A systematic design of emulators for multivariable non square and nonlinear systems

In this paper, multimodel and neural emulators are proposed for uncoupled multivariable nonlinear plants with unknown dynamics. The contributions of this paper are to extend the emulators to multivariable non square systems and to propose a systematic method to compute the multimodel synthesis parameters. The effectiveness of the proposed emulators is shown through two simulation examples. The obtained results are very satisfactory, they illustrate the performance of both emulators and show the advantages of the multimodel emulator relatively to the neural one.     

一类3阶非线性系统的非奇异终端滑模控制

针对传统非奇异终端滑模控制方法不适用于3阶系统的问题,提出一类具有不确定和外干扰的3阶非线性系统的新型非奇异终端滑模控制方法.该方案首先结合backstepping控制中的动态面方法和传统2阶非奇异终端滑模控制构造非奇异3阶终端滑模面,首次提出采用高阶滑模微分器估计值代替控制器中的负指数项.采用非线性干扰观测器任意精度地估计不确定和干扰,设计控制器中的补偿项.采用终端吸引子函数做趋近律避免抖振的同时能保证有限时间趋近滑模面.基于有限时间稳定李雅普诺夫定理证明了被控状态将在有限时间内收敛到任意小的闭球内.所提出方案快于传统的递阶线性滑模控制和其他非奇异终端滑模控制.仿真中与其他滑模控制方案对比,总误差减小18%以上,超调及收敛时间也显著下降.     

有限时间收敛的Terminal滑模控制设计

讨论了一类SISO非线性系统的滑模变结构控制有限时间收敛问题,提出一种新的Terminal滑动模态及相应控制的设计方法,可用于带有外部扰动的二阶非线性系统。研究结果表明,系统状态在滑模面上能以较快的速度达到平衡点,在滑模面上到达平衡点的时间均是有限的,并且与普通的Terminal滑模相比,在滑模面上能以更短的时间到达平衡点。仿真结果表明了所提方法的有效性。     

非线性不确定系统的非奇异快速终端滑模控制

针对存在非匹配干扰的非线性系统,设计了一种基于干扰观测器和反步法的非奇异快速终端滑模控制.引入非线性干扰观测器估计系统的不确定性,利用反步的思想处理高阶非线性系统,从而可以将非线性干扰观测器估计的干扰值引入反步法的虚拟控制量中,同时设计一种新颖的非奇异快速终端滑模控制律保证系统的收敛速度和精度.利用Lyapunov函数从理论上证明了所设计的控制器可以保证闭环系统的有限时间收敛.最后通过数值仿真验证了所设计的控制方法的有效性.     

一种固定时间收敛模型参考终端滑模控制方法

针对一类具有模型不确定性和外部扰动的时变非线性系统, 基于模型参考控制方法, 设计了具有固定时间收敛特性的终端滑模控制器. 首先, 提出一种带有输入饱和限幅和补偿信号滤波的模型参考控制结构; 然后针对广义误差信号, 采用新型终端滑模面设计了补偿控制器, 较好地平衡靠近和远离平衡点的收敛速度. 基于李雅普诺夫方法证明了闭环系统的稳定性和固定时间收敛特性, 并给出了收敛时间上界. 最后将该方法应用到含有极限环的非线性系统跟踪控制中, 仿真结果验证了该方法的有效性.     

Fixed-time sliding mode observer-based controller for a class of uncertain nonlinear double integrator systems

This paper investigates a fixed-time convergence issue using the sliding mode observer-based controller for a class of uncertain nonlinear double integrator systems. This observer-based controller is designed assuming that only the first state measurement is available and there is no information about external disturbances and modeling uncertainties. A new form of sliding mode observer in combination with a sliding mode controller is designed to estimate unmeasured state and unknown disturbances and uncertainties as well as provide the estimated data in the control law. A novel form of sliding surfaces for the robust observer-based controller is proposed for which fixed-time convergence is guaranteed to achieve trajectory tracking. In the proposed fixed-time scheme, the bound on the settling time is user-defined using design parameters regardless of the system's initial conditions. The control law and observer law are designed such that the chattering issue is alleviated in the control signal. The stability analysis of the closed-loop system using the observer-based controller is established via the Lyapunov theory. The validity of the controller design is tested by applying and simulating an example of a robot manipulator in Simulink/MATLAB. The superiority of the proposed method is demonstrated by comparing it with two other methods from the relevant literature.     

非线性不确定系统的鲁棒滑模观测器设计

对非线性不确定性系统,提出一种鲁棒滑模观测器.所提出的鲁棒滑模观测器通过滑模与相应的控制策略来实现,设计参数的选取不需要求解大量方程,同时能保证对系统的非线性不确定项具有鲁棒性.通过设计滑模,可以调整观测器跟踪系统状态的收敛速度,使状态估计达到预期的指标.仿真结果验证了提出方法的有效性.     

