏感域分析表征,采用Bcklund变换进行目标函数统一迭代,得到非凸松弛解的3种核函数分别是线性核函数、多项式核函数和高斯核函数。计算双线性化常微分方程的非凸松弛解的对称广义中心的稳定性平衡点,计算线性化常微分方程的非凸松弛解满足的边界条件,通过Bcklund变换扩展欧几里得算法,实现对非凸松弛解的稳定性和收敛性的证明,得到在不同多向增量式和减量式分析下,采用Bcklund变换的双线性化常微分方程非凸松弛解是收敛和稳定的。  相似文献   

7.
李琰 《科技通报》2015,(4):82-84
在保密通信中,导频信号需要通过加密方法实现同步控制,传统方法对保密通信的同步导频控制信号加密采用Co-training监督学习加密算法,无法获得足够泛化性能的控制密钥,承载信息信号所引起的导频信号的抗噪性能差,加密性能不好。提出一种基于高斯差分双线性映射的改进的training监督学习导频对称加密方法,构建半监督学习算法及驱动-响应式导频信号保密通信系统,引入SVM监督学习辅助策略和富信息策略到Tri-training学习过程,构建高斯差分双线性映射构建Sprott系统,得到导频加密信号的平面奇怪吸引子,构建保密通信的调制、解调与反向导频对称加密同步控制算法。仿真实验表明采用该算法进行导频信号对称加密,能使得通信系统中已调信号实现同步控制,又能承载信息加密传输,使其独立完成信道传输两端通信收发,抗噪性能和准确性较优。  相似文献   

8.
迭代学习控制系统的鲁棒性分析   总被引:5,自引:0,他引:5  
孙明轩 《科技通报》1996,12(4):198-203
讨论了在偏离,状态输出扰动和非线性扰动同时存在的干扰环境中运行的迭代学习控制系统的鲁棒性问题。通过更精确的误差渐近界估计,结合迭代学习控制算法中的开环和闭环方案,给出了算法的鲁棒性条件,以及算法收敛性所要求的渐近干扰条件。  相似文献   

9.
大学学报     
《中国科技信息》2011,(15):10-14
广义系统静态输出反馈控制的一个新方法 摘要对广义系统提出了一种新的、简单的静态输出反馈控制器的设计方法.通过引入辅助矩阵变量.对含有Lyapunov矩阵和输出反馈控制器增益矩阵的双线性不等式进行解耦.并结合变量替换法将双线性不等式及包含Lyapunov矩阵的非严格不等式转化为线性矩阵不等式(LMI).利用这种方法.能够得到保证闭环广义系统容许性的LMI条件和静态输出反馈控制器.一个数值例子表明了所提方法的有效性该方法很容易推广到正常系统的静态输出反馈控制.  相似文献   

10.
在密码协议中,双线性对得到了广泛的应用,对于一些协议的构造,则更多应用了其特殊形式--反身双线性对.该文研究了仅X坐标的反身双线性对的计算,与原来的双线性对计算相比较,运算速度提高了接近42%,并且节省了部分带宽,所以该方法能够较好地应用在资源受限的环境中.  相似文献   

11.
In this paper, an iterative learning control strategy is presented for a class of nonlinear pure-feedback systems with initial state error using fuzzy logic system. The proposed control scheme utilizes fuzzy logic systems to learn the behavior of the unknown plant dynamics. Filtered signals are employed to circumvent algebraic loop problems encountered in the implementation of the existing controllers. Backstepping design technique is applied to deal with system dynamics. Based on the Lyapunov-like synthesis, we show that all signals in the closed-loop system remain bounded over a pre-specified time interval [0,T]. There even exist initial state errors, the norm of tracking error vector will asymptotically converge to a tunable residual set as iteration goes to infinity and the learning speed can be easily improved if the learning gain is large enough. A time-varying boundary layer is introduced to solve the problem of initial state error. A typical series is introduced in order to deal with the unknown bound of the approximation errors. Finally, two simulation examples show the feasibility and effectiveness of the approach.  相似文献   

