基于分片线性函数的图象压缩方法

使用了一种新分片线性逼近算法,算法首先对极大极小友谊赛一分片线性函数的紧凑表示形式做了改进,然后发挥了分片线性逼近的优势。在此基础上,提出了一种基于分片线性逼近的图象压缩编码方法。这种方法具有解压缩速度快的优点,与其它的图象压缩方法（例如DCT）相结合,能够提高图象的压缩效率。     

Building blocks for goal-directed motion

An approach for the integration of intelligent goal directed motion within an interactive real-time computer animation environment is sketched. The approach is based on a cause-and-effect model for intelligent goal direction motion which gives rise to types of motion primitives: one is the application of a so called multi-track recording paradigm for direction motion manipulation; the second is an algorithm to mimic a control system for goal directed motion of joints in a multi-link structure. The techniques described here are features of the procedure based animation system which is described in Reference 1.     

Piecewise linear classification using seniority logic committee methods,with application to remote sensing

A committee classification technique based upon a form of seniority decision logic, and which implements piecewise linear decision surfaces, is proposed and a viable training algorithm is presented. The method determines automatically the number of committee members required and is not dependent upon user specified parameters. Examples are given to illustrate the effectiveness of the method using both model data and satellite remote sensing image data.     

多速率分段线性系统预测控制的显式设计

针对输出采样周期是输入更新周期N倍的多速率分段线性(Piecewise linear, PWL)系统, 本文提出了保证稳定性的显式预测控制器设计方法. 首先, 基于动态规划原理将预测控制优化问题分解为多个单级优化问题; 然后, 根据分段线性系统各子模型以及目标函数的具体形式, 进一步将各单级优化问题分为若干个子问题, 再利用多参数二次规划(Multiparametric quadratic programming, MP-QP)方法求解;最后,通过比较各子问题的解从而得到系统的最优显式控制律. 在设计过程中, 将系统的最大正不变集作为优化问题的终端约束集, 从而保证了系统的稳定性. 仿真结果表明本文提出的显式预测控制方法能够有效降低多速率分段线性系统的在线计算时间, 在保证系统稳定性的同时, 满足其对输入更新速度的要求.     

Explicit output-feedback nonlinear predictive control based on black-box models

Nonlinear model predictive control (NMPC) algorithms are based on various nonlinear models. A number of on-line optimization approaches for output-feedback NMPC based on various black-box models can be found in the literature. However, NMPC involving on-line optimization is computationally very demanding. On the other hand, an explicit solution to the NMPC problem would allow efficient on-line computations as well as verifiability of the implementation. This paper applies an approximate multi-parametric nonlinear programming approach to explicitly solve output-feedback NMPC problems for constrained nonlinear systems described by black-box models. In particular, neural network models are used and the optimal regulation problem is considered. A dual-mode control strategy is employed in order to achieve an offset-free closed-loop response in the presence of bounded disturbances and/or model errors. The approach is applied to design an explicit NMPC for regulation of a pH maintaining system. The verification of the NMPC controller performance is based on simulation experiments.     

分片线性规划及应用

提出通过分片线性逼近和分片线性规划,将非线性优化问题转化为一系列的线性规划进行求解的方法。讨论了分片线性规划的性质,证明了分片线性规划问题可以通过有限次线性规划得到求解,同时,给出了分片线性规划问题局部最优解的充要条件,并基于此构造了求解分片线性规划问题的下降算法。该算法与自适应链接超平面模型相结合,成功地对离心式冷水机组的工作点进行了优化。通过优化,机组的能耗比之当前工作点有了明显的下降,表明通过分片线性规划求解非线性优化问题的有效性。     

Piecewise linear aggregation functions based on triangulation

We introduce a method to construct piecewise linear binary aggregation functions on the unit interval, based on a triangulation of the unit square with one additional vertex. We derive conditions under which such piecewise linear aggregation functions possess additional interesting properties, such as idempotence, symmetry, Lipschitz continuity and 2-monotonicity. This construction method can also be used to approximate binary aggregation functions. In this way, copulas and quasi-copulas are approximated by singular copulas.     

Piecewise linear controller improving its own reliability

Although the capability of neural networks in nonlinear dynamics modelling is well-established, the reliability of the output heavily depends on the training data. The reliability is a serious problem in applying it to real problems. In this paper, we propose a radial basis functions network (RBFN) which evaluates its own reliability and improves itself recursively. This network approximates the input-output relationships with a piecewise linear regression. An adaptive internal model control algorithm in which the reliability of the model is used to tune the controller performance, is also proposed.     

基于函数的时间序列分段线性表示方法

考虑到时间序列的时间特性对不同区段的影响以及时间序列数据动态增长的实际情况,在RPAA ( Reversed Piecewise Aggregate Approximation)和PAA(Piecewise Aggregate Approximation)方法的基础上,提出了一种新的时间序列分段线性表示方法FPAA(Founction Piecewise Aggregate Approximation)。FPAA方法通过定义函数影响因子,克服了RPAA和PAA方法的不足。该方法具有线性时间复杂度,满足下界定理,并且支持时间序列的在线划分。实验表明,与PAA方法和RPAA方法相比,所提出的方法可以较有效地进行时间序列的在线查询。     

Approximate explicit receding horizon control of constrained nonlinear systems

An algorithm for the construction of an explicit piecewise linear state feedback approximation to nonlinear constrained receding horizon control is given. It allows such controllers to be implemented via an efficient binary tree search, avoiding real-time optimization. This is of significant benefit in applications that requires low real-time computational complexity or low software complexity. The method has a priori guarantee of asymptotic stability with region of attraction being a close inner approximation to the stabilizable set. This is achieved by ensuring that the approximation error does not exceed the stability margin.     

