将基于知识的规则模型和解析的数学模型有机结合，建立两级结构的实时专家控制系统（ECS）。由具有专家自学习功能的实时专家系统（ES）以专家优化方式寻找电解液最优酸锌含量比和最优温度，由实时控制系统（RTCS）控制新液流量、总地槽液位和冷却风机状态，保证生产过程在最优生产条件下进行。本文介绍了系统结构、专家优化技术、实时控制技术和系统实现。

针对起动机性能测试，设计一种智能PID控制器，它根据不同控制状态采取不同控制策略，将PID控制与Fuzzy推理控制相结合，在线自动整定PID参数，提高了控制系统的适应能力和鲁棒性，改善了系统的动态品质。此外，还介绍了测试系统组成、参数校对技术。实际运行结果表明，该系统检测精度高，快速性能好，可靠性高，能稳定运行于复杂环境的电机生产线上。

本文针对焦炉集气管压力系统具有强耦合、强干扰、典型非线性的特点，提出一种混合智能控制方法，将经典PID控制、前馈控制、专家控制相结合，把三种方法的简便性、可靠性、抗扰动快速性、灵活性融为一体，发挥各自的长处。并介绍了控制器的设计方法、系统实现与工业运行结。实际运行结果证明了该方法的有效性。

Depending on varying prices of electricity, an optimal power-dispatching system (OPDS) is developed to minimize the cost of power consumption in the electrochemical process of zinc (EPZ). Due to the complexity of the EPZ, the main factors influencing the power consumption are determined by qualitative analysis, and a series of conditional experiments is conducted to acquire sufficient data, then two backpropagation neural networks are used to describe these relationships quantitatively. An equivalent Hopfield neural network is constructed to solve the optimization problem where a penalty function is introduced into the network energy function so as to meet the equality constraints, and inequality constraints are removed by alteration of the Sigmoid function. This OPDS was put into service in a smeltery in 1998. The cost of power consumption has decreased significantly, the total electrical energy consumption is reduced, and it is also beneficial to balancing the load of the power grid. The actual results show the effectiveness of the OPDS. This paper introduces a successful industrial application and mainly presents how to utilize neural networks to solve particular problems for the real world.

With the increasing complexity of industrial application, an embedded control system (ECS) requires processing a number of hard real-time tasks and needs fault-tolerance to assure high reliability. Considering the characteristics of real-time tasks in ECS, an integrated algorithm is proposed to schedule real-time tasks and to guarantee that all real-time tasks are completed before their deadlines even in the presence of faults. Based on the nonpreemptive critical-section protocol (NCSP), this paper analyzes the blocking time introduced by resource con icts of relevancy tasks in fault-tolerant multiprocessor systems. An extended schedulability condition is presented to check the assignment feasibility of a given task to a processor. A primary/backup approach and on-line replacement of failed processors are used to tolerate processor failures. The analysis reveals that the integrated algorithm bounds the blocking time, requires limited overhead on the number of processors, and still assures good processor utilization. This is also demonstrated by simulation results. Both analysis and simulation show the e ectiveness of the proposed algorithm in ECS.