Multivariable adaptive actuator nonlinearity compensation
Gang Tao, Yun Ling
Abstract
Gang Tao, Yun Ling
Abstract
Many control systems are multivariable. Coupling dynamics in a multivariable system make it essentially more difficult to control than a single-variable system. In this paper, two adaptive schemes are developed for compensation of unknown nonsmooth nonlinearities at the input of a known multivariable linear plant: one with a state feedback design and the other with an output feedback design, based on a multivariable parameter estimation algorithm for coupled error models. Unlike their single-variable counterparts, some of the multivariable adaptive actuator nonlinearity compensation problems still remain unsolved if the linear plant is also unknown.
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Many control systems are multivariable. Coupling dynamics in a multivariable system make it essentially more difficult to control than a single-variable system. In this paper, two adaptive schemes are developed for compensation of unknown nonsmooth nonlinearities at the input of a known multivariable linear plant: one with a state feedback design and the other with an output feedback design, based on a multivariable parameter estimation algorithm for coupled error models. Unlike their single-variable counterparts, some of the multivariable adaptive actuator nonlinearity compensation problems still remain unsolved if the linear plant is also unknown.
Key concepts: Multivariable calculus, Control theory (sociology), Compensation (psychology), Actuator, Nonlinear system, Adaptive control, Computer science, Control engineering