基于神经状态空间的非线性系统建模研究

提出了一种基于神经状态空间的非线性系统建模方法.神经状态空间(NNSP)具有系统的拟线性特性,许多线性系统控制器设计方法均可以扩展到NNSP模型.本文采用了增广卡尔曼滤波方法进行神经状态空间的参数辨识,高阶校验模型用于验证非线性系统神经状态空间的模型的有效性.将本法应用于典型的化学过程的建模,结果表明本方法正确有效.     

Almost Disturbance Decoupling for HOFA Nonlinear Systems with Strict-Feedback Form

Journal of Systems Science and Complexity - The article is devoted to the almost disturbance decoupling problem for high-order fully actuated (HOFA) nonlinear systems with strict-feedback form....     

最小相位不确定非线性系统的观测器设计

针对一类系统相对阶小于系统阶数的非线性系统,提出了一种基于输入输出线性化的观测器设计方法。首先考虑了模型已知时的非线性系统,通过微分同胚,将原系统变换为标准型,证明只要系统的零动态是局部指数稳定的,则基于估计误差的非线性动态方程是稳定的,即估计状态收敛到真实状态。然后分析了存在模型不确定性的系统的观测器设计问题,用RBF神经网络逼近不确定性,设计了神经网络加权系数的调整规律和Lyapunov函数,实现了含有不确定性时误差动态方程的渐近稳定性。仿真结果证明了算法的有效性。     

Global Practical Exponential Stabilization for One-Sided Lipschitz Systems with Time Delay

This paper addresses the practical stabilization problem for a class of one-sided Lipschitz nonlinear time delay systems with external disturbances. In case there is no perturbation, the exponential convergence of the observer was confirmed. When external disturbances appear in the system, a separation principle is established, and the authors show that the closed loop system is exponentially practical stable. By choosing a suitable Lyapunov-Krasovskii functional, the authors derive new sufficient conditions to guarantee the exponential stability of the systems. Finally, a physical model is performed to prove the efficiency and applicability of the suggested approach.

     

Design of control invariant sets of planar systems

Control invariant sets play a key role in model predictive control. Using Lyapunov function, a technique is proposed to design control invariant sets of planar systems in a precise form. First, it is designed for a linear system in Brunovsky canonical form. Then, the result is extended to general linear systems. Finally, the nonlinear control systems are considered, and some sufficient conditions and design techniques are also obtained. Numerical examples are presented to illustrate the proposed design methods.     

不确定多变量线性系统的快速收敛滑模控制

讨论了一类不确定多变量线性系统滑模变结构控制的快速收敛问题,提出一种指数型快速终端滑模变结构控制方案。通过非奇异线性变换将不确定系统化为简约标准型,而后设计了非线性指数型快速终端滑模超曲面,给出了滑模面参数矩阵的选择方法。在此基础上设计了变结构控制律,使系统状态在有限时间内到达滑模面上,随后保持在滑模面上并按指数型终端滑模的规律运动,在有限时间内收敛到平衡点。与普通的快速终端滑模相比,系统状态能以更短的时间到达平衡点。该方法具有全局稳定性和鲁棒性,仿真结果证明其有效性。     

基于T-S模型的非线性系统离散时间滑模控制

基于T-S模糊模型,讨论了一类非线性离散时间系统的控制问题。采用T-S模糊模型来描述非线性系统的动态模型,再将非线性系统的全局T-S模糊模型转化为线性不确定系统的模型。这样复杂的非线性系统的稳定问题就转化为线性不确定系统的鲁棒镇定问题。采用离散时间滑模控制方法实现线性不确定系统的鲁棒镇定。利用用线性矩阵不等式技术设计稳定的滑动模面,以降低非匹配不确定对系统的影响。给出了线性矩阵不等式形式的稳定滑动模面存在的充分条件。此外还给出了滑模控制律的设计方法。所给设计方法可保证系统鲁棒镇定,并且在滑动模面附近的抖振可明显减弱。最后,给出了truck-trailer的仿真算例,证明了所给方法的可行性和有效性。     

