scholarly journals Monitoring procedure for intelligent control: on-line identification of maximum closed-loop log modulus

1993 ◽  
Vol 32 (1) ◽  
pp. 90-99 ◽  
Author(s):  
Ren Chiou Chiang ◽  
Cheng Ching Yu
Keyword(s):  
Intelligent Control ◽  
Closed Loop ◽  
Line Identification ◽  
Monitoring Procedure ◽  
On Line

On-line Identification in Closed Loop

1991 ◽  
pp. 158-169
Author(s):  
Rolf Isermann
Keyword(s):  
Closed Loop ◽  
Line Identification ◽  
On Line

Intelligent Control of Uncertain PMSM Based on Stable and Adaptive Discrete-Time Neural Network Compensators

2021 ◽  
Vol 54 (4) ◽  
pp. 575-589
Author(s):  
Aziz El Janati El Idrissi ◽  
Mohsin Beniysa ◽  
Adel Bouajaj ◽  
Mohammed Réda Britel
Keyword(s):  
Neural Network ◽  
Intelligent Control ◽  
High Speed ◽  
Closed Loop ◽  
Permanent Magnet Synchronous Motor ◽  
Closed Loop System ◽  
Adaptive Neural Network ◽  
Control Scheme ◽  
On Line ◽  
Classical Vector

In this paper, stable and adaptive neural network compensators are proposed to control the uncertain permanent magnet synchronous motor (PMSM). Firstly, the overall uncertainties caused by mathematical modelling, parameters variation during operation and external load torque disturbances are modelled. Secondly, a new motion control scheme, where (d-q) current loops are dotted by two on-line tuning neural network compensators (NNCs), is used to compensate these uncertainties. As a result, the speed control loop is processed easily by proportional integral (PI) controller. Stability of the closed-loop system is also designed according to the Lyapunov stability. Compared to classical vector control, the simulations of PMSM system at different speeds including nominal, low and high speed, with and without uncertainties, show the effectiveness of the proposed control scheme.

Self-Tuning Control Application to Closed-Loop Servohydraulic Material Testing

1990 ◽  
Vol 112 (4) ◽  
pp. 680-689 ◽  
Author(s):  
S. R. Lee ◽  
K. Srinivasan
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Material Testing ◽  
Pole Placement ◽  
Radial Clearance ◽  
Loop Control ◽  
Line Identification ◽  
Self Tuning ◽  
Simulation And Experiment ◽  
On Line

Extensive reliance on manual controller tuning in closed-loop material testing applications makes such applications good candidates for self-tuning control implementation. The current work deals with the modeling, on-line identification, and self-tuning control of electrohydraulic servomechanisms used for closed-loop control of stroke, load, or strain involving low signal frequencies. The application to load and strain control results in servovalve operation close to null and increases the significance of nonideal aspects of servovalve operation such as valve mechanical null offset, valve overlap and radial clearance. Modifications in process modeling and on-line identification necessary to accommodate these aspects are described and shown to be effective by simulation and experiment. A pole-placement controller design approach is used for controller adaptation, the control algorithm being chosen based on analysis of robustness of the control system. The self-tuning control system is shown to be effective, by simulation and experiment.

On-Line Identification of Process Model Based on Swarm Intelligence Technology

2011 ◽  
Vol 403-408 ◽  
pp. 3216-3219 ◽  
Author(s):  
Li Ting Cao ◽  
Qi Bing Jin ◽  
Tong Shun Fan ◽  
Wei Su
Keyword(s):  
Process Model ◽  
Closed Loop ◽  
Estimation Algorithm ◽  
System Optimization ◽  
Step Response ◽  
Identification Methods ◽  
Identification Method ◽  
Line Identification ◽  
On Line ◽  
Intelligent Technology

On-line identification problem of process model was discussed in this paper, which use warm intelligent technology. An on-line identification method based on HPSO-Rosenbrock parameter estimation algorithm is proposed to solve the problem that traditional identification methods cannot be used in continuous-time systems on closed-loop step response conditions. This identification method is a combined method of a modified PSO and Rosenbrock which can make full use of global search ability of PSO and local search ability of Rosenbrock. Identification results of HPSO-Rosenbrock algorithm were made and compared with the other identification methods. The simulation and compare results show that the on-line identification method proposed in this paper is an approximate unbiased and effective identification method. This method can be successfully applied to closed-loop identification under secious noise and big dead-time object which provides a new idea for system optimization and advanced control.

New closed-loop on-line identification technique for updating the dynamic matrix

2001 ◽  
Vol 34 (25) ◽  
pp. 329-334
Author(s):  
Eduardo Shigueo Hori ◽  
Wu Hong Kwong
Keyword(s):  
Closed Loop ◽  
Dynamic Matrix ◽  
Line Identification ◽  
Identification Technique ◽  
On Line

On-Line Identification of Process Models in Closed-Loop Material Testing

1989 ◽  
Vol 111 (2) ◽  
pp. 172-179 ◽  
Author(s):  
S. R. Lee ◽  
K. Srinivasan
Keyword(s):  
Process Model ◽  
Closed Loop ◽  
Material Testing ◽  
Process Models ◽  
Identification Schemes ◽  
Test Conditions ◽  
Line Identification ◽  
Simulation And Experiment ◽  
On Line ◽  
Command Signals

On-line identification of process models in mechanical material testing situations is considered here. The identification is to be performed under closed loop test conditions and using normally available command signals. Process model forms appropriate for a variety of material testing situations are developed here. The performance of on-line identification schemes is evaluated for some material testing situations, using simulation and experiment. The identification schemes are successful in performing parameter estimation using simple process models.

Sign in / Sign up

Export Citation Format

Share Document