共查询到20条相似文献，搜索用时 437 毫秒
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针对非线性,不确定性的一级倒立摆系统,本文提出了基于切换模糊化的自适应模糊滑模控制器,通过自适应模糊控制方法,将滑模控制器中的切换项进行模糊逼近,可将切换项连续化,削弱了滑模控制的抖振现象。仿真结果证明,本控制系统有较强的鲁棒性和自适应跟踪能力。 相似文献
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随机控制是控制理论与应用的一个重要分支。由于大量实际系统存在非高斯或非线性干扰信号,针对这类系统提出了输出密度函数形状控制方法,以输出概率密度函数作为研究和控制对象,系统地分析多种建模和控制方法。本文围绕输出PDF控制,综述了其控制原理;深入梳理了四种利用B样条模型逼近输出概率密度函数的建模方法以及输出PDF模型建立之后,实现对输出PDF形状完全跟踪的不同跟踪控制算法;最后,指出随机分布控制中存在的问题。 相似文献
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针对一类不确定非线性时滞系统,提出了一种具有确定逼近域的自适应模糊控制器的设计方案。在动态面控制（DSC）的基础上,通过时滞代换技巧,使得自适应模糊逼近器的输入为参考信号,从而可以明确定义逼近域,同时可以处理系统中完全未知的时滞信号。基于Lyapunov-Krasovskii范函,证明闭环系统所有信号为半全局一致有界的,并且跟踪误差可以收敛到原点附件的一个小邻域内。仿真结果进一步说明了该方法的有效性。 相似文献
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针对自由漂浮状态的空间机器人模型不确定性及其动力传动机构的摩擦死区非线性,将一种自适应模糊小脑模型关联控制( FCMAC)补偿策略用于轨迹跟踪及补偿问题.利用模糊神经网络并引入GL矩阵及其乘法算子“.”分别对执行机构中的摩擦死区及系统模型不确定部分进行自适应补偿,其补偿误差及外界扰动通过滑模控制器来消除.基于Lyapunov理论证明了闭环系统跟踪误差的有界性.仿真表明控制器可以达到较高精度,且能满足实时性要求. 相似文献
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混沌是非线性系统的固有现象,电力系统是典型的非线性系统。针对周期性负荷扰动下电力系统中出现的混沌,提出了一种模糊滑模控制方法,设计了模糊滑模控制器,从理论上证明了控制器可以快速到达切换面。在该控制器的作用下使系统输出渐进跟踪参考轨迹,用模糊控制规则来抑制常规滑模控制器中的高频抖振。仿真结果表明,所设计的模糊滑模控制器能够有效抑制电力系统的混沌振荡。 相似文献
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《科技通报》2015,(10)
研究非线性系统的鲁棒性,在大扰动条件下,提高系统的稳定控制性能。传统的控制方法采用PID神经网络控制,在参数自适应过程中产生控制偏差。提出一种基于单神经元纠偏控制的非线性系统鲁棒性改进方法。控制结构是一个三层前向神经元网络,采用单神经元纠偏控制,自适应调节神经元输入输出层权重,给定模型的不确定性分为参数的不确定性和未建模的动态特性不确定性,由此得到偏移控制非线性小扰动方程,进行控制系统鲁棒性和稳健性证明。仿真结果表明,采用该算法实现对非线性系统的控制,自适应调节时间短,超调量小,纠偏性能较好,自适应跟踪控制性能优越,误差减少,控制精度较高,鲁棒性较优。 相似文献
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本文以两轮自平衡小车为研究对象,首先选用合适状态变量,运用Lagrange建模理论,基于广义坐标系下非完整动力学Routh方程建立了系统的多输入多输出非线性动力学模型;分析了模糊PID方法的平衡控制。并通过实验对控制效果进行了验证。 相似文献
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《Journal of The Franklin Institute》2022,359(1):371-391
This paper addresses the adaptive fuzzy event-triggered control (ETC) problem for a class of nonlinear uncertain systems with unknown nonlinear functions. A novel ETC approach that exhibits a combinational triggering (CT) behavior is proposed to update the controller and fuzzy weight vectors, achieving the non-periodic control input signals for nonlinear systems. A CT-based fuzzy adaptive observer is firstly constructed to estimate the unmeasurable states. Based on this, an output feedback ETC is proposed following the backstepping and error transformation methods, which ensures the prescribed dynamic tracking (PDT) performance. The PDT performance indicates that the transient bounds, over-shooting and ultimate values of tracking errors are fully determined by the control parameters and functions chosen by users. The closed-loop stability is guaranteed under the framework of impulsive dynamic system. Besides, the Zeno phenomenon is circumvented. The theoretical analysis indicates that the proposed scheme guarantees control performance while considerably reducing the communication resource utilization and controller updating frequency. Finally, the numerical simulations are conducted to verify the theoretical findings. 相似文献
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《Journal of The Franklin Institute》2022,359(17):9591-9617
In this paper, an adaptive finite-time funnel control for non-affine strict-feedback nonlinear systems preceded by unknown non-smooth input nonlinearities is proposed. The input nonlinearities include backlash-like hysteresis and dead-zone. Unknown nonlinear functions are handled using fuzzy logic systems (FLS), based on the universal approximation theorem. An improved funnel error surface is utilized to guarantee the steady-state and transient predetermined performances while the differentiability problem in the controller design is averted. Using the Lyapunov approach, all the adaptive laws are extracted. In addition, an adaptive continuous robust term is added to the control input to relax the assumption of knowing the bounds of uncertainties. All the signals in the closed-loop system are shown to be semi-globally practically finite-time bounded with predetermined performance for output tracking error. Finally, comparative numerical and practical examples are provided to authenticate the efficacy and applicability of the proposed scheme. 相似文献