Finite time convergent control using terminal sliding mode

A method for terminal sliding mode control design is discussed. As we know, one of the strong points of terminal sliding mode control is its finite-time convergence to a given equilibrium of the system under consideration, which may be useful in specific applications. The proposed method, different from many existing terminal sliding model control design methods, is studied, and then feedback laws are designed for a class of nonlinear systems, along with illustrative examples.     

新型有限时间收敛滑模扩张状态观测器研究

针对一类具有量测噪声的非线性不确定系统,设计了基于新型滑模扩张状态观测器的Terminal滑模控制方案．首先对系统进行两次状态扩张,然后设计一种新型滑模扩张状态观测器,通过采用特殊的滑模面保证观测误差在有限时间内收敛到零．在此基础上,设计Terminal滑模控制器,使系统状态也能在有限时间内收敛到零．严格的理论证明和仿真结果均证明了所设计新型滑模观测器及闭环控制方案的有效性和快速性．     

Passivity‐based sliding mode controller/observer for second‐order nonlinear systems

A passivity‐based sliding mode control for a class of second‐order nonlinear systems with matched disturbances is proposed in this paper. Firstly, a nonlinear sliding surface is designed using feedback passification, in which the passivity is employed to guarantee the closed‐loop system's stability. The passivity‐based controller comprising a discontinuous term guarantees globally asymptotical convergence to the sliding surface. A sliding mode‐based control law that satisfies the reaching and sliding condition is also developed. Moreover, the passivity‐based sliding mode observer is also developed to effectively estimate the system states. Compared with conventional sliding mode control, the proposed control scheme has a shorter reaching time; and hence, the system performance is less affected by disturbances, thus eliminating the need to increase the control input gain. Finally, simulation results demonstrate the validity of the proposed method.     

Terminal sliding mode observers for a class of nonlinear systems

This paper proposes a terminal sliding mode observer for a class of nonlinear systems to achieve finite time convergence for all error states. Compared to standard sliding mode observers which only enable finite time convergence of the output error, the observer in this paper makes use of fractional powers to reduce other non-output errors to zero in finite time. A 2-degree-of-freedom robotic manipulator is used to demonstrate the effectiveness of the proposed observer.     

一类迟滞模型的动态滑模跟踪控制器设计

针对一种典型的动态迟滞模型。提出一种基于动态滑模原理的跟踪控制器．通过构造辅助的滑模变量来实现动态滑模控制的两阶段收敛．在保证系统状态有限时间收敛的前提下．求取了滑模控制量．并给出了控制器参数所满足的条件．仿真实验表明。该滑模迟滞补偿器能有效地补偿压电陶瓷等对象所表现出的迟滞特性．     

Adaptive sliding mode controller design based on T-S fuzzy system models

An adaptive sliding mode control (ASMC) technique based on T-S fuzzy system models is proposed in this paper for a class of perturbed nonlinear MIMO dynamic systems in order to solve tracking problems. A T-S fuzzy model is firstly formed by utilizing fuzzy theorem to amalgamate a set of linearized dynamic equations. The adaptive sliding mode controller is then designed based on this fuzzy model with perturbations. The proposed control scheme can drive the dynamics of controlled system into a designated sliding surface in finite time, and guarantee the property of asymptotical stability. It is also shown that the information of upper bound of modeling errors as well as perturbations, except the information of upper bound of input uncertainty, is not required when using the proposed controller.     

带有非线性不确定奇异系统的积分滑模控制

针对一类含有非线性不确定的奇异系统, 提出了一种面向性能的鲁棒控制器. 控制器由3部分组成: 积分滑模控制、附加的非线性控制及复合非线性反馈控制. 积分滑模控制可将匹配不确定完全抵消并使系统轨迹进入理想滑模; 附加的非线性控制用来抑制理想滑动模态上非匹配不确定对系统稳定性和性能的影响; 复合非线性反馈控制则保证闭环系统输出按性能要求渐近地跟踪参考输入信号. 最后通过算例说明所提算法的有效性.     

具有未知参数的混沌系统的有限时间滑模同步控制

针对带有未知参数和非线性输入的两个不同的混沌系统之间的同步问题进行研究. 提出一个相比于传统滑模面具有更快收敛速度的终端滑模面, 并结合自适应控制理论和滑模控制理论, 设计一个自适应滑模控制律, 使同步误差在有限时间内收敛到滑模面, 并沿滑模面在有限时间内收敛到零点, 最终实现两个不同的混沌系统之间的同步. 最后, 以带有不确定性和外部扰动的Lorenz 系统和Liu 系统为例进行数值仿真, 仿真结果表明, 同步误差在有限时间内收敛到零点, 从而验证了所设计控制律的有效性和可行性.     

