基于交流伺服电机的关节位置多目标优化控制

给出了采用X－Q自适应控制构成的一类非线性控制器以及实现多目标优化控制系统的计算机辅助设计参数寻优方法,讨论怎么应用X－Q自适应控制器实现多目标优化控制,并给出实现多目标优化机器人关节位置控制系统的实例。计算机仿真校验其性能指标的结果表明,多目标优化系统的性能指标好,设计方法简单、通用、适用于工程设计。     

太阳光源跟踪伺服系统的多目标优化控制

为了实现多目标优化控制的性能,提出了采用X—Q自适应控制器构成的一类非线性控制器,以及实现多目标优化控制系统的计算机辅助设计参数寻优方法,讨论了怎样应用X—Q自适应控制器实现多目标优化控制,并给出实现多目标优化太阳光源跟踪伺服系统实例。仿真校验其性能指标的结果表明,多目标优化系统的性能指标好,设计方法简单、通用,适用于工程设计。     

自适应模糊PID控制的无刷直流电机及仿真

提出了利用自适应模糊PID控制器实现对永磁无刷直流电机调速系统进行设计的新方法。文中首先建立永磁无刷直流电机的数学模型，以此进行转速和电流双闭环调速系统控制；并通过调节PWM发生器的开关频率来减少转矩脉动。接着将模糊控制器和PID控制器通过自适应因子结合，在线自调整控制参数，进一步完善了PID控制器的性能，提高了系统的控制精度。并把MATLAB中的Fuzzy Toolbox和SIMULINK以及Power System Blockset有机结合起来，实现了该自适应模糊PID控制器的计算机仿真。结果表明，该方法有较高的精度。     

基于预估模型切换的过热汽温无辨识自适应控制

针对电厂锅炉的过热汽温系统具有大惯性、大时滞和多模型等特性.研究一种基于预估模型切换的无辨识自适应预估控制方法.该方法需设计一个无辨识自适应预估控制器和基于主蒸汽流量变化率的切换律,给出若干个一阶预估模型.在系统运行过程中,这些预估模型在切换律控制下根据运行工况按优化切换时间自适应地切换,而其中的优化切换时间是用切换系统优化理论计算得到的.仿真试验结果表明,该方法适用于过热汽温系统,具有良好的控制品质、较强的抗扰和自适应能力,且对预估模型的精度要求不高,控制参数容易整定,易于工程实现.     

多机电力系统参数自适应控制设计的模型与应用

针对具有非线性负荷的多机电力系统（MMEPS）励磁控制的跟踪和系统参数的不确定，采用非线性分代数系统（DNAS）的反馈线性化技术，得到相应的以电磁功率作为输入量的标准化控制方程，并给出相应的非线性控制规律的表达式，提出了参数自适应控制方程，并得到相应的非线性控制器的表达式，实现了具有非线性负荷的MMEPS的目标跟踪及其稳定性。     

多个时滞混沌系统自适应有限时间同步控制

针对多个时滞混沌系统,研究了其有限时间同步控制问题,所考虑的混沌系统具有不同的结构和时变状态时滞,通过设计适当的自适应更新律,用以在线更新控制器的增益,从而达到更快地收敛速度,并给出了自适应控制器设计方法。利用Lyapunov稳定性定理和有限时间稳定性理论,证明了所设计的自适应控制器和相应的控制增益自适应更新律,均能保证多个误差动态系统的状态在有限时间内达到同步,并给出了同步过渡时间的估计。最后,通过对3个典型的混沌系统,即Lorenz系统、Chen系统和Lü系统的算例仿真,进一步验证了所提自适应有限时间同步控制方法的可行性和有效性。     

基于神经网络的永磁同步电机矢量控制

采用单神经元自适应PID控制器对永磁同步电机进行了调速控制。详细介绍了PMSM(Perrnanent Magnet Synchronous Motor)的矢量控制原理。最后给出PMSM单神经元自适应PID控制的仿真结果和硬件实现方法。仿真结果表明，该系统具有良好的动态性能。     

