【作者】 曲子芳；

【导师】 张正娣；

【作者基本信息】 江苏大学 ， 控制科学与工程， 2021， 博士

【摘要】 非线性动力系统的运行体系和交互机制伴随着科学技术的飞速发展而愈加复杂,于是,人类对系统的多样性功能和智能化水平提出了更高的期望和要求。同时,由于系统动力学环境的差异性、能量的突变性和机械构造的复杂性等因素的存在,导致被控对象（过程）也变得越来越复杂,从而使整个受控系统往往呈现出非线性、不确定性和以时滞、执行器或传感器故障、状态不可量测为特征代表的复杂性。因此,针对此类系统的控制方案的研究和设计标准在不断地更新,期望所设计的控制方案能够使得系统快速趋于稳定的同时,既能维持系统的控制性能,又能保证系统的安全运作。基于非线性动力控制系统的研究现状,本文采用模糊采样控制方法做进一步的改进研究和应用拓展,并通过采取有效的控制策略及设计可靠的控制方案使得系统渐近稳定,从而实现控制方案的简单实用和降低算法保守性等目标。最终使系统性能得以优化,且系统将具有较好的稳定性、较高的运行效率及更简单灵活的操作流程等。本文主要研究内容如下:1.非线性时滞动力系统的模糊采样H₂/H_∞控制研究主要探讨了具有时滞行为的非线性动力系统的模糊采样控制问题,实现了H₂/H_∞性能。通过运用输入时滞方法,进行了模糊采样H₂/H_∞控制系统的稳定性分析与综合。利用Lyapunov-Krasovskii稳定性理论,提出了新的H₂/H_∞控制标准,设计了能同时保证H₂性能和H_∞性能的模糊采样控制器。研究提出的控制器的有效性通过卡车拖车系统和连续搅拌釜式反应堆系统进行了仿真验证。仿真结果表明所提出的模糊采样H₂/H_∞控制器具有更加优越的性能。2.非线性时变时滞动力系统的模糊采样H_∞控制研究主要讨论了具有时变时滞行为的非线性动力系统的模糊采样控制问题,实现了H_∞性能。采用Takagi-Sugeno（T-S）模糊模型描述系统,根据Lyapunov-Krasovskii稳定性理论,提出了一种模糊采样H_∞控制算法。运用线性矩阵不等式得到了控制器存在的一些充分性条件,该条件使得H_∞性能衰减到规定的水平,并保证模糊闭环系统渐近稳定。以卡车拖车系统为仿真算例,验证了所提出设计方案的有效性。3.非线性时变时滞动力系统的模糊采样最优控制研究主要探究了具有时变时滞行为的非线性动力系统的模糊采样最优控制问题。基于Lyapunov-Krasovskii稳定性理论,利用自由权值矩阵方法,建立了一些新的稳定性判据。为了保证模糊采样闭环控制系统渐近稳定,设计了T-S模糊采样控制器。通过对比分析发现所得结果具有较低的保守性。运用计算机模拟的卡车拖车系统和连续搅拌釜式反应堆系统两个实验验证了所提出的设计方案的有效性和优越性。4.非线性不可靠动力系统的区间二型模糊采样H_∞控制研究主要研究了具有参数不确定性和随机通信的非线性动力系统的区间二型模糊采样H_∞控制问题。将非线性系统建模为区间二型T-S模糊模型结构,利用上、下隶属度函数有效地表征参数的不确定性,充分利用线性矩阵不等式和自由权值矩阵,在数学期望意义下设计了区间二型模糊采样控制器,使模糊闭环系统保持渐近稳定,并满足H_∞性能指标。以倒立摆系统为例展示了模糊采样控制设计的适用性和优越性。5.非线性不可靠动力系统的区间二型模糊采样最优控制研究主要分析了具有参数不确定性和数据丢包的非线性动力系统的区间二型模糊采样最优控制问题。考虑到被控系统具有非线性、参数不确定性和数据丢包等多种特征,采用区间二型模糊系统对其进行建模分析。运用自由权值矩阵方法,在Lyapunov-Krasovskii稳定性理论的基础上,得到了基于线性矩阵不等式的有效控制方案。定性分析中充分利用隶属度函数的属性和边界信息,放宽了所提出的充分性条件,基于此,提出了有效可行的控制器,使模糊闭环系统保持渐近稳定,并满足最优控制性能指标。运用倒立摆系统仿真实验对模糊控制方案的有效性进行了充分的验证。更多还原