Derivative and integral terminal sliding mode control for a class of MIMO nonlinear systems

This paper presents derivative and integral terminal sliding mode control (TSMC) for a class of MIMO nonlinear systems in a unified viewpoint. First, integral TSMC is developed for robust output tracking of uncertain relative-degree-one systems by introducing sign and fractional integral terminal sliding modes. Next, by combining derivative and integral terminal sliding modes in a recursive structure, two derivative-integral terminal sliding mode control (DI-TMSC) methods are proposed to achieve exact or approximate finite-time convergence for the output tracking of higher order nonlinear systems. Different from traditional TSMC, this paper accomplishes finite convergence time for more general high-order MIMO systems and avoids the singular problem in the controller design. Furthermore, the control system is forced to start on the terminal sliding hyperplane, so that the reaching time of the sliding modes is eliminated. In other words, the transient response is improved under more relaxed stability conditions. Finally, several numerical simulations and experiments show the expected control performance.     

Optimal Systematic Determination of Models' Base for Multimodel Representation: Real Time Application

The multimodel approach is a powerful and practical tool to deal with analysis, modeling, observation, emulation and control of complex systems. In the modeling framework, we propose in this paper a new method for optimal systematic determination of models base for multimodel representation. This method is based on the classification of data set picked out of the considered system. The obtained cluster centers are exploited to provide the weighting functions and to deduce the corresponding dispersions and their models base. A simulation example and an experimental validation on a semi-batch reactor are presented to evaluate the effectiveness of the proposed method.     

A new approach for multimodel identification of complex systems based on both neural and fuzzy clustering algorithms

The multimodel approach was recently developed to deal with the issues of complex systems modeling and control. Despite its success in different fields, it is still faced with several design problems, in particular the determination of the number and parameters of the different models representative of the system as well as the choice of the adequate method of validities computation used for multimodel output deduction.In this paper, a new approach for complex systems modeling based on both neural and fuzzy clustering algorithms is proposed, which aims to derive different models describing the system in the whole operating domain. The implementation of this approach requires two main steps. The first step consists in determining the structure of the model-base. For this, the number of models must be firstly worked out by using a neural network and a Rival Penalized Competitive Learning (RPCL). The different operating clusters are then selected referring to two different clustering algorithms (K-means and fuzzy K-means). The second step is a parametric identification of the different models in the base by using the clustering results for model orders and parameters estimation. This step is ended in a validation procedure which aims to confirm the efficiency of the proposed modeling by using the adequate method of validity computation. The proposed approach is implemented and tested with two nonlinear systems. The obtained results turn out to be satisfactory and show a good precision, which is strongly related to the dispersion of the data and the related clustering method.     

Robotic Manipulators State Observation Via One-Time Gain Switching

High-gain Luenberger-like state observation would provide the best possible tracking error of nonlinear systems at the expense of higher transient variance and slower convergence to the real state. Conversely, low-gain Luenberger-like observation usually provides lower transient variance of the error system, but might lead to nonzero or nonconvergent steady tracking error. This paper presents new switching-gain observer designs that capitalize on the benefits of low-gain, high-gain, and sliding mode observations. Switching and non-switching observer designs are both considered. Since adaptive observers are often of complex structures and might be difficult to implement, a simpler adaptation form is presented using one-time switching between two predetermined solutions. A nonlinear coordinate transformation is applied to obtain a linear observable system with nonlinear perturbation terms characterized by a Lipschitz constant and/or a finite bound on the norm. Sufficient conditions are derived for the existence of sliding mode, asymptotic stability of the error system, and the independence of the reconstruction error system from the perturbation inputs during the sliding mode. The new observer designs are applied to flexible-joint manipulators in order to explore their performance capabilities. The switching-gain observer was shown to be a reasonable compromise that is easy to be implemented.     

一种基于指数趋近律的非线性系统变结构轨迹跟踪控制新方法

针对多输入多输出二阶不确定非线性机械系统中轨迹跟踪控制的问题,提出一种新的基于指数趋近律的滑模变结构控制方法,用于提高系统的平稳性和快速性。在滑模变结构控制器设计过程中采用一种新的指数趋近律以改进闭环系统的暂态和稳态响应性能,使系统跟踪误差收敛速度加快,特别是减少轨迹跟踪误差到达滑模面的时间,同时提高了系统轨迹跟踪过程的平稳性。通过采用边界层方法消除滑模控制输入抖振问题,避免控制过程中执行器的频繁切换,进一步提高所提出滑模控制器在实际系统中的实用性。基于李雅普诺夫稳定性理论证明了闭环系统的稳定性和跟踪误差的收敛性。数值仿真验证了所提出的控制方法的有效性。