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 paper presents a new control approach which can restrain the vibration of centrifuges. In the new scheme, changed support stiffness and self-tuning feed-forward PID control of the decreased vibration force are effectively combined. Some advanced techniques, (such as adaptive modification for unstable vibration regions, two-livel computer control, curve-traching control), are used to make the centrifuge system run in a minimum-vibration state. A horizontal centrifugal experiment is used to test the new control method. Experimental results show the effectiveness of the proposed scheme.

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 presents a novel adaptive decoupling controller for general stochastic multivariable systems with arbitrary time delay structure. The decoupling controller is constructed using a diagonal dynamic precompensator to diagonalize the system interactor matrix and then combining the feed for ward control strategy and the generalized minimum variance approach. It cannot only control unstable and/or non-minimum phase processes but also decouple the closed-loop systems both dynamically and in the static state. It is adaptively implemented in direct form. The global convergence properties and parameter estimate consistency for this adaptive decoupling algorithm are also discussed. It is shown that this adaptive controller not only has globally convergent properties but also generates strongly consistent parameter estimates. The results of simulations and an application are proposed to demonstrate the effectiveness of the algorithm.

A direct adaptive tracking control architecture I proposed for a clss of continuous-time nonlinear dynamic systems, for which an explicit linear parameterization of the uncertainty in the dynamics in either unknown or impossible. The architecture employs fuzzy systems to approximate the optimal controller which is designed on the assumption that all the dynamics in the system are known, develops fuzzy sliding controller to compensate for the plant uncertainties, smooth the control signals and increase robustness. Global asymptotic stability is established in the Lyaunov sense, with the tracking errors converging to a neighborhood of zero. The simulation results verify the effectiveness of the proposed control algorithm.