Filtered adaptive constrained sampled-data control for uncertain multivariable nonlinear systems

A filtered adaptive constrained sampled-data controller for uncertain multivariable nonlinear systems in the presence of various constraints is synthesized in this paper. A piecewise constant adaptive law drives that estimation error dynamics to zero at each sampling time instant yields adaptive parameters. The filtered control scheme consists of two components. Based on an estimation/cancellation strategy, a disturbance rejection control law is designed to compensate the nonlinear uncertainties within the bandwidth of low-pass filters, whereas a constraint violation avoidance control law is designed to solve an online constrained optimization problem. Although a reduced sampling time helps to minimize the estimation error caused by the neglect of unknowns, the resulting aggressive signals put more restrictions on the control law. Greater sacrifice of tracking performance is required to satisfy the constraints. The constraints violation avoidance control law is in favor of a larger sampling time. Sufficient conditions are given to guarantee the stability of the closed-loop system with the sampled-data controller, where the input/output signals are held constant over the sampling period. Numerical examples are provided to validate the theoretical results, comparisons between the constrained sampled-data controller and unconstrained adaptive controller with the implementation of different sampling times are carried out.     

Regulator problem for uncertain linear discrete-time systems with constrained control

A necessary and sufficient condition to test the robustness of a regulator of uncertain linear systems with constrained control is given. The candidate regulator for this test is that stabilizing nominal systems. An illustrative example is also given.     

Extracting Modes of Constrained Structure with Elastic Supports from Free Test Data

The dynamic flexibility (DF) and improved dynamic flexibility (IDF) methods can be applied to extract constrained structural modes from free-free modal test data. The residual flexibility method is also good for boundaries of constrained structure with rigid supports. Under elastic support boundary conditions both the DF and residual flexibility methods cannot produce accurate results. This paper expands the previously published IDF method to become a more general approach for structural design engineers. A new method called the general dynamic flexibility (GDF) method has been developed in this paper to extract constrained structural modes from free test data. The GDF method can always be applied as follows: (1) when the boundary support stiffness is very stiff, the GDF method can accurately obtain results from rigid support as by Liu et al. in 2001 and Zhang and Wei in 2003; (2) when the support stiffness is soft, the present method can produce results similar to those free-free modal parameters measured by hanging structures using rubber band; (3) when the support stiffness is zero, the method can reproduce true free-free modal parameters; and (4) when the support stiffness has any finite values, the GDF method can also achieve satisfactory results for engineering use. The algorithm included in the GDF method converges rapidly and is numerically stable in the analysis. This feature is very practical for many engineering applications for using the GDF method.     

Constraint-based beautification and dimensioning of 3D polyhedral models reconstructed from 2D sketches

3D models reconstructed from 2D sketches are inaccurate because of the inherent inaccuracies in the input and the reconstruction method. It is therefore necessary to “beautify” them before use in CAD systems. We present a method that detects geometric constraints, such as parallel and orthogonal faces, present in the reconstructed model and then selects a subset that constrains the object sufficiently and consistently. The subset selection algorithm first prioritizes the constraints depending on their type and then uses a novel method, based on quasi-Newton optimization, to detect and eliminate redundant and inconsistent constraints. The remaining constraints then define the dimensions of the model fully and consistently. Results from our implementation show that the method can beautify and dimension recovered 3D models correctly at acceptable speed.     

State feedback stabilization of discrete linear switching systems subject to nonsymmetrical state and control bounds

Stabilization problem of discrete-time linear switching systems with bounds on the state and control input is solved in this paper.First,the synthesis of state feedback controllers that ensure the stab...     

CLP(ℜ) and some electrical engineering problems

The Constraint Logic Programming Scheme defines a class of languages designed for programming with constraints using a logic programming approach. These languages are soundly based on a unified framework of formal semantics. In particular, as an instance of this scheme with real arithmetic constraints, the CLP() language facilitates and encourages a concise and declarative style of programming for problems involving a mix of numeric and non-numeric computation.In this paper we illustrate the practical applicability of CLP() with examples of programs to solve electrical engineering problems. This field is particularly rich in problems that are complex and largely numeric, enabling us to demonstrate a number of the unique features of CLP(). A detailed look at some of the more important programming techniques highlights the ability of CLP() to support well-known, powerful techniques from constraint programming. Our thesis is that CLP() is an embodiment of these techniques in a language that is more general, elegant and versatile than the earlier languages, and yet is practical.An earlier version of this paper appeared in the proceedings of the 4th International Conference on Logic Programming, Melbourne, May 1987. Much of this work was carried out while the authors were at Monash University, Melbourne, Australia.     

Continuous-time norm-constrained Kalman filtering

This paper considers continuous-time state estimation when part of the state estimate or the entire state estimate is norm-constrained. In the former case continuous-time state estimation is considered by posing a constrained optimization problem. The optimization problem can be broken up into two separate optimization problems, one which solves for the optimal observer gain associated with the unconstrained state estimates, while the other solves for the optimal observer gain associated with the constrained state estimates. The optimal constrained state estimate is found by projecting the time derivative of an unconstrained estimate onto the tangent space associated with the norm constraint. The special case where the entire state estimate is norm-constrained is briefly discussed. The utility of the filtering results developed are highlighted through a spacecraft attitude estimation example. Numerical simulation results are included.     

一种求解QoS约束组播路由问题的遗传算法*

针对多维QoS约束的组播路由问题,提出了一种基于遗传算法的解决方案QCMRA-GA(GA of QoS Constraints Multicast Routing Algorithm).该算法对经典遗传算法的三大算子进行了重新设计,有效地克服了遗传算法的早熟现象.对染色体进行Prufer树型编码,可以避免回路的产生,并根据编码特性,进行基于叶子节点和Steiner节点的解空间压缩,提高了算法的收敛速度.实验表明QCMRA-GA的正确性和效率性.     

基于语义的QoS感知Web服务发现机制

随着提供相同功能的Web服务数量的日益增多,服务质量(Quality of Service,QoS)成为用户选择Web服务的重要考虑因素.目前,通过对服务QoS属性在语法层匹配来提供Web服务选取的机制不能很好地满足复杂QoS属性匹配的要求.研究了基于用户QoS需求偏好,将用户需求的QoS与候选服务的QoS进行语义比较,结合约束规划(Constraint Programming)方法,在语义层匹配Web服务的QoS属性,选取满足匹配要求的服务,最后对满足QoS属性值约束的候选服务进行优化选择处理,获取最终匹配的候选服务.     

2K-H型多级行星齿轮减速器优化设计系统

讨论了行星齿轮减速器设计中的穷举优化因素,以太阳轮和全部行星轮的体积之和最小为优化设计目标函数,以太阳轮的参数为设计变量,建立了优化数学模型,设计出行星轮系的优化设计系统,并以三级行星减速机为例,介绍了该系统的实际应用。