Stable Reconfigurable Generalized Predictive Control With Application to Flight Control

2005 ◽  
Vol 128 (2) ◽  
pp. 371-378 ◽  
Author(s):  
Jianjun Shi ◽  
Atul G. Kelkar ◽  
Don Soloway

This paper presents the development of a multiinput multioutput generalized predictive control (GPC) law and its application to reconfigurable control design in the event of actuator saturation. The stability of the GPC control law without reconfiguration is first established using an end-point state weighting. Based on the constrained nonlinear optimization, an end-point state weighting matrix synthesis method is derived. A novel reconfiguration strategy is developed for systems that have actuator redundancy and are faced with actuator saturation type failure. An elegant reconfigurable control design is presented with stability proof. A numerical simulation using a short-period approximation model of a civil transport aircraft is presented to demonstrate the reconfigurable control architecture.

Author(s):  
Jianjun Shi ◽  
Atul G. Kelkar ◽  
Donald Soloway

This paper presents development of multi-input multi-output (MIMO) Generalized Predictive Control (GPC) law and its application to reconfigurable control design in the event of actuator saturation. The stability of the GPC control law without reconfiguration is first established using Riccati-based approach and state-space formulation. A novel reconfiguration strategy is developed for the systems which have actuator redundancy and are faced with actuator saturation type failure. An elegant reconfigurable control design is presented with stability proof. A numerical example with application to reconfigurable flight control is presented to demonstrate the results presented in the paper.


2016 ◽  
Vol 28 (5) ◽  
pp. 722-729 ◽  
Author(s):  
Zhe Guan ◽  
◽  
Shin Wakitani ◽  
Toru Yamamoto ◽  

[abstFig src='/00280005/15.jpg' width='300' text='Schematic figure of data-oriented GPC-PID controller' ] This paper presents a data-oriented technique for designing a proportional-integral-derivative (PID) controller based on a generalized predictive control law for linear unknown systems. In several control design approaches, a model-based control theory, which requires accurate modeling and identification of the plant, is used to calculate the control parameters. However, in higher-order systems and/or systems with an unknown time delay such as chemical industries and thermal industries, it is difficult to model or identify the plant accurately. Over the last decade, data-oriented techniques in which the online or offline data are utilized have been attracting considerable attention. Designing the controllers for unknown plants based on only the input/output data is the main feature of this technique. In this study, controller parameters are first obtained by using a generalized predictive control law with the data-oriented technique, and are converted to PID parameters from the practical point of view. The proposed method is validated experimentally using a real injection-molding machine. The results demonstrate the efficiency of the proposed method.


2001 ◽  
Author(s):  
R. Mehra ◽  
M. Wasikowski ◽  
R. Prasanth ◽  
R. Bennett ◽  
D. Neckels

Sign in / Sign up

Export Citation Format

Share Document