针对复杂工业过程具有多变量强耦合、非线性、参数时变特点，基于常规解耦控制技术的控制系统无法应用的问题，讨论了多变量智能解耦控制方法，并进行了工程化研究，提出了具有三级控制结构的基于分布式计算机控制系统（DCS）的多变量智能解耦控制技术。最后介绍了多变量智能解耦控制技术的复杂工业过程中成功应用的实例。

This note describes a multivariable generalized self-tuning controller with decoupling which combines the classical pole-zero placement strategy with the optimal strategy for self-tuning control. The controller uses techniques of updating polynomial matrices on line and eliminating the tracking errors with out use of an integrator, and decouples the multivariable system.

This paper presents a robust vibration control for SCARA-type robot manipulators. Some nonlinear terms in the model of robot manipulators are compensated for by nonlinear feedbak, while th others together with parameter variations, are treated as disturbances. μ-synthesis, which combines the structured singular value and H∞ control to design controllers for plants with structured uncertainty, is applied to design a feedback controller that achieves robust stability and robust performance. Then, by the model-matching method, a feedforward controller is designed to further improve the reference input tracking. Finally, simulation and experiments are conducted to check the effetiveness of the proposed control scheme.

This paper proposed a method to set up control modes for a class of industrial processes, realizing closed-loop control on the suprivisory control level. The control system frame and the implementation of the control system have been developed in detailed. An application example has also been introduced to verify the correctness of object-oriented modeling and control method.

For many multivariable systems, because of the strong cross coupling between controlled variables, it is important to design the decoupling controller. This paper presents a decoupling design of multivariable generalized predictive control by combining feed-forward control with multivariable generalized predictive control, which can realise decoupling control for systems with arbitrary time delay structure.