共查询到14条相似文献,搜索用时 218 毫秒
1.
2.
3.
4.
针对非线性时变时延系统,采用输入时延和自由权重矩阵方法研究模糊采样最优控制问题.应用T-S模糊系统表征非线性系统,控制器是零阶保持采样信号.由线性矩阵不等式给出最优控制准则,所设计的模糊采样控制器在闭环系统渐近稳定意义下可保证期望最优控制性能.最后,通过卡车拖车系统实验验证模糊采样控制设计方案的可行性. 相似文献
5.
用T-S模糊系统来逼近非线性系统,它的IF-THEN规则后件由线性状态空间子系统构成,进而可以应用模糊系统的控制理论求得模糊控制器,用此非线性控制器来控制非线性系统,以求良好的控制效果;将模糊控制技术应用于混沌控制中,可以克服反馈线性化等传统方法对参数完全精确已知的限制;模糊规则后件部分以局部线性方程形式给出的T-S模糊模型可以通过调整相关参数很好地逼近混沌系统,基于该模型采用平行分散补偿技术设计出具有相同规则数目的模糊控制器,控制器所有参数可以通过求解一组线性矩阵不等式一次性得到。仿真结果验证了该方法的有效性。 相似文献
6.
7.
面对复杂工业过程控制的需求, 设计一种结合数据信息的特殊模型结构, 在保证控制系统有效性的前提下通过模型的结构来简化控制器的求解是亟待解决的问题. 为此, 本文提出一种基于多信号源的神经模糊Hammerstein-Wiener模型, 突破传统的迭代分离方法, 通过组合式多信号实现Hammerstein-Wiener模型中神经模糊非线性环节和线性环节的分离, 同时设计了神经模糊模型参数的非迭代优化算法, 将研究结果拓广到分段非线性系统,改善了模型的适用范围. 该算法保证了模型的预测精度,具有逼近较强非线性过程的能力. 在此基础上设计了基于神经模糊Hammerstein-Wiener模型的控制系统, 利用模型的特殊结构将非线性系统的控制问题简化为线性系统的控制问题, 采用简单的PID控制器便能达到较好的控制效果.仿真结果验证了上述方法的有效性. 相似文献
8.
9.
针对一般形式的非线性系统,提出一种基于模糊双曲模型(FHM)的积分滑模控制器设计方法.利用模糊双曲模型来表述这类连续非线性系统.构建出积分滑模面,利用线性矩阵不等式(LMI)方法得到滑模动态渐近稳定的充分条件.设计了积分滑模控制器,保证了系统的状态轨迹能够在有限时间内到达滑模面上并且保持在它上面运动.仿真结果表明了该方法的有效性. 相似文献
10.
研究了一类非线性系统的模糊变结构控制问题,并给出了稳定性证明。通过将非线性系统化为多个精确T—S模型来建立非线性系统精确的T—S模糊模型,将模糊理论与成熟的线性变结构控制理论相结合设计一种模糊变结构控制器,用Lyapunov稳定性理论证明该控制器能确保模糊动态模型全局渐近稳定,从而使非线性系统稳定。仿真结果表明了该设计方法的有效性。 相似文献
11.
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
12.
In this paper, a new intelligent robot motion control architecture – a highly accurate model-free fuzzy motion control- is proposed in order to achieve improved robot motion accuracy and dynamic performance. Its architecture combines a Mamdani fuzzy proportional (P) and a conventional integral (I) plus derivative (D) controller for the feedback part of the system, and a Takagi-Sugeno-Kang fuzzy controller for the feed-forward, nonlinear part. The fuzzy P + ID controller improves the performance of the nonlinear system, and the TSK fuzzy controller uses a TSK fuzzy inference system based on extended subtractive- clustering method which integrates information on joint angular displacement, velocity and acceleration for torque identification. The advantage of this kind of model-free control is that it uses the information directly from the input/output of the nonlinear system, without any complex robot model computation, in order to decrease the control system’s sensitivity to any dynamical uncertainty. Furthermore, parametric search for clustering parameters in extended subtractive clustering secures the high accuracy of the system identification. Consequently, this proposed model-free fuzzy motion control benefits from the advantages of two kinds of fuzzy system. It not only incorporates flexible design, good performance and simple conception but also ensures precise motion control and great robustness. Comparisons with other intelligent models and results from numerical studies on a 4-bar planar parallel mechanism show the effectiveness and competitiveness of the proposed control. 相似文献
13.
14.
针对Chua混沌系统这一复杂的非线性系统给出一种基于T-S模型的模糊变结构控制律设计。首先采用T-S模糊动态模型描述非线性系统,得到混沌系统的全局模糊模型;然后采用Lyapunov稳定性理论设计出确保模糊动态模型全局渐近稳定的变结构控制器,将模糊控制与成熟的线性变结构控制相结合,来解决非线性系统控制问题。仿真验证了方案的有效性。模糊控制器简单,规则少。 相似文献