Modeling and Compensation of Nonlinear Systems Using Sensitivity Analysis

1968 ◽  
Vol 90 (2) ◽  
pp. 187-194
Author(s):  
J. G. Thompson ◽  
R. H. Kohr
Keyword(s):  
Sensitivity Analysis ◽  
Nonlinear Systems ◽  
Performance Index ◽  
Characteristic Parameter ◽  
Sensitivity Equation ◽  
System Sensitivity ◽  
System Equation ◽  
Sensitivity Functions ◽  
Minimization Procedure ◽  
Free Parameters

In this paper sensitivity analysis techniques are applied to two aspects of the nonlinear system design problem: The modeling of nonlinear systems and the compensation of nonlinear systems. In the modeling problem the free parameters of the model are selected to minimize an integral performance index where the integrand is a function of the response of the model and the response of the modeled system. Sensitivity functions, which indicate the sensitivity of the response of the model to changes in the free parameters are used in the minimization procedure. Similarly, in the compensation problem, the adjustable parameters of the compensated system are selected to minimize an integral performance index where the integrand is a function of the response of the compensated system and a desired response. Sensitivity functions, which indicate the sensitivity of the response of the compensated system to changes in the adjustable parameters, are again used in the minimization procedure. The sensitivity functions are obtained from multiple solutions of the general sensitivity equation subjected to various forcing functions. The general sensitivity equation is obtained by differentiation of the model equation or of the compensated system equation. The free or the adjustable parameters are determined as functions of some characteristic parameter which represents the magnitude of the input, the degree of the nonlinearity or some other performance characteristic of the system. All the required computations may be performed by a digital computer. Three nonlinear examples are given to illustrate the method.

Quadratic Sensitivity Analysis of Fixtures and Locating Schemes for Rigid Parts

2000 ◽  
Vol 123 (3) ◽  
pp. 462-472 ◽  
Author(s):  
Johan S. Carlson
Keyword(s):  
Sensitivity Analysis ◽  
Numerical Experiments ◽  
Geometric Constraints ◽  
Fixture Design ◽  
Practical Relevance ◽  
Sensitivity Equation ◽  
Relative Gain ◽  
Contact Points ◽  
Scheme Evaluation ◽  
Error Interaction

The main purpose of locating schemes are to position parts. The locating scheme utilizes tooling elements, referred to as locators, to introduce geometric constraints. A rigid part is uniquely positioned when it is brought into contact with the locators. By using kinematic analysis we derive a quadratic sensitivity equation that relates position error in locators with the resulting displacement of the part held by the locating scheme. The sensitivity equation which depends on the locator positions and the workpiece geometry around the contact points can be used for locating scheme evaluation, robust fixture design, tolerancing and diagnosis. The quadratic sensitivity equation derived in this paper is novel by adequate dealing with locator contact at nonprismatic surfaces, nonsmall errors, locator error interaction effects and locator errors in arbitrary directions. Theory for comparing the relative gain in precision by using the quadratic sensitivity equation instead of the linear is developed. The practical relevance of the quadratic sensitivity equation is tested through numerical experiments.

Developments in Nonlinear Controller Synthesis: An Overview

1978 ◽  
Vol 100 (1) ◽  
pp. 59-69 ◽  
Author(s):  
Devendra P. Garg
Keyword(s):  
Functional Analysis ◽  
Nonlinear Systems ◽  
Performance Improvement ◽  
Performance Index ◽  
Controller Synthesis ◽  
Analysis Approach ◽  
Nonlinear Controller ◽  
System Synthesis ◽  
Synthesis Techniques ◽  
Nonlinear Controllers

In this paper developments in nonlinear controller synthesis techniques are surveyed. First, the use of functional analysis approach for system synthesis is discussed. Next, the application of intentional nonlinear controllers for performance improvement and optimization via performance index minimization is presented. This is followed by a discussion of signal stabilization using artificial dither. Finally, approaches are given for design of controllers to meet stability requirements for both single and multiple-loop nonlinear systems.

