Set-point-related indirect iterative learning control for multi-input multi-output systems

A form of iterative learning control (ILC) is used to update the set-point for the local controller. It is referred to as set-point-related (SPR) indirect ILC. SPR indirect ILC has shown excellent performance: as a supervision module for the local controller, ILC can improve the tracking performance of the closed-loop system along the batch direction. In this study, an ILC-based P-type controller is proposed for multi-input multi-output (MIMO) linear batch processes, where a P-type controller is used to design the control signal directly and an ILC module is used to update the set-point for the P-type controller. Under the proposed ILC-based P-type controller, the closed-loop system can be transformed to a 2-dimensional (2D) Roesser s system. Based on the 2D system framework, a sufficient condition for asymptotic stability of the closed-loop system is derived in this paper. In terms of the average tracking error (ATE), the closed-loop control performance under the proposed algorithm can be improved from batch to batch, even though there are repetitive disturbances. A numerical example is used to validate the proposed results.     

Reduction of controller fragility by pole sensitivity minimization

Presents a method for the reduction of controller fragility. The method is based on the sensitivity of closed-loop poles to perturbations in the controller parameters. By means of a state space parameterization of the controller, the closed-loop pole sensitivity can be reduced. A controller fragility measure based on the closed-loop pole sensitivity is proposed. Conditions for the optimal state-space realization of the controller are presented, along with a numerical method for obtaining the solution     

Further results on variable output feedback controllers

Zak and Hui (1993) proposed a sliding mode controller for linear multiple-input-multiple-output (MIMO) systems using static output feedback. The author's previous paper (1996) provides an improvement of the output feedback controller of Zak-Hui for a class of linear single-input-single-output (SISO) systems that eliminated two important limitations: 1) system uncertainties must be bounded by the system output; and 2) a requirement of a matrix inequality. The controller developed previously can guarantee global closed-loop stability. This paper extends the previous results to linear MIMO systems. It is emphasized that the proposed MIMO controller yields global closed-loop stability whereas the one in Zak-Hui can only guarantee local stability. An application of the proposed MIMO controller to an aircraft model is included to show the effectiveness of the method     

A model-free design of reduced-order controllers and application to a DC servomotor

This paper presents a new model-free technique to design fixed-structure controllers for linear unknown systems. In the current control design approaches, measured data are used to first identify a model of the plant, then a controller is designed based on the identified model. Due to errors associated with the identification process, degradation in the controller performance is expected. Hence, we use the measured data to directly design the controller without the need for model identification. Our objective here is to design measurement-based controllers for stable and unstable systems, even when the closed-loop architecture is unknown. This proposed method can be very useful for many industrial applications. The proposed control methodology is a reference model design approach which aims at finding suitable parameter values of a fixed-order controller so that the closed-loop frequency response matches a desired frequency response. This reference model design problem is formulated as a nonlinear programming problem using the concept of bounded error, which can then be solved to find suitable values of the controller parameters. In addition to the well-known advantages of data-based control methods, the main features of our proposed approach are: (1) the error is guaranteed to be bounded, (2) it enables us to avoid issues related to the use of minimization methods, (3) it can be applied to stable and unstable plants and does not require any knowledge about the closed-loop architecture, and (4) the controller structure can be selected a priori, which means that low-order controllers can be designed. The proposed technique is experimentally validated through a real position control problem of a DC servomotor, where the results demonstrate the efficacy of the proposed method.     

广义系统输出反馈严格正实控制器设计

研究连续广义系统的正实控制问题。目的是设计静态输出反馈和动态输出反馈严格正实控制器使得闭环系统容许且扩展严格正实。基于广义系统严格正实引理，利用线性矩阵不等式和广义代数Riccati不等式，给出了广义系统静态输出反馈和动态输出反馈严格正实控制器存在的充要条件及设计方法。对动态输出反馈情形，给出了一个数值算例说明控制器设计方法的有效性及可行性。     

Data-driven asymptotic stabilization for discrete-time nonlinear systems

In this paper, we propose a data-driven feedback controller design method based on Lyapunov approach, which can guarantee the asymptotic stability of the closed-loop and enlarge the estimate of domain of attraction (DOA) for the closed-loop. First, sufficient conditions for a feedback controller asymptotically stabilizing the discrete-time nonlinear plant are proposed. That is, if a feedback controller belongs to an open set consisting of pairs of control input and state, whose elements can make the difference of a control Lyapunov function (CLF) to be negative-definite, then the controller asymptotically stabilizes the plant. Then, for a given CLF candidate, an algorithm, to estimate the open set only using data, is proposed. With the estimate, it is checked whether the candidate is or is not a CLF. If it is, a feedback controller is designed just using data, which satisfies sufficient conditions mentioned above. Finally, the estimate of DOA for closed-loop is enlarged by finding an appropriate CLF from a CLF candidate set based on data. Because the controller is designed directly from data, complexity in building the model and modeling error are avoided.     

