基于GA和H_∞混合优化的船舶航向控制器设计新方法

提出一种ＧＡ和Ｈ∞混合优化的般舶航向控制器设计新方法。该方法采用Ｈ∞环路成形技术设计船舶航向控制器,成形权函数采用遗传算法进行优化,从而避免了凭经验试凑权函数的盲目性,使控制器的设计系统化,且简单易行。仿真结果表明了该设计方法的有效性     

基于H∞环路成形和自适应神经模糊推理系统的模糊控制器设计

H_∞环路成形方法设计的控制器阶次较高,不便于工程实现和参数调整;用传统方法确定模糊控制器隶属度函数的参数和模糊规则比较费时且难以保证鲁棒性能和时频域性能指标.针对上述情况,提出了一种综合运用H_∞环路成形和自适应神经模糊推理系统来设计模糊控制器的方法.首先采用H_∞环路成形设计方法,得到鲁棒裕量、动态和稳态性能都符合要求的控制器,然后用自适应神经模糊推理系统来逼近此控制器,最后根据自适应神经模糊推理系统参数确定相应的模糊控制器规则和参数.该方法确定模糊控制器隶属度函数的参数精确而省时,且能保证控制器具有较强的鲁棒性和良好的控制效果.通过对小车倒立摆系统进行的仿真,验证了该控制器设计方法的有效性.     

基于RBF神经网络的一类不确定非线性系统自适应H控制

基于RBF神经网络提出了一种H_∞ 自适应控制方法.控制器由等效控制器和H_∞ 控制器两部分组成.用RBF神经网络逼近非线性函数,并把逼近误差引入到网络权值的自适应律中用以改善系统的动态性能.H_∞ 控制器用于减弱外部干扰及神经网络的逼近误差对跟踪的影响.所设计的控制器不仅保证了闭环系统的稳定性,而且使外部干扰及神经网络的逼近误差对跟踪的影响减小到给定的性能指标.最后给出的算例验证了该方法的有效性.     

基于改进遗传算法的环形倒立摆PID参数整定

针对传统的环形倒立摆PID控制器参数整定方法主观性强,系统响应性能不佳等问题,提出来了一种基于改进遗传算法的环形倒立摆PID参数整定方法.采用仿真研究方法,比较了试凑法、遗传算法和改进遗传算法求取的PID控制器参数对环形倒立摆的控制效果.实验表明,相比于试凑法,遗传算法得到的PID控制器参数使系统的超调量减小、调节时间缩短;改进的遗传算法得到的PID控制器参数使系统的响应性能进一步优化.改进遗传算法求取PID控制器参数的方法对于环形倒立摆以外的控制系统也有借鉴作用.     

基于人工蜂群优化的环形二级倒立摆H∞鲁棒控制器设计

采用H∞回路成形控制方法实现环形二级倒立摆系统的平衡控制;对于H∞回路成形控制器来说,权函数的选择直接影响控制器性能,而往往权函数的选择是需要通过设计人员的不断试凑来完成,不仅设计效率低下,而且无法得到最优的控制性能;因此引入人工蜂群算法,依靠其优异的全局寻优能力,完成对H∞回路成形控制器权函数的求解并保证最优的控制器性能;仿真结果表明,蜂群算法能够寻优到最优的权函数参数,对应的H∞控制器能够保证环形二级倒立摆在受到外界干扰的情况下依然保持在平衡位置。     

一种基于预稳定区域的∞控制器参数优化方法

基于控制理论, 提出了一种具有预期闭环极点区域的H_∞ 控制器参数优化设计方法, 该方法设计中既考虑了H_∞ 性能指标又兼顾了动态性能指标, 克服了常规H_∞ 设计方法中不稳定控制器的问题等不足. 实验结果表明, 该方法具有计算简便、可实现性好、鲁棒性和动态品质良好、对模型参数变化的敏感性低等优点.     

基于GA和H∞混合优化的船舶航向控制器设计新方法

提出一种ＧＡ和Ｈ∞混合优化的船舶航向控制器设计新方法,该方法采用Ｈ∞环路成形技术设计船舶航向控制器,成形权函数采用遗传算法进行优化,从而避免了凭试验凑权函数的盲目性,使控制器的设计系统化,且简单易行。仿真结果表明了该设计方法的有效性。     

区间离散广义系统状态反馈鲁棒H∞控制

讨论了一类区间离散广义系统的状态反馈鲁棒H_∞控制问题.在给出区间离散广义系统的等价描述之后,基于系统参数矩阵不等式,得到了问题可解的充分条件,并给出了状态反馈控制器显式表示.所得的控制器保证闭环系统正则,具有因果关系,稳定并且满足给定的H_∞性能指标.数值例子说明了该方法的正确性.     

