无补偿预热技术在大同市集中供热工程中的应用

一、概况： 大同市是山西省的第二大城市，位于山西省的最北部，地处黄土高原东北边缘，大同盆地北部幅员 １４１２７平方公里，人口 ２７６万。大同地区属于典型的温带大陆性气候。四季温差变化较大，最低温度－ ２９． １℃，冬季采暖计算温度－１７℃，采暖期五个半月计１６     

Constrained Optimal Control of Hybrid Systems With a Linear Performance Index

We consider the constrained finite and infinite time optimal control problem for the class of discrete-time linear hybrid systems. When a linear performance index is used the finite and infinite time optimal solution is a piecewise affine state feedback control law. In this paper, we present algorithms that compute the optimal solution to both problems in a computationally efficient manner and with guaranteed convergence and error bounds. Both algorithms combine a dynamic programming exploration strategy with multiparametric linear programming and basic polyhedral manipulation     

On the computation of linear model predictive control laws

Finite-time optimal control problems with quadratic performance index for linear systems with linear constraints can be transformed into Quadratic Programs (QPs). Model Predictive Control requires the on-line solution of such QPs. This can be obtained by using a QP solver or evaluating the associated explicit solution. The objective of this note is twofold. First, we shed some light on the computational complexity and storage demand of the two approaches when an active set QP solver is used. Second, we show the existence of alternative algorithms with a different tradeoff between memory and computational time. In particular, we present an algorithm which, for a certain class of systems, outperforms standard explicit solvers both in terms of memory and worst case computational time.     

挖掘机铲斗安装孔座的焊接修复

<正>我校一辆WY-25型履带式液压挖掘机,经长期使用,铲斗的安装孔座磨损严重,已无法使用,需修复,见图1。经分析,该挖掘机的铲斗斗体材料是低合金高强钢Q345,安装孔座材料是铸钢。更换新的安装孔座,需要把铸钢安装孔座焊接到低合金高强钢铲斗     

Dynamic programming for constrained optimal control of discrete-time linear hybrid systems

In this paper we study the solution to optimal control problems for constrained discrete-time linear hybrid systems based on quadratic or linear performance criteria. The aim of the paper is twofold. First, we give basic theoretical results on the structure of the optimal state-feedback solution and of the value function. Second, we describe how the state-feedback optimal control law can be constructed by combining multiparametric programming and dynamic programming.     

Regularization and validation of neural network models of nonlinear systems

A characteristic feature of the neural network models is the large number of parameters. A model offering many parameters usually gives rise to problems, and the variance contribution to the modeling error might be very high. Therefore, it is crucial to find the model with the optimal number of parameters. In this paper two techniques of selection of the optimal number of model parameters are described and compared: explicit and implicit regularization techniques. Model validation forms the final stage of an identification procedure with the aim of assessing objectively whether the identified model agrees sufficiently well with the observed data. In this paper the reliability of the correlation-based validation tests and the χ²-test is analyzed.