Conditional Congruence Closure over Uninterpreted and Interpreted Symbols

A framework for generating congruence closure and conditional congruence closure of ground terms over uninterpreted as well as interpreted symbols satisfying various properties is proposed. It is based on some of the key concepts from Kapur’s congruence closure algorithm (RTA97) for ground equations based on introducing new symbols for all nonconstant subterms appearing in the equation set and using ground completion on uninterpreted constants and purified equalities over interpreted symbols belonging to different theories. In the original signature, the resulting rewrite systems may be nonterminating but they still generate canonical forms. A byproduct of this framework is a constant Horn completion algorithm using which ground canonical Horn rewrite systems can be generated for conditional ground theories.

New efficient algorithms for generating congruence closure of conditional and unconditional equations on ground terms over uninterpreted symbols are presented. The complexity of the conditional congruence closure is shown to be O(n*log(n)), which is the same as for unconditional ground equations. The proposed algorithm is motivated by our attempts to generate efficient and succinct interpolants for the quantifier-free theory of equality over uninterpreted function symbols which are often a conjunction of conditional equations and need additional simplification. A completion algorithm to generate a canonical conditional rewrite system from ground conditional equations is also presented. The framework is general and flexible and is used later to develop congruence closure algorithms for cases when function symbols satisfy simple properties such as commutativity, nilpotency, idempotency and identity as well as their combinations. Interesting outcomes include algorithms for canonical rewrite systems for ground equational and conditional theories on uninterpreted and interpreted symbols leading to generation of canonical forms for ground terms, constrained terms and Horn equations.

     

Positive-Controllability,Positive-Near-Controllability,and Canonical Forms of Driftless Discrete-Time Bilinear Systems

Controllable canonical forms play important roles in the analysis and design of control systems. In this paper, a fundamental class of discrete-time bilinear systems are considered. Such systems are of interest since, on one hand, they have the most complete controllability theory. On the other hand, they can be nearly-controllable even if controllability fails. Firstly, controllability of the systems with positive control inputs is studied and necessary and sufficient algebraic criteria for positive-controllability and positive-near-controllability are derived. Then, controllable canonical forms and nearly-controllable canonical forms of the systems are presented, respectively, where the corresponding transformation matrices are also explicitly constructed. Examples are given to demonstrate the effectiveness of the derived controllability criteria and controllable canonical forms.

     

Trajectory Tracking Control of Euler-Lagrange Systems with ISS-Like Robustness to Actuator Noises

This paper studies global robust tracking of uncertain Euler-Lagrange systems with input disturbances. The authors develop a robust regulation-based approach for the problem. Specifically, by introducing a novel nonlinear internal model, the authors solve global asymptotic trajectory tracking with disturbance rejection of multiple step/sinusoidal signals with unknown amplitudes, frequencies, and phases. Moreover, the authors show that a robustness property to actuator noises can be guaranteed in a sense of strong integral input-to-state stability (iISS). That is, the closed-loop system is not only iISS but also input-to-state stable (ISS) to small magnitude actuator noises. Furthermore, the authors explore a by-product overparametrized linear regression estimation, coming up with robust estimation of the unknown parameters. Finally, the authors present several numerical examples to illustrate the theoretical results.

     

一个典型C~3I系统的微分方程作战模型的建立

本文针对目前C~3I系统建模研究遇到的难题:如何把C~3I系统的组成内容与它所处的战争环境结合起来,运用复杂系统的一些建模方法、基于问题导向的原则,提出了一套战争环境下C~3I系统建模的规范化建模方法,使C~3I系统与军方常用于描述作战的Lanchester型格斗方程有机地结合起来,形成C~3I系统的作战方程。文中以一个典型的防空作战的C~3I想定进行了具体的计算,建立了该想定的微分方程模型。结果表明,这种方法解决了C~3I系统与Lanchester方程的结合问题,从而使C~3I系统本身的各个组成部分能在模型中与作战环境有机地结合起来。     