具有时滞的积分和不稳定对象的鲁棒控制

针对含时滞的积分和不稳定对象提出了一种新颖的两自由度控制结构,首先用一个比例控制器镇定给定值响应,然后基于鲁棒H₂最优性能指标设计给定值跟踪控制器.根据实际运行抗干扰要求,在对象输入和输出端之间设计负载扰动抑制闭环,利用扰动观测器抑制负载干扰信号,通过提出期望的闭环余灵敏度函数来确定扰动观测器,同时给出了扰动抑制闭环保证鲁棒稳定性的充要条件.最后通过仿真实例验证了该方法相对于近期其它方法的优越性.     

混合H2/H∞鲁棒控制器设计

在状态空间描述下,定义了混合H₂/H_∞控制的完整信息、完整控制、干扰顺馈、输出估计这4种典型情况.在二次稳定意义上,讨论了混合H₂/H_∞的性能指标,及这4种典型情况的混合H₂/H_∞线性反馈控制器设计,给出了充分必要条件.在典型情况分析的基础上,研究一般意义上的混合H₂/H_∞反馈控制器设计.H₂和H_∞的干扰输入阵及性能评价函数各不相同时的混合H₂/H_∞反馈控制器,与H₂和H_∞控制器设计相似,归结为解两个Riccati方程.但这两个Riccati方程含有参数,最优解要通过搜索这两个参数得到.结果包含了单纯的H₂和H_∞设计,可看作是H₂,H_∞和混合H₂/H_∞的统一设计方法.最后通过一个简单的例子,说明了控制器设计方法的可行性.     

汽车主动悬架系统H∞控制器的降阶

基于整车模型设计的主动悬架控制系统,控制器阶数往往较高.在保证主动悬架闭环系统性能的情况下如何尽可能地降低控制器的阶数,是有待解决的问题.本文首先建立汽车7自由度整车悬架模型.针对人体敏感的振动频率范围,设计汽车主动悬架H_∞控制器.在此基础上采用Hankel范数最优降阶法对所设计的高阶控制器进行降阶研究,与模态截取法、均衡截取法进行比较,结果显示Hankel范数最优降阶法能获得更好的降阶效果.对采用降阶和全阶控制器的主动悬架系统进行仿真的结果表明,Hankel范数最优降阶法在较大程度地降低控制器阶数的同时,闭环系统频域和时域特性没有明显降低且汽车乘坐舒适性良好.     

Design of distributed PID-type dynamic matrix controller for fractional-order systems

With the continuous requirements for product quality and safety operation in industrial production, it is difficult to describe the complex large-scale processes with integer-order differential equations. However, the fractional differential equations may precisely represent the intrinsic characteristics of such systems. In this paper, a distributed PID-type dynamic matrix control method based on fractional-order systems is proposed. First, the high-order approximate model of integer order is obtained by utilising the Oustaloup method. Then, the step response model vectors of the plant is obtained on the basis of the high-order model, and the online optimisation for multivariable processes is transformed into the optimisation of each small-scale subsystem that is regarded as a sub-plant controlled in the distributed framework. Furthermore, the PID operator is introduced into the performance index of each subsystem and the fractional-order PID-type dynamic matrix controller is designed based on Nash optimisation strategy. The information exchange among the subsystems is realised through the distributed control structure so as to complete the optimisation task of the whole large-scale system. Finally, the control performance of the designed controller in this paper is verified by an example.     

一种基于遗传算法的新的模糊控制器优化方法

通过分析对模糊控制器优化的原理,提出一种新的优化设计方法,通过引入等比因子,实现用三个参数调整输入、输出语言变量的隶属函数,再通过遗传算法寻优包括量化和比例因子在内的这些参数,使得性能指标最大,从而使设计出的模糊控制器性能更优。仿真结果表明,本文方法简单,有效。     

Controller reduction using canonical interactions

A conceptual approach to controller reduction is proposed that is based on closed-loop considerations. The method assesses the interactions between the plant and a high-order controller as described by canonical correlation coefficients. A free parameter in the algorithm of the reduced controller makes it possible to trade stability robustness versus performance. Several examples demonstrate the efficacy of the method     

一类非线性多变量系统的多模型自适应控制

针对一类不确定的非线性多变量离散时间动态系统,提出了一种基于切换的多模型自适应控制方法.该控制方法的特点在于以下两个方面:首先,引入一个高阶差分算子使得非线性系统的非线性项的限制条件不再要求全局有界;其次,提出的控制方法由线性自适应控制器、神经网络非线性自适应控制器以及切换机构组成:线性控制器用来保证闭环系统的输入输出信号有界,神经网络非线性控制器用来改善闭环系统的性能,基于性能指标的切换机构在每一时刻选择性能指标较好的控制器对系统进行控制.理论分析和仿真实验说明了提出的多模型自适应控制方法的有效性.     