汽包锅炉汽轮机系统的非线性σ校正复合模型参考自适应控制

提出引入σ校正技术的复合模型参考自适应控制方法,可以克服已知的系统干扰。存在未建模动态和未知干扰时,在任何有界的初始条件下,σ校正复合模型参考自适应控制系统的跟踪误差都是有界的。针对典型的汽包锅炉汽轮机系统的非线性模型,将静态状态反馈精确线性化方法和σ校正复合模型参考自适应控制方法相结合,设计了协调控制器。讨论了静态全状态反馈线性化对多输入多输出系统的干扰抑制能力和对多输入多输出摄动系统的鲁棒线性化问题。介绍了非线性σ校正复合模型参考自适应控制器的设计方法。给出了满足约束条件前提下的模型匹配条件的极点配置设计方法。仿真结果表明,所设计的复合控制系统可以实现良好的解耦控制,鲁棒性和抗干扰能力强。     

电液伺服系统的非线性鲁棒自适应控制

摘要：针对电液伺服非线性系统的参数不确定性以及模型不确定项，基于Lyapunov稳定方法，提出了一种适用于电液伺服系统的非线性鲁棒自适应控制策略。首先以跟踪误差为基础给出系统目标控制函数的定义方法，然后基于Lyapunov稳定性分析方法，给出了不确定参数的自适应律， 以及自适应控制器的设计。同时引入一种简单的鲁棒设计方法补偿系统的模型不确定项。该方法具有结构简单，鲁棒性强的特点，并且系统控制量平稳，无振动现象出现。仿真结果显示，采用该控制方法可取得良好的控制效果，并进一步证实了理论分析的正确性。     

一种新型的自适应推理控制恒压恒频交流电源的研究

针对CVCF交流电源系统这样一个输出可测，而负荷扰动不可测的系统推理控制器数学模型的建立及其自适应问题进行了分析、讨论和研究；在推理控制器的设计中，提出了一种简化的等效设计方法，获得了在物理上可以实现的推理控制器模型。由于CVCF交流电源系统其对象是具有非线性和时变性的，为了获得良好的动态响应，使系统具有更强的鲁棒性，在上述研究的基础上，通过建立参数估计模型来实现推理控制器的自适应控制。理论分析和仿真实验结果证明了该文所研究的自适应推理控制设计方法应用于CVCF交流电源系统的有效性，系统在动态响应、抗干扰能力、增强鲁棒性等获得了令人满意的结果。介绍了应用新型芯片DSP-ADMC331设计和实现CVCF交流电源自适应推理控制系统，其有着广阔的应用前景。     

Multi-objective PID controller tuning for a FACTS-based damping stabilizer using Non-dominated Sorting Genetic Algorithm-II

Design of an optimal controller requires optimization of multiple performance measures that are often noncommensurable and competing with each other. Design of such a controller is indeed a multi-objective optimization problem. Non-Dominated Sorting in Genetic Algorithms-II (NSGA-II) is a popular non-domination based genetic algorithm for solving multi-objective optimization problems. This paper investigates the application of NSGA-II technique for the tuning of a Proportional Integral Derivate (PID) controller for a Flexible AC Transmission System (FACTS)-based stabilizer. The design objective is to improve the damping of power system when subjected to a disturbance with minimum control effort. The proposed technique is applied to generate Pareto set of global optimal solutions to the given multi-objective optimization problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented and compared with a conventionally designed PID controller under various loading conditions and disturbances to show the effectiveness and robustness of the proposed approach. Finally, the proposed design approach is extended to a multi-machine power system to damp the modal oscillations with minimum control efforts.     

Robust optimal centralized controller to mitigate the small signal instability in an islanded inverter based microgrid with active and passive loads

This paper proposes a robust optimal centralized controller to mitigate the small signal instability caused by the interaction between the control loops of rectifier interfaced active loads (RIALs) and the inverter interfaced distributed generations. The proposed controller is based on a robust linear quadratic regulator with prescribed degree-of-stability (LQRPDS). In order to reduce communication system burden and improve the flexibility and reliability of the proposed controller, a kalman state estimator has been designed. The optimal values of the diagonal weighting matrices of LQRPDS and kalman estimator are obtained by formulating a bi-objective optimization problem, which is solved using a fast and elitist multi-objective non-dominated sorting genetic algorithm (NSGA-II). A full dynamical linearized state space model of an islanded MG represented in synchronous (DQ) reference frame has been considered for analyzing the stability. However, schur balanced model order reduction technique has been used to reduce the complexity in the design of the controller. Eigenvalue analysis and time-domain simulations have been presented to demonstrate the robust performance of the controller under various load configurations as well as under step load disturbances. The efficacy of the proposed centralized controller is verified by comparing its performance with that of LQR based centralized controller.     