【Abstract】 The operation system and interaction mechanism of nonlinear dynamic system become more and more complex.Therefore,human beings put forward more expectations and requirements for the diversity function and intelligent level of the system.At the same time,due to the differences of system dynamics environment,energy,respectively,and the complexity of the mechanical structure of the controlled object（process）is also becoming more and more complex,thus,the controlled system performance is often complicated nonlinearity,uncertainty and time delay,actuator or sensor failures,state measurement to represent characteristics of complexity.Therefore,the research and design of the system control scheme have a higher standard.It is expected that the designed control scheme can make the system quickly become stable,which can not only maintain the control performance of the system,but also ensure the safe operation of the system.Based on the research status of nonlinear dynamic control system,this topic will further improve the fuzzy sampled-data control method and expand its application,in order to achieve the goal of simple and practical control scheme and reduce the conservatism of algorithm,make the system stable,high operation efficiency,simple and flexible operation,and provide reliable feasibility control for nonlinear dynamic system control scheme and effective control strategy.The framework of this paper is as follows:1.Research on fuzzy H₂/H_∞sampled-data control for nonlinear dynamical systems with time delayIn this chapter,the problem of fuzzy sampled-data H₂/H_∞control for a class of nonlinear dynamical systems with time delay is studied.The synthesis and stability analysis of fuzzy H₂/H_∞sampled-data control for dynamic systems with time delay are studied by using the input delay method.Based on Lyapunov-Krasovskii stability theory,a new H₂/H_∞criterion is proposed,and a fuzzy sampled-data controller is designed to guarantee both H₂and H_∞performance.The design principle of the controller is verified by two examples.Experimental results show that H₂/H_∞sampled-data control has better performance.2.Study on fuzzy Sampled-data H_∞control for nonlinear time-varying delay dynamical systemsThe problem of sampled-data H_∞control for nonlinear fuzzy systems with time-varying delay is studied.Takagi-Sugeno（T-S）fuzzy model is used to describe the system.According to Lyapunov-Krasovskii stability theory,a fuzzy sampled-data H_∞control algorithm is obtained.In addition,by using linear matrix inequalities（LMIs）,some sufficient conditions of the controller are obtained,which make the H_∞performance decay to the specified level and make the fuzzy closed-loop system stable.The mechanical system is taken as an example to prove the feasibility of the design scheme.3.Research on fuzzy sampled-data optimal control for nonlinear time-varying delay dynamical systemsThe fuzzy sampled-data optimal control problem of a class of nonlinear dynamical systems with time-varying delay behavior is studied.Based on Lyapunov-Krasovskii stability theory,some new stability criteria are established.In order to ensure the asymptotic stability of the fuzzy closed-loop sampled-data control system,an efficient and feasible controller is designed.The results show that the conclusions are less conservative in stability analysis.Two examples of truck trailer system simulated by computer and continuous stirred tank reactor system are given to illustrate the superiority and feasibility of the design.4.Interval type-2（IT2）fuzzy sampled-data H_∞control for nonlinear and unreliable dynamical systemsThe problem of IT2 fuzzy sampled-data H_∞control is studied for nonlinear systems with parameter uncertainty and stochastic communication.The nonlinear system is modeled as T-S fuzzy structure,and the upper and lower membership functions are used to capture the uncertainty of parameters effectively.By making full use of LMIs and free weighting matrices,the sampled-data controller is designed to keep the fuzzy closed-loop system asymptotically stable and satisfy the H_∞performance index.Taking the inverted pendulum system as an example,the applicability and superiority of IT2fuzzy sampled-data control design are demonstrated.5.Research on IT2 fuzzy sampled-data optimal control for nonlinear and unreliable systemsThe problem of IT2 fuzzy sampled-data optimal control is studied.Considering the nonlinearity,parameter uncertainty and data loss of the controlled system,IT2 fuzzy system is used to describe it.Based on Lyapunov-Krasovskii stability theory,a superior control scheme based on LMIs is obtained by using the free weighting matrix method.In addition,the IT2 sampled-data fuzzy controller is designed to keep the fuzzy closed-loop system asymptotically stable and meet the optimal control performance index.The effectiveness of the fuzzy control scheme is fully verified by the simulation experiment of inverted pendulum system.更多还原