A systematic method for design of multivariable fuzzy logic controlsystems

This paper proposes a systematic method to design a multivariable fuzzy logic controller for large-scale nonlinear systems. In designing a fuzzy logic controller, the major task is to determine fuzzy rule bases, membership functions of input/output variables, and input/output scaling factors. In this work, the fuzzy rule base is generated by a rule-generated function, which is based on the negative gradient of a system performance index; the membership functions of isosceles triangle of input/output variables are fixed in the same cardinality and only the input/output scaling factors are generated from a genetic algorithm based on a fitness function. As a result, the searching space of parameters is narrowed down to a small space, the multivariable fuzzy logic controller can quickly constructed, and the fuzzy rules and the scaling factors can easily be determined. The performance of the proposed method is examined by computer simulations on a Puma 560 system and a two-inverted pendulum system     

Differential evolution based high-order peak filter design with application to compensation of contact-induced vibration in HDD servo systems

Sensitivity loop shaping using add-on peak filters is a simple and effective method to reject narrow-band disturbances in hard disk drive (HDD) servo systems. The parallel peak filter is introduced to provide high-gain magnitude in the concerned frequency range of open-loop transfer function. Different from almost all the known peak filters that possess second-order structures, we explore in this paper how high-order peak filters can be designed to improve the loop shaping performance. The main idea is to replace some of the constant coefficients of common second-order peak filter by frequency-related transfer functions, and then differential evolution (DE) algorithm is adopted to perform optimal design. We creatively introduce chromosome coding and fitness function design, which are original and the key steps that lead to the success of DE applications in control system design. In other words, DE is modified to achieve a novel design for hard disk drive control. Owing to the remarkable searching ability of DE, the expected shape of sensitivity function can be achieved by incorporating the resultant high-order peak filter in parallel with baseline feedback controller. As a result, a seventh-order peak filter is designed to compensate for contact-induced vibration in a high-density HDD servo system, where the benefits of high-order filter are clearly demonstrated.     

High-order sliding mode observers and integral backstepping sensorless control of IPMS motor

This paper presents a robust high-order sliding mode interconnected observer and an integral backstepping controller for a sensorless interior permanent magnet synchronous motor. To limit the chattering phenomenon on the observed state, a super twisting algorithm is combined with an interconnected observer to design a new high-order sliding mode observer which will be used for multiple-input multiple-output systems. The proposed observer is used to estimate in finite time the rotor position, the speed and the stator resistance. Moreover, a robust nonlinear controller based on the backstepping algorithm is designed where integral actions are introduced step by step. This controller allows to track a desired reference which is computed by using a maximum-torque-per-ampere strategy. Simulation results are shown to illustrate the performance of the proposed scheme by using significant trajectories including the zero speed and under parametric uncertainties.     

Robust Output Feedback Consensus of High-order Multi-agent Systems with Nonlinear Uncertainties

In this paper, the output feedback consensus problem of high-order multi-agent systems with nonlinear uncertainties is researched by the robust control method. By the dimensional extension of the observation matrix, the consensus control problem is transformed into a stability problem. Then the robust controller is designed by combining the nominal controller and the robust compensator. The nominal controller can obtain desired nominal performance based on the output informations. The robust compensator, which relys on robust signal compensation technology, is order to suppress the nonlinear uncertainties. According to the proposed method, output consensus error can be guaranteed as small as desired. Finally, simulation results are given to illustrate the effectiveness of this control method.     

Single-loop controller design via IMC principles

In this paper, a new internal model control (IMC)-based single-loop controller design is proposed. The model reduction technique is employed to find the best single-loop controller approximation to the IMC controller. Compared with the existing IMC-based methods, the proposed design is applicable to a wider range of processes, and yields a control system closer to the IMC counterpart. It can be made automatic for on-line tuning. The users have the option to choose between PID and high-order controllers to suit the applications better. It turns out that high-order controllers may be necessary to achieve high performance for essentially high-order processes.