Piecewise linear approximation of plane curves by perimeter optimization

A method for the piecewise linear approximation of a plane curve is described. An approximate curve is obtained by choosing a certain number of points from a set of sampled points of the original curve. A “point choice function” that represents the relation between the original points and the chosen points is formulated. The approximation is performed by the dynamic programming principle searching for the optimal point choice function that attains the minimal error about arc length of the curve. Evaluation of the global approximate error provides efficient curve approximations, irrespective of shape complexity, number of sampled points, and irregularity of sampling interval.     

基于斜率提取边缘点的时间序列分段线性表示方法

本文引入解析几何中的斜率,提出了一种新颖的基于斜率提取边缘点的时间序列分段线性表示方法SEEP。对于斜率变化范围比较集中的时间序列,SEEP表示方法有着非常好的效果,与以往的分段线性表示方法相比,SEEP表示方法与原始时间序列之间的拟合误差更小,而且要小很多;对于斜率变化范围比较大的时间序列,SEEP表示方法与原始时间序列之间的拟合误差,和以往的分段线性表示方法相比,也相差不大,并且SEEP表示方法计算简单,易于实现。算法的时间复杂度仅为O（n）,     

约束非线性系统切换鲁棒预测控制

采用“分段蕴含”(PWE)方法, 用一组线性变参数模型(LPV)近似约束非线性系统, 降低模型近似的保守性. 对每个LPV模型引入参数Lyapunov函数, 得到稳定的控制律, 并施加于非线性系统. 当检测到LPV模型发生切换时, 根据可行域的离线设计方法确定适当的切换律, 使系统按照设定的规则切换, 保证切换后的初始状态可行. 在文章最后给出了基于切换策略的控制算法的可行性和稳定性. 与传统非线性预测控制相比, 基于切换策略的鲁棒预测 控制方法保守性更低, 计算量更小.     

Piecewise affinity of min-max MPC with bounded additive uncertainties and a quadratic criterion

This brief shows how a min-max MPC with bounded additive uncertainties and a quadratic cost function results in a piecewise affine and continuous control law. Proofs based on properties of the cost function and the optimization problem are given. The boundaries of the regions in which the state space can be partitioned are also treated. The results are illustrated by an example.     

An operational semantics for Icon: Implementation of a procedural goal-directed language

The generation of compiled code for expressions in programming languages such as Icon that support goal-directed evaluation in addition to traditional control structures presents more of a challenge than generating code for traditional imperative programming languages. This paper describes a code-generation technique for translating Icon programs into a traditional high-level language. Translations into both Pascal and C are discussed. However, any language that provides function parameters and recursion is sufficient. The technique described here has been used in the implementation of an optimizing compiler for Icon.     

一类有约束的分段线性系统双模预测控制

研究分段线性（PL）系统预测控制问题,提出了PL系统双模预测控制,并证明了该方法的稳定性.该方法使用混合逻辑动态系统来建模PL系统,利用PL系统状态反馈控制来确定PL系统的受控不变集,并结合双模预测控制方法获得PL系统双模预测控制.该方法解决了系数矩阵的选择问题,不需要满足最终状态等式约束.一个分段线性系统的实例证明了该方法是可行的.     

A nonlinear model predictive control system based on Wiener piecewise linear models

In this paper a nonlinear model predictive control (NMPC) based on a Wiener model with a piecewise linear gain is presented. This approach retains all the interested properties of the classical linear model predictive control (MPC) and keeps computations easy to solve due to the canonical structure of the nonlinear gain. Some guidelines for the identification of the nominal model as well as the uncertainty bounds are discussed, and two examples that show the possibility of application of this control scheme to real life problems are presented.     

Piecewise Linear Projection Based on Self-Organizing Map

A piecewise linear projection algorithm, based on kohonen's Self-Organizing Map, is presented. Using this new algorithm, neural network is able to adapt its neural weights to accommodate with input space, while obtaining reduced 2-dimensional subspaces at each neural node. After completion of learning process, first project input data into their corresponding 2-D subspaces, then project all data in the 2-D subspaces into a reference 2-D subspace defined by a reference neural node. By piecewise linear projection, we can more easily deal with large data sets than other projection algorithms like Sammon's nonlinear mapping (NLM). There is no need to re-compute all the input data to interpolate new input data to the 2-D output space.     

基于LMI方法的离散分段线性系统静态输出反馈控制

研究了离散分段线性系统静态输出反馈控制问题. 基于分段二次李亚普诺夫函数, 给出了静态输出反馈镇定控制器综合的新的充分的线性矩阵不等式条件. 同时, 通过使用Finsler引理, 引入一组具有特殊结构的松弛变量以减少设计保守性. 与以后方法相比, 所提出的方法具有好的性能, 并且在已有方法失效的情况下仍可用. 文中还将此方法推广到H无穷控制. 最后给出三个例子说明方法的有效性.