New Results on H∞ Control for Nonlinear Conformable Fractional Order Systems

This paper deals with H_∞ control problem for nonlinear conformable fractional order systems. The authors first derive new sufficient condition for exponential stability of nonlinear conformable fractional order systems based on Lyapunov-like function method for conformable fractional order systems and linear matrix inequalities(LMIs) approach. Then, by introducing a new concepts of H_∞ control problem for nonlinear conformable fractional order systems, the authors study H_∞ performance analysis and H_∞ state feedback controller design problems for the considered systems. In terms of LMIs, a sufficient condition is proposed to ensure the nonlinear conformable fractional order systems are not only exponentially stable, but also satisfy H_∞ performance γ. An explicit expression for state feedback controllers is also designed to make the closed-loop system is exponentially stable with H_∞performance γ. Finally, numerical examples are given to illustrate the validity and effectiveness of the proposed results.     

Constrained predictive control based on T-S fuzzy model for nonlinear systems

A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.     

DESIGN OF NONLINEAR OBSERVERS

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<Emphasis Type="Italic">H</Emphasis><Subscript>∞</Subscript> control for nonlinear stochastic Markov systems with time-delay and multiplicative noise

This paper is concerned with the H_∞ control problem for a class of nonlinear stochastic Markov jump systems with time-delay and system state-, control input- and external disturbancedependent noise. Firstly, by solving a set of Hamilton-Jacobi inequalities (HJIs), the exponential mean square H_∞ controller design of delayed nonlinear stochastic Markov systems is presented. Secondly, by using fuzzy T-S model approach, the H_∞ controller can be designed via solving a set of linear matrix inequalities (LMIs) instead of HJIs. Finally, two numerical examples are provided to show the effectiveness of the proposed design methods.     

On PID Control Theory for Nonaffine Uncertain Stochastic Systems

PID(proportional-integral-derivative) control is recognized to be the most widely and successfully employed control strategy by far. However, there are limited theoretical investigations explaining the rationale why PID can work so well when dealing with nonlinear uncertain systems.This paper continues the previous researches towards establishing a theoretical foundation of PID control, by studying the regulation problem of PID control for nonaffine uncertain nonlinear stochastic systems. To be ...     

Robust Feedback Controller for Exponential Stability of Nonlinear Systems with Mismatched Uncertainties

The robust stabilization of nonlinear systems with mismatched uncertainties is investigated. Based on the stability of the nominal system, a new approach to synthesizing a class of continuous state feedback controllers for uncertain nonlinear dynamical systems is proposed. By such feedback controllers, the exponential stability of uncertain nonlinear dynamical systems can be guaranteed. The approach can give a clear insight to system analysis. An illustrative example is given to demonstrate the utilization of the approach developed. Simulation results show that the method presented is practical and effective.     

非线性时变系统的部分指数稳定性分析

讨论了非线性时变系统平凡解的部分指数稳定性和全局部分指数稳定性。分别利用数量与向量Lyapunov函数并结合数量与向量比较原理,得到了保证系统平凡解部分指数稳定和全局部分指数稳定的一系列充分条件。作为特殊情形,对于一类定常拟线性系统,在一定的条件下,若其对应的线性系统的平凡解是部分渐近稳定的,利用二次型Lyapunov函数得到了保证拟线性系统的平凡解是全局部分指数稳定的一个代数判据,这些结果在实际应用中具有一定的指导意义。最后用两个数值例子对所得主要结果加以阐明。     

Networked Learning Predictive Control of Nonlinear Cyber-Physical Systems

Cyber-physical systems integrate computing, network and physical environments to make the systems more efficient and cooperative, and have important and extensive application prospects, such as the Internet of things. This paper studies the control problem of nonlinear cyber-physical systems with unknown dynamics and communication delays. A networked learning predictive control scheme is proposed for unknown nonlinear cyber-physical systems. This scheme recursively learns unknown system dynamics, actively compensates for communication delays and accurately tracks a desired reference. Learning multi-step predictors are presented to predict various step ahead outputs of the unknown nonlinear cyber-physical systems. The optimal design of controllers minimises a performance cost function which measures the tracking error predictions and control input increment predictions. The system analysis leads to the stability criteria of closed-loop nonlinear cyber-physical systems employing the networked learning predictive control scheme. An example illustrates the outcomes of the proposed scheme.