基于广义模糊双曲正切模型的自适应控制器

针对一类非线性函数未知的非线性离散系统，提出一种新的基于广义模糊双曲正切模型的参考模型自适应控制器设计方法，并利用Lyapunov稳定性理论证明了该控制器是全局渐近稳定的．仿真例子证明了该方法的有效性．     

A simple receding horizon control for state delayed systems and its stability criterion

In this paper, a simple receding horizon (or model predictive) control for state delayed systems is presented and its solution is given in a closed form by a reduction method. While the control for a time-delay system is usually complex, the proposed controller is simple to construct and therefore can be simply implemented in real applications. To check the closed-loop stability of the proposed controller, a sufficient condition is provided by linear matrix inequalities. In addition, a numerical algorithm is presented for computing the eigenvalues of systems with distributed time delays, which can be used as a necessary and sufficient condition to check closed-loop stability. It is shown by simulation that this simple control can be a stabilizing control for time-delay systems.     

一阶伪线性系统的模型参考输出跟踪控制

针对伪线性系统的模型参考输出跟踪问题,设计伪线性系统的模型参考跟踪策略.控制器分为两部分,其一为反馈镇定控制器,保证闭环系统是渐近稳定的;另一为前馈补偿控制器,通过求解基于控制器存在条件建立的方程组得到控制器的参量矩阵,使得闭环系统的输出渐近跟踪参考系统的输出,且当系统中存在时变系数时方法仍是有效的,控制器中保有部分自由度可以进一步利用,以提高具体控制任务所需的系统性能.数值仿真验证了所提出方法的有效性.     

A fuzzy adaptive variable-structure control scheme for uncertain chaotic MIMO systems with sector nonlinearities and dead-zones

In this paper, a fuzzy adaptive variable-structure controller is investigated for a class of uncertain multi-input multi-output (MIMO) chaotic systems with both sector nonlinearities and dead-zones. A suitable adaptive fuzzy system is used to reasonably approximate the uncertain functions. A Lyapunov approach is employed to derive the parameter adaptation laws and prove the boundedness of all signals of the closed-loop system as well as the exponential convergence of the closed-loop errors to an adjustable region. The proposed controller can be applied to the systems with or without sector nonlinearities and/or dead-zones in the input. The effectiveness of the proposed fuzzy adaptive controller is illustrated throughout simulation results.     

基于辅助变量的闭环系统子空间辨识

提出一种基于辅助变量的子空间辨识方法,适用于控制器信息未知以及参考输入已知的闭环系统参数辨识.通过将输入-输出数据块正交投影到辅助变量的行空间,直接得到扩展观测矩阵垂空间的估计.由此可从闭环系统中提取出对象模型信息,同时由SVD分解得到扩展观测矩阵与下三角Toeplitz矩阵的估计.给出了系统参数矩阵、噪声矩阵的计算方法.将所提出的子空间辨识方法应用于闭环动态的系统参数估计,其结果表明了该方法的有效性.     

Adaptive neural control and learning of affine nonlinear systems

This paper presents deterministic learning from adaptive neural network control of affine nonlinear systems with completely unknown system dynamics. Thanks to the learning capability of radial basis function, neural network (NN), stable adaptive NN controller is designed for the unknown affine nonlinear systems. The designed adaptive NN controller is rigorously shown that learning of the unknown closed-loop system dynamics can be achieved during the stable control process because partial persistent excitation condition of some internal signals in the closed-loop system is satisfied. Subsequently, neural learning controller using the knowledge obtained from deterministic learning is constructed to achieve closed-loop stability and improve control performance. Numerical simulation is provided to show the effectiveness of the proposed control scheme.     

基于观测器的受扰多项式系统H∞输出跟踪控制

考虑一类受到外部扰动影响的多项式系统在状态不完全可测情况下的H_∞输出跟踪控制问题.首先,综合前馈-反馈复合控制思想,设计基于观测器的输出跟踪控制器,其中反馈镇定控制器用于保证闭环系统稳定,前馈补偿控制器用以实现对参考模型输出信号的跟踪;然后,提出具有输出反馈结构的跟踪控制方法,其优势在于实现了分离原则,可单独设计观测器和控制器,降低计算复杂度;接着,利用依赖全状态的齐次多项式Lyapunov函数导出使得闭环系统渐近稳定且满足H_∞跟踪性能的充分条件,借助多项式平方和凸优化技术可直接求得相应的观测器和控制器;最后,通过数值仿真实例验证所提出设计方法的有效性和优越性.     

