MPC860在七号信令通信网中的应用

介绍了摩托罗拉嵌入式处理器MPC860的内部结构、主要功能和性能特性。主要分析了MPC860在通信方面的优越性和先进性,包括通信处理模块、中断处理机制、七号信令的特殊使用等。描述了MPC860在七号信令通信网中的具体应用方案。对我国通信现状和七号信令的通信原理和层次结构进行了介绍。     

Adaptive predictive control algorithm based on Laguerre Functional Model

Laguerre Functional Model has many advantages such as good approximation capability for the variances of system time‐delay, order and other structural parameters, low computational complexity, and the facility of online parameter identification, etc., so this model is suitable for complex industrial process control. A series of successful applications have been gained in linear and non‐linear predictive control fields by the control algorithm based on Laguerre Functional Model, however, former researchers have not systemically brought forward the theoretical analyses of the stability, robustness, and steady‐state performance of this algorithm, which are the keys to guarantee the feasibility of the control algorithm fundamentally. Aimed at this problem, we introduce the principles of the Incremental Mode Linear Laguerre Predictive Control (IMLLPC) algorithm, and then systemically propose the theoretical analyses and proofs of the stability and robustness of the algorithm, in addition, we also put forward the steady‐state performance analysis. At last, the control performances of this algorithm on two different physical industrial plants are presented in detail, and a number of experimental results validate the feasibility and superiority of IMLLPC algorithm. Copyright © 2005 John Wiley & Sons, Ltd.     

基于MPC850 VxWorks系统的BSP设计

首先介绍嵌入式系统VxWorks及其启动过程;分析了基于MPC 850最小系统的硬件和BSP的执行流程;重点研究了MPC850BSP的设计与应用程序加载,包括其硬件驱动程序的设计、应用程序加载、建立调试环境和target server的配置等;基于MPC850系统的Vxworks BSP调试平台的实现,对Vxworks上层应用软件和底层硬件驱动的并行开发有着很重要的意义。     

工业过程的先进控制

在分析工业过程特点的基础上，总结了工业过程先进控制的发展现状，阐述了PID控制器参数整定和模型预测控制的基本概念和内容，讨论了工业过程先进控制的核心内容及其带来的可观的经济效益，并探讨了先进控制软件的产业化问题。     

Optimal maintenance planning for sustainable energy efficiency lighting retrofit projects by a control system approach

The energy savings achieved by implementing energy efficiency (EE) lighting retrofit projects are sometimes not sustainable and vanish rapidly given that lamp population decays as time goes by if without proper maintenance activities. Scope of maintenance activities refers to replacements of failed lamps due to nonrepairable lamp burnouts. Full replacements of all the failed lamps during each maintenance interval contribute to a tight project budget due to the expense for the lamp failure inspections, as well as the procurement and installation of new lamps. Since neither “no maintenance” nor “full maintenance” is preferable to the EE lighting project developers (PDs), we propose to design an optimal maintenance plan that optimises the number of replacements of the failed lamps, such that the EE lighting project achieves sustainable performance in terms of energy savings whereas the PDs obtain their maximum benefits in the sense of cost–benefit ratio. This optimal maintenance planning (OMP) problem is aptly formulated as an optimal control problem under control system framework, and solved by a model predictive control (MPC) approach. An optimal maintenance plan for an EE lighting retrofit project is designed as a case study to illustrate the effectiveness of the proposed control system approach.     

A General Robust MPC Design for the State‐Space Model: Application to Paper Machine Process

Applying model predictive control (MPC) in some cases such as complicated process dynamics and/or rapid sampling leads us to poorly numerically conditioned solutions and heavy computational load. Furthermore, there is always mismatch in a model that describes a real process. Therefore, in this paper in order to prevail over the mentioned difficulties, we design a robust MPC using the Laguerre orthonormal basis in order to speed up the convergence at the same time with lower computation adding an extra parameter “a” in MPC. In addition, the Kalman state estimator is included in the prediction model and accordingly the MPC design is related to the Kalman estimator parameters as well as the error of estimations which helps the controller react faster against unmeasured disturbances. Tuning the parameters of the Kalman estimator as well as MPC is another achievement of this paper which guarantees the robustness of the system against the model mismatch and measurement noise. The sensitivity function at low frequency is minimized to tune the MPC parameters since the lower the magnitude of the sensitivity function at low frequency the better command tracking and disturbance rejection results. The integral absolute error (IAE) and peak of the sensitivity are used as constraints in optimization procedure to ensure the stability and robustness of the controlled process. The performance of the controller is examined via the controlling level of a Tank and paper machine processes.     

基于PowerPC主机处理器的计算机模块设计

PowerPC主机处理器MPC7447A是高性能、低功耗的32位嵌入式处理器,文章设计了基于MPC7447A的单板计算机,详细说明了硬件设计中处理器节点设计、控制器设计等要点,并介绍了VxWorks BSP的开发方法。     

Model-based Predictive Control for Spatially-distributed Systems Using Dimensional Reduction Models

In this paper, a low-dimensional multiple-input and multiple-output (MIMO) model predictive control (MPC) configuration is presented for partial differential equation (PDE) unknown spatially-distributed systems (SDSs). First, the dimension reduction with principal component analysis (PCA) is used to transform the high-dimensional spatio-temporal data into a low-dimensional time domain. The MPC strategy is proposed based on the online correction low-dimensional models, where the state of the system at a previous time is used to correct the output of low-dimensional models. Sufficient conditions for closed-loop stability are presented and proven. Simulations demonstrate the accuracy and efficiency of the proposed methodologies.     

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.     

基于容许集的多胞不确定系统三模RMPC

针对输入和状态受约束的多胞不确定线性系统,提出了基于容许集的扩大吸引域三模鲁棒模型预测控制方法.在多面体不变集离线模型预测控制算法的基础上引入容许集,以多面体不变集序列的并集作为模态1,基于N步容许集的控制容许集作为模态2,并利用离线设计和在线优化的控制策略,设计了三模变终端约束鲁棒模型预测控制算法,以实现系统渐近稳定.该算法不仅降低了在线运算量,而且扩大了吸引域.最后的仿真结果验证了所提出算法的有效性.