Publication

Application of the minimum state error variance approach to nonlinear system control

Ljubisa Miskovic
2002
Journal Articles

Abstract

A class of modified state space self-tuning controllers of the minimum state error variance type was considered. A suitable chosen structure of the proposed controller allows the tracking of a time-varying reference input and makes it possible to apply this solution to nonlinear and non-stationary plants. The advantage in using the proposed algorithm for nonlinear system control is demonstrated through its application to aircraft control around a prespecified reference trajectory in the presence of characteristic disturbances. The results show that the proposed controller has good tracking performance and possesses rather good immunity towards disturbances.

Official source

https://infoscience.epfl.ch/entities/publication/62a1fc8c-ce8a-410a-acc1-be19d3eb488f

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Ljubisa Miskovic
2002
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/62a1fc8c-ce8a-410a-acc1-be19d3eb488f

About this result

Related concepts (30)

Nonlinear control

Nonlinear control theory is the area of control theory which deals with systems that are nonlinear, time-variant, or both. Control theory is an interdisciplinary branch of engineering and mathematics that is concerned with the behavior of dynamical systems with inputs, and how to modify the output by changes in the input using feedback, feedforward, or signal filtering. The system to be controlled is called the "plant".

Control theory

Control theory is a field of control engineering and applied mathematics that deals with the control of dynamical systems in engineered processes and machines. The objective is to develop a model or algorithm governing the application of system inputs to drive the system to a desired state, while minimizing any delay, overshoot, or steady-state error and ensuring a level of control stability; often with the aim to achieve a degree of optimality. To do this, a controller with the requisite corrective behavior is required.

Least squares

The method of least squares is a standard approach in regression analysis to approximate the solution of overdetermined systems (sets of equations in which there are more equations than unknowns) by minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the results of each individual equation. The most important application is in data fitting.