12.
In this paper, the development and experimental validation of a novel double two-loop nonlinear controller based on adaptive neural networks for a quadrotor are presented. The proposed controller has a two-loop structure: an outer loop for position control and an inner loop for attitude control. Similarly, both position and orientation controllers also have a two-loop design with an adaptive neural network in each inner loop. The output weight matrices of the neural networks are updated online through adaptation laws obtained from a rigorous error convergence analysis. Thus, a training stage is unnecessary prior to the neural network implementation. Additionally, an integral action is included in the controller to cope with constant disturbances. The error convergence analysis guarantees the achievement of the trajectory tracking task and the boundedness of the output weight matrix estimation errors. The proposed scheme is designed such that an accurate knowledge of the quadrotor parameters is not needed. A comparison against the proposed controller and two other well-known schemes is presented. The obtained results showed the functionality of the proposed controller and demonstrated robustness to parametric uncertainty.  相似文献   

13.
In this paper, a novel fractional-order partial pole assignment (FPPA) control algorithm is proposed for systems with time-delay. The FPPA control algorithm is essentially an extension of the original pole assignment, which could change undesired pole locations into desired pole locations. The presented control scheme can be used on open loop poorly damped or unstable systems, which is superior to most other time-delay compensation schemes. The discussion on choosing desirable pole locations is presented based on stability and resonance conditions in the frequency domain. The controlled system is also studied in the time domain based on different transient performance indicators, namely overshoot, settling time, and rising time. In addition, the parameters of the proposed FPPA control algorithm are tunable, thus the control scheme can be used to satisfy different control requirements. Simulation results of stable and unstable fractional-order plants with time-delay are shown to verify the effectiveness and practicability of the FPPA control algorithm.  相似文献   

14.
The dynamics of Pressurized Heavy Water Reactor (PHWR) are complex and open-loop unstable in nature. In such systems, parametric and input disturbances may cause instability if the control system fails to reject these disturbances. For such a large, unstable and uncertain process, designing a control scheme with the ability to reject disturbances along with good reference tracking capabilities is a challenging problem. The control scheme should not only be robust but also deterministic and easier to implement. In order to fulfill all these control scheme requirements for nuclear industries, in this work, a Cross-Coupled Nonlinear Proportional Integral Derivative (CCN-PID) scheme is suggested for a 70th order Multi-Input Multi-Output (MIMO) PHWR. It is also shown in this work that the proposed CCN-PID is a simple Cross-Coupled Proportional, Nonlinear Integrator and Derivative (CC-PNID) sliding surface based Sliding Mode Control (SMC). Furthermore, for the output feedback design, a High Gain Observer (HGO) is constructed for the PHWR process. In order to assure robust stability of the closed loop system, a Lyapunov based analysis of the state feedback CCN-PID control scheme is firstly presented. Then, in a similar way, robust stability analysis of HGO is carried out and finally, the stability analysis of the HGO and CCN-PID based output feedback control scheme is evaluated. In order to investigate the performance of the designed HGO based output feedback CCN-PID control scheme, four different scenarios are simulated. The results of these simulations show that the suggested control scheme efficiently rejects parametric uncertainties and input disturbances and corrects the power tilts while keeping the reactor stable and within safe limits of operation. The results also show that the scheme controls the reactor in an effective manner such that the reactor power closely follows the reference signal. The results of the control scheme presented in this work are also compared with earlier works.  相似文献   

15.
A homing mechanism is required for repositioning as a system performs tasks repeatedly. By examining the effect of poor repositioning on the tracking performance of iterative learning control, this paper develops a varying-order learning approach for the performance improvement. Through varying-order learning, the resultant system output trajectory is ensured to follow a given trajectory with a lowered error bound, in comparison with the conventional fixed-order method. A discrete-time initial rectifying action is introduced in the formed varying-order learning algorithm, and a sufficient condition for convergence is derived. An implementable scheme is presented based on the proposed approach, and illustrated by numerical results of two examples of robotic manipulators.  相似文献   

