Synthesis of continuous control of a mechanical system with an unknown inertia matrix

The problem of the synthesis of a bounded control for a Lagrange scleronomic system is considered. We assume that the kinetic energy matrix of the system is known with some accuracy and that the system is subjected to uncontrolled bounded perturbations. The feedback control law, which allows us to steer the system to the given state at rest in a finite time, is constructed. The sufficient conditions of this behavior are formulated. The approach applied was proposed earlier for the case of a system with a known kinetic energy matrix. It is based upon the methods of the stability theory of motion. In order to construct the control law and justify it, we use an implicit Lyapunov function. The effectiveness of the control law is demonstrated with the help of numerical modeling of controlled motions of a two-link manipulator, which holds a weight of unknown mass in its hand.     

Maximal controllability of input constrained unstable systems by the addition of implicit constraints

The null controllable set of a system is the largest set of states that can be controlled to the origin. Control systems that have a region of attraction equal to the null controllable set are said to be maximally controllable closed-loop systems. In the case of open-loop unstable plants with amplitude constrained control it is well known that the null controllable set does not cover the entire state-space. Further the combination of input constraints and unstable system dynamics results in a set of state constraints which we call implicit constraints. It is shown that the simple inclusion of implicit constraints in a controller formulation results in a controller that achieves maximal controllability for a class of open-loop unstable systems.     

Nonlinear prediction of manufacturing systems through explicit and implicit data mining

Many processes in the industrial realm exhibit stochastic and nonlinear behavior. Consequently, an intelligent system must be able to ndapt to nonlinear production processes as well as probabilistic phenomena. To this end, an intelligent manufacturing system may draw on techniques from disparate fields, involving knowledge in both explicit and implicit form.In order for a knowledge based system to control a manufacturing process, an important capability is that of prediction: forecasting the future trajectory of a process as well as the consequences of the control action. This paper presents a comparative study of explicitaand implicit methods to predict nonlinear chaotic behavior. The evaluated models include statistica; procedures as well as neural networks and case based reasoning. The concepts are crystallized through a case study in the prediction of chaotic processes adulterated by various patterns of noise.     

Numerical study of passive and active flow separation control over a NACA0012 airfoil

This paper is focused on numerical investigation of subsonic flow separation over a NACA0012 airfoil with a 6° angle of attack and flow separation control with vortex generators. The numerical simulations of three cases including an uncontrolled baseline case, a controlled case with passive vortex generator, and a controlled case with active vortex generator were carried out. The numerical simulation solves the three-dimensional Navier-Stokes equations for compressible flow using a fully implicit LU-SGS method. A fourth-order finite difference scheme is used to compute the spatial derivatives. The immersed-boundary method is used to model both the passive and active vortex generators. The characteristic frequency that dominates the flow is the natural frequency of separation in the baseline case. The introduction of the passive vortex generator does not alter the frequency of separation. In the case with active control, the frequency of the sinusoidal forcing was chosen close to the natural frequency of separation. The time- and spanwise-averaged results were used to examine the mean flow field for all three cases. The passive vortex generators can partially eliminate the separation by reattaching the separated shear layer to the airfoil over a significant extent. The size of the averaged separation zone has been reduced by more than 80%. The flow control with active vortex generator is more effective and the separation zone is not visible in the averaged results. The three-dimensional structures of the flow field have also been studied.     

隐式GPC算法在重介分选过程控制中的研究

为解决重介分选过程中重介质悬浮液密度与液位过程模型失配问题,引入隐式GPC算法对模型参数进行在线辨识,实现对重介质悬浮液的密度与液位解耦控制。仿真结果表明,针对重介分选过程模型具有大滞后、强耦合的这一特性,隐式GPC算法控制效果较好,抗干扰能力强,在模型失配的情况下,仍然保持系统的输出稳定。     

基于CARIMA模型的多变量极点配置自校正直接算法及其鲁棒性

本文根据 CARIMA 模型,采用双线性一步松驰算法和多项式矩阵展开交换法,给出一种适用于非最小相位系统的多变量极点配置自校正直接算法,并研究了其鲁棒性.此法计算量小,对初值选择不敏感,系统跟踪调节性能好,鲁棒性强,是一种有应用前景的极点配置直接算法。     

Feedback sensitivity functions analysis of finite‐time stabilizing control system

This paper presents feedback sensitivity functions analysis of implicit Lyapunov function‐based control system in case of finite‐time stabilization problem. The Gang of Four is chosen as a feedback sensitivity tool. The results can be used for parametric tuning of control algorithms in order to guarantee desired closed‐loop sensitivity specifications. The obtained results are supported by numerical examples. Copyright © 2016 John Wiley & Sons, Ltd.     

参数时变系统的广义预测控制研究

针对参数时变系统,研究了自适应预测控制器的设计问题.采用隐式广义预测控制算法(IGPC),无需辨识对象模型参数,而是利用输入/输出数据直接辩识控制器参数,以求解最优控制增量,具有计算量小、实时性高的特点.仿真结果表明,在不需要关于被控对象先验知识的情况下,隐式广义预测控制器可以很好地跟踪设定值的变化,同时对于系统外部干扰和模型参数的变化具有很好的适应能力,在参数时变系统控制器设计中具有良好的应用前景.     

Experimental evaluation of teleoperation system with force-free control and visual servo control by human operator perception

This research considers the teleoperation of an articulated robot arm by means of force-free control and visual servo control (VSC) over communication channels using the Internet technology. A semi-autonomous type teleoperation system contains a human supervisory control and VSC schemes and switches one scheme to another for accomplishing the required task accurately. The main investigation is carried out to find how it effectively improves the accuracy and the effectiveness of the teleoperation after provision of a visual feedback channel to the system. The system accuracy, effectiveness, repeatability and handleability based on the human operator’s skills and operator’s cognitive aspects are evaluated using experimental results and statistical data analysis. Effectiveness of the statistical analysis is assured by increasing the number of experiment data and assuming environmental factors, and implicit variables maintain to be unchanged. Correlation coefficients are calculated to find out how controlled input parameters are related to the successful output given by the system.     

Bézier representation for cubic surface patches

The paper describes a new method for creating rectangular Bézier surface patches on an implicit cubic surface. Traditional techniques for representing surfaces have relied on parametric representations of surfaces, which, in general, generate surfaces of implicit degree 8 in the case of rectangular Bézier surfaces with rational biquadratic parameterization. The method constructs low-degree algebraic surface patches by reducing the implicit degree from 8 to 3. The construction uses a rectangular biquadratic Bézier control polyhedron that is embedded within a tetrahedron and satisfies a projective constraint. The control polyhedron and the resulting cubic surface patch satisfy all of the standard properties of parametric Bézier surfaces, including interpolation of the corners of the control polyhedron and the convex-hull property.