Discrete-time optimal fuzzy controller design: global conceptapproach

Proposes a systematic and theoretically sound way to design a global optimal discrete-time fuzzy controller to control and stabilize a nonlinear discrete-time fuzzy system with finite or infinite horizon (time). A linear-like global system representation of a discrete-time fuzzy system is first proposed by viewing such a system in a global concept and unifying the individual matrices into synthetic matrices. Then, based on this kind of system representation, a discrete-time optimal fuzzy control law which can achieve a global minimum effect is developed theoretically. A nonlinear two-point boundary-value-problem (TPBVP) is derived as a necessary and sufficient condition for the nonlinear quadratic optimal control problem. To simplify the computation, a multi-stage decomposition of the optimization scheme is proposed, and then a segmental recursive Riccati-like equation is derived. Moreover, in the case of time-invariant fuzzy systems, we show that the optimal controller can be obtained by just solving discrete-time algebraic Riccati-like equations. Based on this, several fascinating characteristics of the resultant closed-loop fuzzy system can easily be elicited. The stability of the closed-loop fuzzy system can be ensured by the designed optimal fuzzy controller. The optimal closed-loop fuzzy system can not only be guaranteed to be exponentially stable, but also stabilized to any desired degree. Also, the total energy of system output is absolutely finite. Moreover, the resultant closed-loop fuzzy system possesses an infinite gain margin, i.e. its stability is guaranteed no matter how large the feedback gain becomes. An example is given to illustrate the proposed optimal fuzzy controller design approach and to demonstrate the proven stability properties     

Design of a switching controller for nonlinear systems with unknown parameters based on a fuzzy logic approach

This paper deals with nonlinear plants subject to unknown parameters. A fuzzy model is first used to represent the plant. An equivalent switching plant model is then derived, which supports the design of a switching controller. It will be shown that the closed-loop system formed by the plant and the switching controller is a linear system. Hence, the system performance of the closed-loop system can be designed. An application example on controlling a two-inverted pendulum system on a cart will be given to illustrate the design procedure of the proposed switching controller.     

A closed-loop data based test for robust performance improvement in iterative identification and control redesigns

In robust iterative identification and control redesign techniques, a stabilizing controller connected in a closed loop is normally replaced by an alternative attractive stabilizing controller to improve robustness and performance of the closed-loop system. In this paper, novel test methods are proposed to check whether a new stabilizing controller improves performance or not when the existing controller is replaced by this new controller in the closed loop. The proposed tests are based on closed-loop data and no plant model, and can be used for both the SISO and MIMO linear time-invariant systems. For the proposed tests, the plant dynamics is assumed to be unknown whereas the existing and new controller transfer function matrices are known to the designer. These assumptions are common in iterative identification and control redesign techniques. The performance improvement test methods proposed in this paper build on the experimental set-up proposed in Dehghani, Lecchini, Lanzon, and Anderson (2009) which was used to only check whether controllers ensure internal stability of a feedback interconnection or not. In this paper, new test methods are proposed to ascertain robust performance improvement that cannot be obtained from test results of Dehghani et al. (2009). A numerical example is illustrated to show effectiveness of the proposed test methods.     

冷带轧机厚控系统自适应鲁棒输出反馈动态控制器设计

冷带轧机厚控系统可被认为是一个受外界干扰的线性不确定时滞系统.本文首先设计了标称系统下的鲁棒输出反馈动态控制器,以改善闭环系统的动静态性能;其次,在系统不需要满足不确定性匹配条件的情况下,将参数和外部扰动不确定性综合考虑.应用Lyapunov稳定性理论设计了系统不确定性上界参数的自适应估计器和系统的自适应控制器,保证了闭环系统的渐近稳定性,减小了设计的保守性;两者结合实现了板带出口厚度的有效控制.最后通过一个仿真实例说明本文所提出的自适应鲁棒控制器的有效性.     

Nonlinear robust control of a small-scale helicopter on a test bench

A nonlinear robust controller design procedure is presented, which is designed to simultaneously satisfy multiple conflicting closed-loop performance specifications. Significantly, a robust performance specification for the experimental system, developed for studying the attitude control of a small-scale helicopter in our previous work, is discussed quantitatively. The robust performance specifications and nominal multiple closed-loop performance specifications are conflicting. Use of the Convex Integrated Design (CID) method can provide, where feasible, a single closed-loop controller which satisfies a set of multiple conflicting performance specifications. However, the resultant controller has a complex form. Here, the standard CID method is extended to a more general control system framework to solve the conflicting simultaneous performance design problem. When compared with the standard CID design, the extended CID design procedure generates a relatively simple closed-loop controller. Finally, the synthesised controller is tested in simulation and is validated with an experimental small-scale test helicopter, demonstrating the performance of the proposed controller.