Performance Standards in Dynamics

1977 ◽  
Vol 99 (2) ◽  
pp. 118-122
Author(s):  
N. Komaroff
Keyword(s):  
Control System ◽  
Phase Space ◽  
Dynamical Systems ◽  
System Performance ◽  
Performance Standards ◽  
Design Specifications ◽  
Analysis And Synthesis ◽  
Comprehensive Manner ◽  
Averaging Functions ◽  
And Control

A method to evaluate the performance of dynamical systems governed by ordinary differential equations is presented. It is based on averaging functions describing system behaviour (e.g. velocities) over prescribed domains (e.g. surfaces) in phase space. Quantitative measures of motion are introduced to indicate e.g. how oscillatory or how monotone would be the response following a disturbance. Examples demonstrate how these measures serve as new design specifications whose role is to define, compare and control system performance in a more comprehensive manner. Another application of the work is to qualitative studies in both the analysis and synthesis contexts.

An Integrated Design Approach of Local Control System of a Linear Drive Single Facet Heliostat

2016 ◽  
Author(s):  
M. M. Nageb ◽  
A. A. El-Samahy ◽  
M. A. Rady ◽  
A. M. A. Amin ◽  
R. H. Abd El-Hamid ◽  
...  
Keyword(s):  
Control System ◽  
System Performance ◽  
Integrated Design ◽  
Control Design ◽  
Drive System ◽  
Solar Power Plant ◽  
Central Receiver ◽  
Design Variables ◽  
Integrated Design Approach ◽  
And Control

In a central receiver solar power plant, heliostats are arranged with respect to the central receiver so as to reflect the rays from the sun onto the power tower with high precision by tracking the sun in both the azimuth and elevation directions. The master control system of a solar power plant consists of different levels. The first level is local control; it takes care of the positioning of the heliostats when the aiming point and the time are given to the system, and informs upper level about the status of the heliostats field. The second logic level makes some important dispatch calculations of heliostats field. The most popular linear two-axis local driving system of heliostat consists of two linear driving actuators, the driving mechanism with rotary joints, and the controller. Traditional methods for heliostat design are often based on a sequential approach in which the mechanical structure is designed first and then the control system is advised. In order to reach the optimal design of heliostats, an integrated design approach that concurrently considers the interactions between the mechanical and control subsystems is necessary. In this article, an integrated design methodology of heliostat drive system is presented. The methodology is based on modeling and simulation. The dynamic models that describe the behavior of the mechanical and control components are presented. These models involve mechanical and control design variables such as the motor parameters, power screw (including back lash), heliostat mass, load forces, and wind forces. Matlab, Solidwork, and Simulink are chosen to apply PID tracking control to heliostats, due to the ability to arbitrarily model complex mechanical systems, directly import properly constructed, third-party 3D CAD models, simulate integrated control, handle a variety of robotics nomenclature, and other features. The present methodology is employed for integrated design of a single facet small size heliostat with mirror area of 3 m2.The methods described in this article also show a way to rapidly simulate novel and complex heliostat geometries. Analysis of the heliostat drive system performance and dynamic characteristics according to mechanical and control design variables is conducted for the purpose of control system design and performance optimization. The drive system performance is evaluated in terms of positioning tracking errors, system response, and control system behavior. It is shown that the mechanical characteristics of the ball power screw actuator such as ball-screw diameter, lead, overall flexibility, stiffness, backlash, and inertia significantly influence the performance of drive system.

Guidance, Navigation, and Control System Performance Trades for Mars Pinpoint Landing

2010 ◽  
Vol 47 (1) ◽  
pp. 188-198 ◽  
Author(s):  
Bradley A. Steinfeldt ◽  
Michael J. Grant ◽  
Daniel A. Matz ◽  
Robert D. Braun ◽  
Gregg H. Barton
Keyword(s):  
Control System ◽  
System Performance ◽  
Navigation And Control ◽  
And Control

Pointing and control system performance and improvement strategies for the SOFIA Airborne Telescope

2016 ◽  
Author(s):  
Friederike Graf ◽  
Andreas Reinacher ◽  
Holger Jakob ◽  
Ulrich Lampater ◽  
Enrico Pfueller ◽  
...  
Keyword(s):  
Control System ◽  
System Performance ◽  
Improvement Strategies ◽  
And Control

Structure and Control on FSM Subsystem in Precision Tracking

2014 ◽  
Vol 624 ◽  
pp. 449-453
Author(s):  
Guang Hua Wu ◽  
Hang Li ◽  
Jun Xing Li ◽  
Yong Hui Wang
Keyword(s):  
Control System ◽  
Detailed Analysis ◽  
Experimental Model ◽  
High Precision ◽  
System Performance ◽  
Servo Control ◽  
Fast Speed ◽  
Tracking Technique ◽  
Precision Tracking ◽  
And Control

According to the characteristics of Fast Speed Mirror, the paper discusses that, in a FSM composite axis control system, the mechanism of the servo control, the main system performance, the speed loop of subsystem and effects of automatic zero locking system. Combined with traditional methods, a new structure of axial subsystem is proposed, to improve the rapid high-precision tracking technique. From theory to experimental model, the paper made a detailed analysis.

Use of Simulated Annealing for Adaptive Control System

2013 ◽  
Vol 2 (3) ◽  
pp. 42-54 ◽  
Author(s):  
Tran Trong Dao ◽  
Ivan Zelinka ◽  
Vo Hoang Duy
Keyword(s):  
Artificial Intelligence ◽  
Adaptive Control ◽  
Simulated Annealing ◽  
Control System ◽  
Dynamical Systems ◽  
Adaptive Control System ◽  
And Control

This work deals with using a method of artificial intelligence, mainly the generic probabilistic meta-algorithm can be used in such a difficult task which is analyzed and control of dynamical systems. Simulated annealing (SA) is used in this investigation. The adaptive control system was used in simulations with optimization by Simulated Annealing and the results are presented in graphs.

Symbolic Computation of Quantities Associated With Time-Periodic Dynamical Systems

2015 ◽  
Author(s):  
W. Grant Kirkland ◽  
S. C. Sinha
Keyword(s):  
Control System ◽  
Dynamical Systems ◽  
System Design ◽  
Symbolic Computation ◽  
Picard Iteration ◽  
Control System Design ◽  
Symbolic Form ◽  
Varying Coefficients ◽  
And Control ◽  
Time Periodic

Many dynamical systems can be modeled by a set of linear/nonlinear ordinary differential equations with periodic time-varying coefficients. The state transition matrix Φ(t,α) associated with the linear part of the equation can be expressed in terms of the periodic Lyapunov-Floquét transformation matrix Q(t,α) and a time-invariant matrix R(α). Computation of Q(t,α) and R(α) in a symbolic form as a function of system parameters α is of paramount importance in stability, bifurcation analysis, and control system design. In the past, a methodology has been presented for computing Φ(t,α) in a symbolic form, however Q(t,α) and R(α) have never been calculated in a symbolic form. Since Q(t,α) and R(α) were available only in numerical forms, general results for parameter unfolding and control system design could not be obtained in the entire parameter space. In this work a technique for symbolic computation of Q(t,α), and R(α) matrices is presented. First, Φ(t,α) is computed symbolically using the shifted Chebyshev polynomials and Picard iteration method as suggested in the literature. Then R(α) is computed using the Gaussian quadrature integral formula. Finally Q(t,α) is computed using the matrix exponential summation method. Using Mathematica, this approach has successfully been applied to the well-known Mathieu equation and a four dimensional time-periodic system in order to demonstrate the applications of the proposed method to linear as well as nonlinear problems.

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