16.
This paper proposes a unified method to design an optimized type of the hysteresis modulation-based sliding mode current controller for non-minimum phase power converters in continuous conduction mode. The traditional sliding mode controlled converters have a slow transient voltage response at heavy loads, a large overshoot at light loads and during abrupt output resistance variations. To solve these problems, an optimized feedback control scheme is used according to the output resistance to adjust the coefficients of the controller. The basic idea of this controller is to suggest a new way for reduction of the sensitivity function amplitude of the closed loop system. The presented approach is developed for three basic DC/DC converters; i.e. boost, buck-boost and quadratic boost converters. Generally, the certain advantages of the suggested control approach are: (i) a fast transient response can be achieved in heavy load conditions, (ii) the voltage overshoot can be effectively reduced during load variations; (iii) the transient voltage overshoot can be eliminated in light load conditions; (iv) the closed loop control sensitivity can be reduced and therefore, the performance specification of a control system can be improved compared with the conventional sliding mode current control. To show the reliability of the suggested control scheme, simulations and experimental results for the derived systems are developed. Several conditions are performed to confirm the effectiveness of the proposed controller.  相似文献   

17.
This paper presents a fixed-time composite neural learning control scheme for nonlinear strict-feedback systems subject to unknown dynamics and state constraints. To address the problem of state constraints, a new unified universal barrier Lyapunov function is proposed to convert the constrained system into an unconstrained one. Taking the unconstrained system, a modified fixed-time convergence state predictor is explored, enabling the prediction error for compensating the neural adaptive law to be obtained and improving the learning ability of online neural networks (NNs). Without employing fractional power terms or a complicated switching strategy to build the control law, a new method of constructing a smooth fixed-time dynamic surface control scheme is proposed. This overcomes the potential singularity problem and the explosion of complexity often encountered in fixed-time back-stepping designs. The representative features of our design are threefold. First, it is free of the fractional power terms, yet offers fixed-time convergence. Second, it addresses the state constraint problem without requiring a feasibility check. Third, it constructs a new state-predictor and enhances the approximation accuracy of NNs. The stability of the proposed control scheme is analyzed using the Lyapunov technique. Simulation results are presented to illustrate the effectiveness of the proposed controller.  相似文献   

18.
This paper is concerned with the problem of adaptive event-triggered (AET) based optimal fuzzy controller design for nonlinear networked control systems (NCSs) characterized by Takagi–Sugeno (T–S) fuzzy models. An improved AET communication scheme with a memory adaptive rule is proposed to enhance the utilization of the state response vertex data. Different from the existing ET based results, the improved AET scheme can save more communication resources and acquire better system performance. The sufficient criteria of performance analysis and controller design are presented for the closed-loop control system subject to mismatched membership functions (MFs) and AET scheme. And then, a new MFs online learning algorithm on the basis of the gradient descent approach is employed to optimize the MFs of fuzzy controller and obtain optimal fuzzy controller for further improving system performance. Finally, two simulation examples are presented to verify the advantage and effectiveness of the provided controller design technique.  相似文献   

19.
The recent transition in power generation and consumption is based on the integration of renewable energy sources using DC microgrids. To facilitate this integration, a multi-source DC microgrid structure with wind, photovoltaics, fuel cell and hybrid energy storage system including battery and supercapacitor is presented in this paper. These sources are linked to a DC-bus via DC-DC converters. A hierarchical control strategy with a device and a system-level control for coordinated control between energy sources and their storage devices is proposed. In the device-level control, a variable structure based sliding mode control is applied to regulate the DC bus voltage and to ensure global asymptotic stability. Whereas, the system-level control compensates for the supply and demand mismatches by using a rule-based fuzzy system. To verify the effectiveness of the proposed scheme and the superiority of one controller over another, the proposed controllers are simulated and compared in the MATLAB/Simulink environment under varying load and weather data conditions. Results show that super twisting sliding mode control had negligible chattering as well as better convergence as compared to controllers. Furthermore, the efficiency of the developed scheme is validated by controller hardware in loop experiments.  相似文献   

20.
The backstepping-based adaptive tuning functions design is a control-scheme for uncertain systems that ensures reasonably good stability and performance properties of the closed loop. The complexity of the controller makes inevitable the use of digital computers to perform the calculation of the control signal. This paper addresses the issue of the numerical sensitivity of this control scheme. It is shown that while the increase of the design parameters may be desirable to achieve a good transient performance, it harms the control signal as this increase introduces large high-frequency components due to the numerical errors. The presented results suggest that it is necessary a certain compromise between the choice of the design parameters and the numerical precision of the tools involved in the control design. This compromise can be quantified by explicit expressions.  相似文献   

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