Optimal coordinated design of UPFC and PSS for improving power system performance by using multi-objective water cycle algorithm

This paper presents an optimal design for simultaneously locating unified power flow controller (UPFC) and power system stabilizer (PSS). The parameters of their controllers are also tuned coordinately to enhance the power system stability. A mixed integer nonlinear problem is obtained for the design procedure due to the characteristics of selected objective functions. A new population-based meta-heuristic algorithm, called water cycle algorithm (WCA) is used to solve this problem. The best Pareto optimal set is also attained by defining this problem as a multi-objective function. The simulations results on IEEE 39-bus power system confirm the efficiency and the superior performance of the proposed method when compared with other algorithms.     

基于多目标优化的时滞广域阻尼控制器设计

提出一种考虑区间模式和本地模式协调的时滞广域阻尼控制器设计新方法。首先,根据能控能观指标找出最佳反馈信号和输出控制量。然后,计算超前滞后补偿的时间常数,并构建区间和本地模式协调优化的多目标函数,应用"教与学"优化算法确定最优增益序列。最后,应用均衡降阶算法对系统进行降阶,基于线性矩阵不等式(LMI)理论分析最优增益序列,选出对时滞鲁棒性最好的值。新英格兰测试系统的仿真结果表明,提出的基于多目标优化的时滞广域阻尼控制器设计方法,在很好地抑制了区间振荡模式的同时,保证本地振荡模式不被恶化,并且对时滞具有很好的鲁棒性。     

Multi-objective evolutionary algorithm for SSSC-based controller design

In this paper, an evolutionary multi-objective optimization approach is employed to design a static synchronous series compensator (SSSC)-based controller. The design objective is to improve the transient performance of a power system subjected to a severe disturbance by damping the multi-modal oscillations namely; local mode, inter-area mode and inter-plant mode. A genetic algorithm (GA)-based solution technique is applied to generate a Pareto set of global optimal solutions to the given multi-objective optimization problem. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. Simulation results are presented and compared with a PI controller under various disturbances namely; three-phase fault, line outage, loss of load and unbalanced faults to show the effectiveness and robustness of the proposed approach.     

多目标优化控制系统

本文输出多目标优化控制系统（ＭＯＣＳ）的定义、稳定判据和用来实现ＭＯＣＳ优化 三种非线性控制器（Ｃｌｅｇｇ积分器、Ｘ－Ｑ和Ｘ－Ｊ两种过渡过程自适应ＰＩＤ）与三种优化算法,并给出相应的算例。性能指标好,易于工程实现,解决了控制率中长期没有解决的ＭＯＣＳ优化控制问题。     

Implementation of vibration suppression control on FWL processor

In motion or process control systems, a variety of design techniques have been proposed because of the demand for high performance. The higher performance we demand, the higher the degree of the controller becomes. The controller is generally designed by a CAD system and implemented with a microprocessor. But the microprocessor does not have enough precision to realize the results of design by the CAD system. Therefore, the system performance is degraded by finite word length (FWL) effects. To deal with FWL problems, many design methods have been considered in the signal processing field, and high‐ordered digital filters are often used. Among these methods, the implementation technique based on the state‐space realization can minimize the sensitivity to perturbation of coefficients. Noting that optimal realizations with the same transfer function are unique only up to an orthogonal similarity transformation, we must choose the realization within this class of optimal realizations. In this paper, we present an algorithm to find a state‐space realization which minimizes the frequency‐weighted sensitivity measure of the controller performance. Furthermore, we present some experimental results to verify the effectiveness of the proposed algorithm. © 1999 Scripta Technica, Electr Eng Jpn, 128(1): 45–52, 1999     

基于混沌优化的多变量系统最优控制器设计

基于混沌变量,本文提出一种多变量系统的最优控制器设计方案。针对二次型最优控制中加权矩阵难以确定的问题,引入一种全新的性能指标,实现混沌大范围粗搜索和局部细搜索相结合,搜索出全局最优的权系数。并对通过该方法确定加权阵的LQ控制系统的稳定性进行了分析。最后,本方案在实物二级倒立摆上进行了实验,实验结果证明了该最优控制器设计方法的有效性和实用性。