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《Journal of The Franklin Institute》2021,358(15):7309-7332
The current paper addresses the fuzzy adaptive tracking control via output feedback for single-input single-output (SISO) nonlinear systems in strict-feedback form. Under the situation of system states being unavailable, the system output is used to set up the state observer to estimate the real system states. Furthermore, the estimation states are employed to design controller. During the control design process, fuzzy logic systems (FLSs) are used to model the unknown nonlinearities. A novel observer-based finite-time tracking control scheme is proposed via fuzzy adaptive backstepping and barrier Lyapunov function approach. The suggested fuzzy adaptive output feedback controller can force the output tracking error to meet the pre-specified accuracy in a fixed time. Meanwhile, all the closed-loop variables are bounded. Compared to some existing finite-time output feedback control schemes, the developed control strategy guarantees that the settling time and the error accuracy are independent of the uncertainties and can be specified by the designer. At last, the effectiveness and feasibility of the proposed control scheme are demonstrated by two simulation examples. 相似文献
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《Journal of The Franklin Institute》2022,359(1):392-414
The problem of decentralized adaptive control is investigated for a class of large-scale nonstrict-feedback nonlinear systems subject to dynamic interaction and unmeasurable states, where the dynamic interaction is related to both input and output items. First, the fuzzy logic system is utilized to tackle unknown nonlinear function with nonstrict-feedback structure. Then, by combining adaptive and backstepping technology, the proper output feedback controller is designed. Meanwhile, a fuzzy state observer is proposed to estimate the unmeasurable states. The proposed controller could guarantee that all the signals of the resulting closed-loop systems are bounded. Finally, the applicability of the proposed controller is well carried out by a simulation example. 相似文献
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Shigen Gao Hairong Dong Bin Ning Hongwei Wang 《Journal of The Franklin Institute》2018,355(13):5452-5474
In this paper, a novel error-driven nonlinear feedback technique is designed for partially constrained errors fuzzy adaptive observer-based dynamic surface control of a class of multiple-input-multiple-output nonlinear systems in the presence of uncertainties and interconnections. There is no requirements that the states are available for the controller design by constructing fuzzy adaptive observer, which can online identify the unmeasurable states using available output information only. By transforming partial tracking errors into new error variables, partially constrained tracking errors can be guaranteed to be confined in pre-specified performance regions. The feature of the error-driven nonlinear feedback technique is that the feedback gain self-adjusts with varying tracking errors, which prevents high-gain chattering with large errors and guarantees disturbance attenuation with small errors. Based on a new non-quadratic Lyapunov function, it is proved that the signals in the resulted closed-loop system are kept bounded. Simulation and comparative results are given to demonstrate the effectiveness of the proposed method. 相似文献
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The main contribution of this paper is to develop an adaptive output-feedback control approach for a class of uncertain nonlinear systems with unknown time-varying delays in the pure-feedback form. Both the non-affine nonlinear functions and the unknown time-varying delayed functions related to all state variables are considered. These conditions make the controller design difficult and challenging because the output-feedback controller should be designed using only the output information. In order to overcome these conditions, we design an observer-based adaptive dynamic surface controller where the time-delay effects are compensated by using appropriate Lyapunov–Krasovskii functionals and the function approximation technique using neural networks. A first-order filter is added to the control input to avoid the algebraic loop problem caused by the non-affine structure. It is proved that all the signals in the closed-loop system are semi-globally uniformly bounded and the tracking error converges to an adjustable neighborhood of the origin. 相似文献
