本文针对一类具有多个平衡点的非线性系统，结合控制不变集与和增益调度算法，提出了一种基于扩张终端约束集的双模预测控制设计方法。该方法在非线性系统的有限个平衡点上设计局部LQR控制律，并计算它们的最大控制不变集，在平衡点的选取过程中确保它们的控制不变集是相互重叠的。本文将控制不变集的并集作为双模预测控制的终端约束集，研究了变时域和固定时域模式下双模预测控制的可行性与稳定性。由于使用了扩张终端约束集，使得较小的预测时域即可保证优化的可行性，从而降低了优化问题的规模，减少了在线计算量。仿真结果表明了本文算法的有效性。

This paper is concerned with air handling units (AHUs), the performances of which directly influence those of heating, ventilation and air conditioning systems. An autotuning recedinghorizon optimization method is proposed to synthesize a proportional-integral-derivative (PID) type controller for AHUs. This algorithm is composed of two levels of control. The lower level adopts a conventional PID controller to obtain an acceptable, but not necessarily optimal, performance. The higher level provides optimal low-level controller parameters through minimization of the generalized predictive control criterion. Because the method does not require changes in hardware and the definitions of conventional controller parameters, it can be both easily accepted by process engineers and widely applied to industrial areas. Compared with the performance of a well-tuned conventional PID controller, simulation and experimental results show that the proposed method for AHU systems can achieve a better performance under a wide range of operating conditions.

针对一类工业过程中可描述成Wiener模型的非线性系统，其辨识问题可等价成以估计参数为优化变量的非线性极小值优化问题。利用粒子群优化（PSO）算法在整个参数空间内并行搜索获得极小值优化问题的最优解（Wiener模型的最优估计），通过对粒子的迭代轨迹进行分析，改进了PSO算法中惯性权重和学习因子的选择。通过一个Wiener模型的数值仿真验证了本文提出的辨识方法的有效性和实用性，并将该方法应用在连续退火机组加热炉产品质量模型的辨识研究，取得了满意的辨识效果。

This paper presents an effcient distributed model predictive control scheme based on Nash optimality, in which the on-line optimization of the whole system is decomposed into that of several small co-operative agents in distributed structures, thus it can signi ficantly reduce computational complexity in model predictive control of large-scale systems. The relevant nominal stability and the performance on single-step horizon under the communication failure are investigated. The Shell heavy oil fractionator benchmark control problem is illustrated to verify the effectiveness of the proposed control algorithm. © 2004 Elsevier Inc. All rights reserved.

本文充分考虑大多数复杂热工控制对象非线性特性与运行工况密切相关的实际特点，采用多模型动态矩阵控制方法。并将该方法应用于某电厂300MW机组锅炉过热汽温对象，在典型工况下通过试验数据获得其局部三阶子模型集，基于每个局部子模型分别设计子DMC控制器。通过跟踪实际工况变化来对子控制器加权以获得合适的控制增量。实验结果表明该方法对参数突变适应快，可取得令人满意的控制效果。