Synthesis of Multivariable Controller With Plant Test Data

1994 ◽  
Vol 116 (2) ◽  
pp. 309-313 ◽  
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Control System ◽  
Test Data ◽  
Open Loop ◽  
Loop System ◽  
Controller Synthesis ◽  
System Model ◽  
Multivariable Control ◽  
Open Loop System ◽  
Plant Test ◽  
Multivariable Controller

A method to synthesize decoupled multivariable control system from a batch of plant test data is introduced. The method is applicable when the system has more inputs than outputs and is open-loop stable. An advantage of this method is that explicit identification of an open-loop system model is not required for controller synthesis.

Control System Synthesis Based on Plant Test Data

1995 ◽  
Vol 117 (4) ◽  
pp. 484-489
Author(s):  
Jenq-Tzong H. Chan
Keyword(s):  
Control System ◽  
Test Data ◽  
Closed Loop ◽  
Explicit Knowledge ◽  
Linear Time ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop System ◽  
System Synthesis ◽  
Control System Synthesis

A correlation equation is established between open-loop test data and the desired closed-loop system characteristics permitting control system synthesis to be done on the basis of a numerical approach using experimental data. The method is applicable when the system is linear-time-invariant and open-loop stable. The major merits of the algorithm are two-fold: 1) Arbitrary placement of the closed-loop system equation is possible, and 2) explicit knowledge of an open-loop system model is not needed for the controller synthesis.

A Biological Feedback Control System with Electronic Input: The Artificially Closed Femur-Tibia Control System of Stick Insects

1986 ◽  
Vol 120 (1) ◽  
pp. 369-385 ◽  
Author(s):  
G. WEILAND ◽  
U. BÄSSLER ◽  
M. BRUNNER
Keyword(s):  
Control System ◽  
Feedback Control ◽  
Closed Loop ◽  
Stick Insect ◽  
Open Loop ◽  
Loop System ◽  
Chordotonal Organ ◽  
Closed Loop System ◽  
Open Loop System ◽  
Stick Insects

An experimental arrangement was constructed which is based on the open-loop femur-tibia control system of two stick insect species (Carausius morosus and Cuniculina impigra). It could be artificially closed in the following way: the position of the tibia was measured by an optical device and this value was used to drive a penmotor which moved the receptor apodeme of the femoral chordotonal organ in the same way as in intact animals. This arrangement allows direct comparison of the behaviour of the open-loop and the closed-loop system as well as introducing an additional delay. The Carausius system has a phase reserve of only 30°-50° and the factor of feedback control approaches 1 between 1 and 2 Hz. This agrees with the observation that an additional delay of 70–200 ms produces long-lasting oscillations of 1–2 Hz. The Cuniculina system has a larger phase reserve and consequently a delay of 200 ms produced no oscillations. All experiments show that extrapolation from the open-loop system to the closed-loop system is valid, despite the non-linear characteristics of the loop. Consequences for servo-mechanisms during walking and rocking movements are discussed.

Multi-Stage System Identification of a Gas Turbine

2017 ◽  
Author(s):  
Amit Pandey ◽  
Maurício de Oliveira ◽  
Chad M. Holcomb
Keyword(s):  
Gas Turbine ◽  
Closed Loop ◽  
Open Loop ◽  
Loop System ◽  
Closed Loop Control ◽  
Input Output ◽  
Open Loop System ◽  
Loop Control ◽  
Multi Stage ◽  
Identification Techniques

Several techniques have recently been proposed to identify open-loop system models from input-output data obtained while the plant is operating under closed-loop control. So called multi-stage identification techniques are particularly useful in industrial applications where obtaining input-output information in the absence of closed-loop control is often difficult. These open-loop system models can then be employed in the design of more sophisticated closed-loop controllers. This paper introduces a methodology to identify linear open-loop models of gas turbine engines using a multi-stage identification procedure. The procedure utilizes closed-loop data to identify a closed-loop sensitivity function in the first stage and extracts the open-loop plant model in the second stage. The closed-loop data can be obtained by any sufficiently informative experiment from a plant in operation or simulation. We present simulation results here. This is the logical process to follow since using experimentation is often prohibitively expensive and unpractical. Both identification stages use standard open-loop identification techniques. We then propose a series of techniques to validate the accuracy of the identified models against first principles simulations in both the time and frequency domains. Finally, the potential to use these models for control design is discussed.

Fretting Behavior of Coated and Treated Titanium Alloy Using an Open-Loop System

2005 ◽  
Author(s):  
G. R. Yantio Njankeu ◽  
J.-Y. Paris ◽  
J. Denape ◽  
L. Pichon ◽  
J.-P. Rivie`re
Keyword(s):  
Titanium Alloy ◽  
Relative Motion ◽  
High Frequency ◽  
Open Loop ◽  
Loop System ◽  
Test Apparatus ◽  
Open Loop System ◽  
Wear Rates ◽  
Low Wear

Titanium alloys are well known to present poor sliding behaviour and high wear values. Various coatings and treatments have been tested to prevent such an occurrence under fretting conditions at high frequency of displacement (100 Hz). An original test apparatus, using an open-loop system instead of a classical imposed displacement simulator, has been performed to directly display the phenomenon of seizure, defined as the stopping of the relative motion between the contacting elements. A classification of the tested coatings has been proposed on the basis of their capacity to maintain full or partial sliding conditions, to present low wear rates and to prevent seizure.

Teaching particle swarm optimization through an open-loop system identification project

2011 ◽  
Vol 22 (2) ◽  
pp. 227-237 ◽  
Author(s):  
Paulo Moura Oliveira ◽  
Damir Vrančić ◽  
J. Boaventura Cunha ◽  
E. J. Solteiro Pires
Keyword(s):  
Particle Swarm Optimization ◽  
System Identification ◽  
Particle Swarm ◽  
Open Loop ◽  
Loop System ◽  
Open Loop System ◽  
Swarm Optimization
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