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基于神经网络与多模型的非线性自适应广义预测解耦控制 总被引:1,自引:0,他引:1
针对一类非线性多变量离散时间动态系统,提出了基于神经网络与多模型的非线性自适应广义预测解耦控制方法.该控制方法由线性鲁棒广义预测解耦控制器和神经网络非线性广义预测解耦控制器以及切换机构组成.线性鲁棒广义预测解耦控制器用于保证闭环系统输入输出信号有界,神经网络非线性广义预测解耦控制器能够改善系统性能.切换策略通过对上述两种控制器的切换,保证系统稳定的同时,改善系统性能.同时本文给出了所提自适应解耦控制方法的稳定性和收敛性分析.最后,通过仿真实例验证了该方法的有效性. 相似文献
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针对一类非线性多变量离散时间动态系统,提出了基于神经网络与多模型的非线性自适应广义预测解耦控制方法.该控制方法由线性鲁棒广义预测解耦控制器和神经网络非线性广义预测解耦控制器以及切换机构组成.线性鲁棒广义预测解耦控制器用于保证闭环系统输入输出信号有界,神经网络非线性广义预测解耦控制器能够改善系统性能.切换策略通过对上述两种控制器的切换,保证系统稳定的同时,改善系统性能.同时本文给出了所提自适应解耦控制方法的稳定性和收敛性分析.最后,通过仿真实例验证了该方法的有效性. 相似文献
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提出了一种低阶鲁棒解耦控制器设计方法,能妥善处理多变量反馈系统的耦合性和方
向性.整个设计过程分两步完成:先将闭环系统的鲁棒性能要求转化为关于控制器参数的约束,
然后设计控制器逼近约束条件,最终得到低阶控制器.仿真结果表明,基于本方法的控制器,其
鲁棒性能接近μ-最优控制器,而远优于内模控制器. 相似文献
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基于互质因子摄动的反馈系统的鲁棒稳定性 总被引:3,自引:0,他引:3
考虑对象和控制器同时具有互质因子摄动时闭环系统的鲁棒稳定性问题,得到了闭环
系统鲁棒稳定的充要条件并给出了鲁棒控制器的优化设计方法. 相似文献
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本文讨论了多变量系统参数摄动下鲁棒观测器-控制器的设计方法,并给出了带观测器-控制器闭环系统的鲁棒稳定条件。 相似文献
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针对一类参数不确定离散时滞广义系统,研究其鲁棒非脆弱H∞状态反馈控制器的设计问题.系统中的不确定项参数与控制器的增益变化同时具有线性分式形式的范数有界.首先,利用Lyapunov函数理论,研究该标称系统的鲁棒H∞控制问题;其次,以线性矩阵不等式(LMI)形式给出该系统的鲁棒非脆弱H∞控制器存在的充分条件及设计方法.该控... 相似文献
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A robust stabilization problem for fuzzy systems is discussed in accordance with the definition of stability in the sense of Lyapunov. We consider two design problems: nonrobust controller design and robust controller design. The former is a design problem for fuzzy systems with no premise parameter uncertainty. The latter is a design problem for fuzzy systems with premise parameter uncertainty. To realize two design problems, we derive four stability conditions from a basic stability condition proposed by Tanaka and Sugeno: nonrobust condition, weak nonrobust condition, robust condition, and weak robust condition. We introduce concept of robust stability for fuzzy control systems with premise parameter uncertainty from the weak robust condition. To introduce robust stability, admissible region and variation region, which correspond to stability margin in the ordinary control theory, are defined. Furthermore, we develop a control system for backing up a computer simulated truck-trailer which is nonlinear and unstable. By approximating the truck-trailer by a fuzzy system with premise parameter uncertainty and by using concept of robust stability, we design a fuzzy controller which guarantees stability of the control system under a condition. The simulation results show that the designed fuzzy controller smoothly achieves backing up control of the truck-trailer from all initial positions 相似文献
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Output containment problem for high-order nonlinear time-invariant multi-agent systems in directed networks is investigated in this paper. The output is related with the observation matrix. The dimensions of observation matrix are extended so that it is non-singular. Then the containment problem is transformed into stability problem. The model of each agent is constructed by a nominal system combined with uncertainties. A robust controller, which includes a nominal controller and a robust compensator, is proposed to achieve output containment and restrain external uncertainties. The nominal controller is based on the output feedback and the nominal system constructed by the nominal controller contains desired containment properties. The robust compensator design is based on robust signal compensation technology for restraining the effects of external disturbances. A sufficient condition on the output containment is proposed and the containment errors can be made as small as desired with the expected convergence rate. Finally, numerical simulation is presented to demonstrate the effectiveness of the control method. 相似文献
