scholarly journals Studies on Closed-loop Interaction in a Multi-loop Single Tank Control System

2018 ◽  
Vol 7 (3.26) ◽  
pp. 38
Author(s):  
Abhijeet Chourdhary ◽  
Amit Jain
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Transfer Functions ◽  
Test Method ◽  
Step Test ◽  
Flow Loop ◽  
Array Analysis ◽  
Relative Gain ◽  
Relative Gain Array ◽  
Tank System

This paper investigates the interaction between level and flow loop in a single tank system. The data generated is used to generate all transfer functions via step test method. The model generated is then simulated on MATLAB-Simulink and the obtained results are then compared with experimental results for verification. A Relative Gain Array analysis is performed to check the interaction and comment on the pairing.  

The Solution of a Problem of Speed of Response on Output Coordinate for Linear Dynamic Systems

2019 ◽  
Vol 20 (9) ◽  
pp. 532-541 ◽  
Author(s):  
V. I. Lovchakov ◽  
O. A. Shibyakin
Keyword(s):  
Control System ◽  
Closed Loop ◽  
Transfer Functions ◽  
Algebraic Method ◽  
Control Signal ◽  
Transient Processes ◽  
Linear Control Systems ◽  
Feedback Signal ◽  
Transient Time ◽  
Speed Of Response

The solution of the so-called problem of speed of response in one coordinate, which has important theoretical and practical importance, is investigated. It is formulated with reference to linear one-dimensional high-order control objects described by a system of ordinary differential equations in a certain phase space. The transient time tnn of the system designed is understood in a sense of the classical control theory in reference to one (output) coordinate of the object and is determined by using the zone Δ = σ* = 4.321 %, which equals the given (desirable) value of the overshoot of the system synthesized. This overshoot corresponds with the speed of response oscillating second-order element with a damping coefficient ζ= = 2 2 0,7071 / . It is indispensable to mention here that the equation Δ = σ is one of the necessary conditions for the maximum speed of response of the system with the oscillating character of transient processes. In accordance to this the task of the speed of response by one coordinate can be described by the following generalized formulation: one must find the linear algorithm of the feedback signal, which provides a preset order of the astatism na for the closed-loop control system and converts the control object from a zero state into a final state, which is determined by the constant signal of the input, with a minimal time value of the transient processes of the system tnn and the preset value of the overshoot σ m σ* while fulfilling the constraint of the control signal |u(t)| m umax. Nowadays the task mentioned is approximately solved by the algebraic method of the synthesis of linear control systems with the determination of a desirable transfer function of the designed closed-loop system based on model normalized transfer functions (NTF). In the works by Kim D. P. there was carried out the analysis of four types of normalized transfer functions characterized by the increased speed of response. In this work two additional types of normalized transfer functions are suggested, in comparison with mentioned NTF they have the increased speed of response in case of the preset value of the overregulation σ* = 4.321 %. On their basis and using the methodology of the modal control the method of the synthesis of the controller is suggested; this method ensures the transient time of the designed system to be close to the minimum in case of the preset constraint of the overregulation and the value of the control signal. It needs to be emphasized that in contrast to the algebraic method of the synthesis, this method is applied to a wider range of control objects: as to minimal-phased objects as to non-minimum-phased ones; as to the objects containing zeros as to those without them. The method is illustrated by an example of synthesis of control system speed of response of the fourth order, containing the results of its modeling.

Kinematics, Dynamics, and Control of Tendon-Driven Mechanisms Using Signal Flow Graphs

1998 ◽  
Author(s):  
Meng-Sang Chew ◽  
Theeraphong Wongratanaphisan
Keyword(s):  
Control System ◽  
Transfer Function ◽  
Closed Loop ◽  
Transfer Functions ◽  
Signal Flow ◽  
Signal Flow Graphs ◽  
Loop Transfer Function ◽  
Dynamics And Control ◽  
Flow Graphs ◽  
And Control

Abstract This paper presents the analysis of the kinematics, dynamics and controls of tendon-driven mechanism under the framework of signal flow graphs. For decades, the signal flow graphs have been applied in many areas, particularly in controls, for determining the closed-loop transfer function of a control system. The tendon-driven mechanism considered here consists of several subsystems including actuator-controller dynamics, mechanism kinematics and mechanism dynamics. Each subsystem will be derived and represented by signal flow graphs. The representation of the whole system can be carried out by connecting the graphs of subsystems at the corresponding nodes. Transfer functions can then be obtained by using Mason’s rules. A 3-DOF robot finger utilizing tendon-driven mechanism is used as an illustrative example.

scholarly journals Comparison of Steady State and Dynamic Interaction Measurements in Multiloop Control Systems

2005 ◽  
Vol 5 (1) ◽  
pp. 1 ◽  
Author(s):  
Renanto Handogo ◽  
Avon T. H. ◽  
Joko Lelono
Keyword(s):  
Control System ◽  
Steady State ◽  
Control Systems ◽  
Dynamic Process ◽  
Dynamic Interaction ◽  
Time Constants ◽  
Relative Gain ◽  
Relative Gain Array ◽  
Multiloop Control ◽  
Multiloop Control System

The applicability of the steady-state Relative Gain Array (RGA) to measure dynamic process interactions in a multiloop control system was investigated. Several transfer function matrices were chosen, and the gains, time constants, and dead times of their elements were varied to represent the systems with dominant dynamic interactions. It was shown that the steady-state RGA method predicted the controller pairing accurately if the pairing elements recommended by RGA had the bigger gains and the same or smaller time constants compared to other elements in the corresponding rows. When these conditions were not met, the RGA would give a wrong result, and dynamic interaction measurements, such as the Average Dynamic Gain Array (ADGA) and the Inverse Nyquist Array (lNA), should be used instead to determine the best controller pairing in a multiloop control system. Keywords: Control pairing, dynamic process interaction, multiloop control systems, Relative Gain Array (RGA), and steady state.

Modelling, Identification and Control of Thermal Deformation of Machine Tool Structures, Part 4: A Multi-Variable Closed-Loop Control System

1999 ◽  
Vol 121 (3) ◽  
pp. 509-516 ◽  
Author(s):  
S. Fraser ◽  
M. H. Attia ◽  
M. O. M. Osman
Keyword(s):  
Control System ◽  
Machine Tool ◽  
Thermal Deformation ◽  
Closed Loop ◽  
Transfer Functions ◽  
Closed Loop Control ◽  
Loop Control ◽  
Closed Loop Control System ◽  
Loop Control System ◽  
Machine Tool Structures

A multi-variable closed-loop control system is proposed to compensate for the thermal deformation of machine tool structures. The control system recognizes the fact the relative thermal displacement between the tool and workpiece is not accessible for direct measurement. Using the generalized thermoelastic transfer functions of the structure, which provide satisfactory input-output dynamic dependencies, the heat input to the structure and thermal displacements are estimated in real time. Artificial heating elements are used as the actuation mechanism of the control system, since they provide an economical solution for retrofitting existing conventional machine tools, and can also be combined with NC controllers to effect the desired compensation of the expansion and bending modes of deformation. Computer simulation test results indicated that even when the random temperature measurement and power actuation errors are taken in consideration, an accuracy of better than 2.5 μm and a control cycle of the order of 1 second are achievable.

Relative gain array analysis for uncertain process models

AIChE Journal ◽  
2002 ◽  
Vol 48 (2) ◽  
pp. 302-310 ◽  
Author(s):  
Dan Chen ◽  
Dale E. Seborg
Keyword(s):  
Process Models ◽  
Uncertain Process ◽  
Array Analysis ◽  
Relative Gain ◽  
Relative Gain Array
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