Design Sensitivity Analysis for the Meshfree Shell Structure

2001 ◽  
Author(s):  
Kyung K. Choi ◽  
Nam H. Kim ◽  
Mark E. Botkin
Keyword(s):  
Sensitivity Analysis ◽  
Shell Structure ◽  
Design Sensitivity ◽  
Design Sensitivity Analysis ◽  
Analysis Method ◽  
Sensitivity Equation ◽  
Material Derivative ◽  
Design Variables ◽  
Sensitivity Analysis Method ◽  
Shell Formulation

Abstract A unified design sensitivity analysis method for a meshfree shell structure with respect to sizing, shape, and configuration design variables is presented in this paper. A shear deformable shell formulation is characterized by a CAD connection, thickness degeneration, meshfree discretization, and nodal integration. The design variable is selected from the CAD parameters, and a consistent design velocity field is then computed by perturbing the surface geometric matrix. The material derivative concept is used to obtain a design sensitivity equation in the parametric domain. Numerical examples show the accuracy and efficiency of the proposed design sensitivity analysis method compared to the analytical solution and the finite difference solution.

scholarly journals Some Aspects of Sensitivity Analysis in Variational Data Assimilation for Coupled Dynamical Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-22 ◽  
Author(s):  
Sergei Soldatenko ◽  
Peter Steinle ◽  
Chris Tingwell ◽  
Denis Chichkine
Keyword(s):  
Sensitivity Analysis ◽  
Dynamical Systems ◽  
Data Assimilation ◽  
Weather Prediction ◽  
Computational Cost ◽  
Variational Data Assimilation ◽  
Practical Implementation ◽  
Parameter Uncertainties ◽  
Sensitivity Functions ◽  
Sensitivity Analysis Method

Variational data assimilation (VDA) remains one of the key issues arising in many fields of geosciences including the numerical weather prediction. While the theory of VDA is well established, there are a number of issues with practical implementation that require additional consideration and study. However, the exploration of VDA requires considerable computational resources. For simple enough low-order models, the computational cost is minor and therefore models of this class are used as simple test instruments to emulate more complex systems. In this paper, the sensitivity with respect to variations in the parameters of one of the main components of VDA, the nonlinear forecasting model, is considered. For chaotic atmospheric dynamics, conventional methods of sensitivity analysis provide uninformative results since the envelopes of sensitivity functions grow with time and sensitivity functions themselves demonstrate the oscillating behaviour. The use of sensitivity analysis method, developed on the basis of the theory of shadowing pseudoorbits in dynamical systems, allows us to calculate sensitivity functions correctly. Sensitivity estimates for a simple coupled dynamical system are calculated and presented in the paper. To estimate the influence of model parameter uncertainties on the forecast, the relative error in the energy norm is applied.

scholarly journals A nonlinear plate control without linearization

2017 ◽  
Vol 15 (1) ◽  
pp. 179-186
Author(s):  
Kenan Yildirim ◽  
Ismail Kucuk
Keyword(s):  
Optimal Control ◽  
Nonlinear Systems ◽  
Control Problem ◽  
Performance Index ◽  
Control Function ◽  
Initial Boundary ◽  
Quadratic Functional ◽  
Penalty Term ◽  
Nonlinear Plate ◽  
Optimal Control Function

Abstract In this paper, an optimal vibration control problem for a nonlinear plate is considered. In order to obtain the optimal control function, wellposedness and controllability of the nonlinear system is investigated. The performance index functional of the system, to be minimized by minimum level of control, is chosen as the sum of the quadratic 10 functional of the displacement. The velocity of the plate and quadratic functional of the control function is added to the performance index functional as a penalty term. By using a maximum principle, the nonlinear control problem is transformed to solving a system of partial differential equations including state and adjoint variables linked by initial-boundary-terminal conditions. Hence, it is shown that optimal control of the nonlinear systems can be obtained without linearization of the nonlinear term and optimal control function can be obtained analytically for nonlinear systems without linearization.

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