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Coherent H∞ Control for Linear Quantum Systems With Uncertainties in the Interaction Hamiltonian 下载免费PDF全文
This work conducts robust H∞ analysis for a class of quantum systems subject to perturbations in the interaction Hamiltonian. A necessary and sufficient condition for the robustly strict bounded real property of this type of uncertain quantum system is proposed. This paper focuses on the study of coherent robust H∞ controller design for quantum systems with uncertainties in the interaction Hamiltonian. The desired controller is connected with the uncertain quantum system through direct and indirect couplings. A necessary and sufficient condition is provided to build a connection between the robust H∞ control problem and the scaled H∞ control problem. A numerical procedure is provided to obtain coefficients of a coherent controller. An example is presented to illustrate the controller design method. 相似文献
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In this paper, a data-driven control approach is developed by reinforcement learning (RL) to solve the global robust optimal output regulation problem (GROORP) of partially linear systems with both static uncertainties and nonlinear dynamic uncertainties. By developing a proper feedforward controller, the GROORP is converted into a global robust optimal stabilization problem. A robust optimal feedback controller is designed which is able to stabilize the system in the presence of dynamic uncertainties. The closed-loop system is ensured to be input-to-output stable regarding the static uncertainty as the external input. This robust optimal controller is numerically approximated via RL. Nonlinear small-gain theory is applied to show the input-to-output stability for the closed-loop system and thus solves the original GROORP. Simulation results validates the efficacy of the proposed methodology. 相似文献
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一类不确定非线性系统的鲁棒自适应控制 总被引:10,自引:1,他引:9
针对一类具有一般不确定性和未知参数的非线性系统,设计出一种适用于输出跟踪
的鲁棒自适应控制器.该控制器对系统的参数和状态的不确定性具有鲁棒性,能保证闭环系
统的全局稳定性,并解决了ε-跟踪问题.仿真实例表明,所设计的鲁棒自适应控制器具有良好
的跟踪性能. 相似文献
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Chih-Min Lin Chin-Hsu Leng Chun-Fei Hsu Chiu-Hsiung Chen 《Neural computing & applications》2009,18(6):567-575
Linear ultrasonic motor (LUSM) has much merit, such as high precision, fast control dynamics and large driving force, etc.;
however, the dynamic characteristic of LUSM is nonlinear and the precise dynamic model of LUSM is difficult to obtain. To
tackle this problem, this study presents a robust neural network control (RNNC) system for LUSM to track a reference trajectory
with L
2 robust tracking performance. The developed RNNC system is composed of a neural network controller and a robust controller.
The neural network controller is the principal controller used to mimic an ideal controller and the robust controller is adopted
to achieve L
2 robust tracking performance. The developed RNNC system is then applied to control an LUSM. Experimental results show that
the developed RNNC system can achieve favorable tracking performance with unknown of LUSM model. 相似文献
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本文针对动态特性未知的参数摄动系统,研究了多回路鲁棒控制问题.在摄动系统开环稳
定的假设下,证明了控制问题存在解的充分必要条件,并提出了相应的控制器参数在线综合算
法. 相似文献
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基于包含两个二次项的分段Lyapunov函数,研究了线性时变不确定系统的鲁棒控制器设计问题.所考虑的系统由两个矩阵的凸组合构成,通过引入一个附加矩阵,推导出鲁棒控制器存在的充分条件.该控制器的状态反馈增益的求解问题可以转化为一组带有两个比例参数的线性矩阵不等式的凸优化问题.最后的数值示例说明了该设计方法的可行性. 相似文献