Open Access. Powered by Scholars. Published by Universities.®

Engineering Commons

Open Access. Powered by Scholars. Published by Universities.®

Missouri University of Science and Technology

Mechanical Engineering

Closed Loop Systems

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Publication Year

Articles 1 - 4 of 4

Full-Text Articles in Engineering

Issues On Stability Of Adp Feedback Controllers For Dynamical Systems, S. N. Balakrishnan, Jie Ding, F. L. Lewis Aug 2008

Issues On Stability Of Adp Feedback Controllers For Dynamical Systems, S. N. Balakrishnan, Jie Ding, F. L. Lewis

Mechanical and Aerospace Engineering Faculty Research & Creative Works

This paper traces the development of neural-network (NN)-based feedback controllers that are derived from the principle of adaptive/approximate dynamic programming (ADP) and discusses their closed-loop stability. Different versions of NN structures in the literature, which embed mathematical mappings related to solutions of the ADP-formulated problems called “adaptive critics” or “action-critic” networks, are discussed. Distinction between the two classes of ADP applications is pointed out. Furthermore, papers in “model-free” development and model-based neurocontrollers are reviewed in terms of their contributions to stability issues. Recent literature suggests that work in ADP-based feedback controllers with assured stability is growing in diverse forms.


Approximate Dynamic Programming Based Optimal Neurocontrol Synthesis Of A Chemical Reactor Process Using Proper Orthogonal Decomposition, Radhakant Padhi, S. N. Balakrishnan Jan 2003

Approximate Dynamic Programming Based Optimal Neurocontrol Synthesis Of A Chemical Reactor Process Using Proper Orthogonal Decomposition, Radhakant Padhi, S. N. Balakrishnan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The concept of approximate dynamic programming and adaptive critic neural network based optimal controller is extended in this study to include systems governed by partial differential equations. An optimal controller is synthesized for a dispersion type tubular chemical reactor, which is governed by two coupled nonlinear partial differential equations. It consists of three steps: First, empirical basis functions are designed using the "Proper Orthogonal Decomposition" technique and a low-order lumped parameter system to represent the infinite-dimensional system is obtained by carrying out a Galerkin projection. Second, approximate dynamic programming technique is applied in a discrete time framework, followed by the …


Stability Analysis Of Nonlinear Machining Force Controllers, Robert G. Landers, Yen-Wen Lu Jan 1999

Stability Analysis Of Nonlinear Machining Force Controllers, Robert G. Landers, Yen-Wen Lu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Model parameters vary significantly during a normal operation, thus, adaptive techniques have predominately been used. However, model-based techniques that carefully account for changes in the force process have again been examined due to the reduced complexity afforded by such techniques. In this paper, the effect of model parameter variations on the closed-loop stability for two model-based force controllers is examined. It was found that the stability boundary in the process parameter space can be exactly determined for force control systems designed for static force processes. For force control systems designed for first-order force processes, it was found that the stability …


Adaptive Critic Based Neurocontroller For Autolanding Of Aircraft With Varying Glideslopes, Gaurav Saini, S. N. Balakrishnan Jan 1997

Adaptive Critic Based Neurocontroller For Autolanding Of Aircraft With Varying Glideslopes, Gaurav Saini, S. N. Balakrishnan

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In this paper, adaptive critic based neural networks have been used to design a controller for a benchmark problem in aircraft autolanding. The adaptive critic control methodology comprises successive adaptations of two neural networks, namely `action' and `critic' networks until closed loop optimal control is achieved. The autolanding problem deals with longitudinal dynamics of an aircraft which is to be landed in a specified touchdown region in the presence of wind disturbances and gusts using elevator deflection as the control for glideslope and flare modes. The performance of the neurocontroller is compared to that of a conventional PID controller. Neurocontroller's …