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This paper investigates the adaptive fuzzy control design problem of multi-input and multi-output (MIMO) non-strict feedback nonlinear systems. The considered control systems contain unknown control directions and dead zones. Fuzzy logic systems (FLSs) are utilized to approximate the unknown nonlinear functions, and the state observers are designed to estimate immeasurable states. By constructing a dead zone compensator and introducing a Nussbaum gain function into the backstepping technique, an adaptive fuzzy output feedback control method is developed. The proposed adaptive fuzzy controller is proved to guarantee the semi-globally uniformly ultimately bounded (SGUUB) of the closed-loop system, and can solve the control design problems of unmeasured states, unknown control directions and dead zones. The simulation results are given to demonstrate the effectiveness of the proposed control method. 相似文献
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《Journal of The Franklin Institute》2022,359(15):7818-7846
In this study, the problem of observer-based control for a class of nonlinear systems using Takagi-Sugeno (T-S) fuzzy models is investigated. The observer-based model predictive event-triggered fuzzy reset controller is constructed by a T-S fuzzy state observer, an event-triggered fuzzy reset controller, and a model predictive mechanism. First, the proposed controller utilizes the T-S fuzzy model and is constructed based on state observations and discrete sampling output, which can greatly reduce the occupation of communication resources. Then, the model predictive strategy for reset law design is designed in this paper. With a reasonable reset of the controller state at certain instants, the performance of the reset control systems is improved. Finally, the validity of the proposed method is illustrated by simulation. The merits of the proposed controller in improving transient performance and reducing the communication occupation are demonstrated by comparing its results with the output feedback fuzzy controller and the first-order fuzzy reset controller. 相似文献
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In this paper, we develop two new model reference adaptive control (MRAC) schemes for a class of nonlinear dynamic systems that is robust with respect to an uncertain state (output) dependent nonlinear perturbations and/or external disturbances with unknown bounds. The design is based on a controller parametrization with an adaptive integral action. Two types of adaptive controllers are considered—the state feedback controller with a plant parameter identifier, and the output feedback controller with a linear observer. 相似文献
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《Journal of The Franklin Institute》2022,359(16):8669-8686
This paper studies a finite-time adaptive fuzzy control approach for a continuous stirred tank reactor (CSTR) with percent conversion constraint and uncertainties. This system is seen as a class of non-affine systems, and the system is resolved by the mean value theorem. Integral barrier Lyapunov functions (iBLFs) are used to handle output constraint in the design process of the finite-time adaptive controller. In order to calculate the time derivative of the virtual controller, a finite-time convergent differentiator (FTCD) is proposed, which can avert the issue of “explosion of complexity” in the backstepping design. Based on the finite time stability theory, the proposed approach not only ensures the closed-loop stability, but also guarantees tracking performance in a finite time. Finally, the simulation results on CSTR are showed to reveal the availability of the developed control scheme. 相似文献