Nonlinear Adaptive Control Law Research Articles

Nonlinear adaptive flight control with genetic algorithm design optimization

This paper examines the use of a nonlinear adaptive control law for multi-axis control of a high-performance aircraft with stabilator, aileron and rudder failures. The control law is based on a backstepping design approach with fixed parameter optimization done using a stochastic genetic algorithm. The control law is demonstrated on a six-degree-of-freedom simulation with nonlinear aerodynamic and engine models, actuator models with saturation, and turbulence. There are substantial differences between the control law design and simulation models, which are used to demonstrate some robustness aspects of this control law. To deal with actuator saturation, the Lyapunov function is modified so that the growth of integrated error and the rate of change of parameter growth are both reduced when the surface commands are growing at a rate that will likely saturate the actuators. Published in 1999 by John Wiley & Sons, Ltd. This article is a US Government work and is in the public domain in the United States.

Robust adaptive control of a robotic manipulator including motor dynamics

An adaptive nonlinear control law that incorporates the manipulator dynamics as well as dynamics of the actuator is developed in this article. The proposed adaptive robust tracking controller requires position measurements only. The controller consists of two parts: a linear observer that generates an estimated error from the error on the joint position, together with a linear feedback controller that utilizes the estimated states. The second part is an adaptive controller that utilizes the feedback states from the linear observer to generate a control effort that takes into consideration the dynamic parameters variation of the robot and actuator. The closed loop system is locally stable in the Lyapunov sense. © 1998 John Wiley & Sons, Inc.

Estimation and Nonlinear Control of an Activated Sludge Wastewater Treatment Process

Design and control of biological wastewater treatment process become subjects of increasing importance because of interest in high effluent quality. But these tasks are made difficult by the absence of a sophisticated instrumentation for on-line measurement of some key biological variables. In this paper we suggest a nonlinear adaptive feedback-linearizing control law for an activated sludge process. The control approach structure is combined with an estimation algorithm, for the on-line reconstruction of biological states and parameter variables of the process. The efficiency and the robustness of both the control and estimation schemes are demonstrated via computer simulations with measurement noises and abrupt jumps of the process kinetic parameters.

Adaptive Control of a Single Link Manipulator Including Motor and Input Unmodelled Dynamics

An adaptive nonlinear control law that incorporates the manipulator dynamics as well as dynamics of the actuator is developed in this article. The technique is based on nonlinear feedback lineariza...

Transient stabilization of power systems with an adaptive control law

Due to a variety of effects, such as lightning, severe storms and equipment failures, the configuration of an electric power system is not constant. Thus, important parameters, such as effective reactances of transmission lines, in an electric power system always contain some uncertainties. The aim of this paper is to discuss transient stability enhancement and voltage regulation of power systems using feedback linearization techniques and an adaptive control approach. A nonlinear controller design approach is employed to design an adaptive nonlinear control law to prevent the loss of synchronism in a power system under a large sudden fault. An adaptive nonlinear controller is proposed and the stability results for the overall system are established. Simulation results show that transient stability enhancement and voltage regulation of a power system under a large sudden fault can be achieved.

Industrial Application of Adaptive Nonlinear Control for Bakers' Yeast Production

An adaptive nonlinear control law was used for the regulation of the ethanol concentration in industrial bakers’ yeast production. Based on the closed-loop linearizing approach, the control law was originally designed for a 20 L fermentor. The control law required ethanol measurement and oxygen transfer rate evaluation. Except for volume value, the scale-up to a 60 000 L fermentor was done without any change in model parameters or tuning parameters values. The results at the industrial scale can be considered as good as that obtained at the laboratory scale.