Optimization of Planar, Spherical and Spatial Function Generators Using Input-Output Curve Planning

1994 ◽  
Vol 116 (3) ◽  
pp. 915-919 ◽  
Author(s):  
Zheng Liu ◽  
J. Angeles
Keyword(s):  
Performance Index ◽  
General Scheme ◽  
Optimization Procedure ◽  
Output Curve ◽  
Input Output ◽  
Function Generation ◽  
Spatial Function ◽  
Function Generators ◽  
Design Requirements ◽  
A Performance

A general scheme for the optimization of planar, spherical and spatial bimodal linkages for function generation is proposed. The problem is solved here following two basic steps: (i) planning input-output ((I/O) curves based on design requirements and selecting data from the planned curve; and (ii) setting up an optimization procedure to minimize a performance index.

Optimization of Function-Generating Mechanisms Using Input-Output Curve Planning: Part I — Curve Planning and Data Preparation

1992 ◽  
Author(s):  
Zheng Liu ◽  
Jorge Angeles
Keyword(s):  
General Scheme ◽  
Optimization Procedure ◽  
Output Curve ◽  
Data Preparation ◽  
Input Output ◽  
Design Strategies ◽  
Design Data ◽  
Design Error ◽  
Structural Error ◽  
Design Requirements

Abstract A general scheme for the optimization of one-degree-of-freedom mechanisms for function generation is proposed in this and an accompanying paper. The problem is solved here following two basic steps: i) planning input-output curves based on design requirements (input-output pairs, mobility, time ratio, etc.) and selecting data from the planned curve; and ii) setting up an optimization procedure to minimize a performance index (design error or structural error). Discussed in Part I is the first step of the optimization scheme, i.e., design-data preparation based on input-output curve planning, while, in Part II, the ensuing formulation and design strategies.

Optimization of Function-Generating Mechanisms Using Input-Output Curve Planning: Part II — Formulation and Optimization Strategies

1992 ◽  
Author(s):  
Zheng Liu ◽  
Jorge Angeles
Keyword(s):  
Optimization Procedure ◽  
Second Step ◽  
Output Curve ◽  
Data Preparation ◽  
Input Output ◽  
Optimization Scheme ◽  
Design Data ◽  
Transmission Quality ◽  
Design Requirements ◽  
Defect Elimination

Abstract As a sequel to Part I, in which design-data preparation based on Input-output curve planning is discussed, Part II focuses on the second step of the optimization scheme. This step includes the basic formulation and some strategies, in the optimization procedure, for: i) transmission-quality evaluation; and ii) branch-defect elimination. Since design requirements on mobility conditions are already considered in the curve-planning phase, discussed in Part I, there is no need to introduce constraints pertaining to mobility type in the formulation, the procedure thus becoming remarkably simple.

Synthesis of Four-Bar Linkage Function Generators by Means of Equations of Motion

1965 ◽  
Vol 87 (2) ◽  
pp. 170-176 ◽  
Author(s):  
C. K. Wojcik
Keyword(s):  
Equations Of Motion ◽  
Angular Acceleration ◽  
Input Output ◽  
Connecting Rod ◽  
Function Generator ◽  
Function Generation ◽  
Function Generators ◽  
Two Parameters ◽  
Four Bar Linkage ◽  
Selection Of

The function generation method presented in this paper is based on consideration of the equations of motion of a four-bar linkage with an assumed input of θ˙1 = 1 rad/sec. For a specified input-output relationship, the task of synthesizing an appropriate four-bar linkage is reduced by this method to a problem of selecting two parameters: θ˙2—the angular velocity and θ¨2—the angular acceleration of the connecting rod. The selection of these parameters is governed by certain conditions imposed on the performance of the four-bar linkage function generator. Using this method, two specific problems are solved and discussed in detail.

A performance index for semicoherent structures

2004 ◽  
Vol 83 (3) ◽  
pp. 323-332 ◽  
Author(s):  
Francesc Carreras ◽  
Josep Freixas ◽  
María Albina Puente
Keyword(s):  
Performance Index ◽  
A Performance

State-Space Dynamic Performance Preview-Predictive Controller

2006 ◽  
Vol 129 (2) ◽  
pp. 144-153 ◽  
Author(s):  
Andrzej W. Ordys ◽  
Masayoshi Tomizuka ◽  
Michael J. Grimble
Keyword(s):  
State Space ◽  
Predictive Control ◽  
Performance Index ◽  
Dynamic Performance ◽  
Optimization Procedure ◽  
Control Algorithms ◽  
Optimization Approach ◽  
Linear Quadratic ◽  
Preview Control ◽  
Predictive Controller

The paper discusses state-space generalized predictive control and the preview control algorithms. The optimization procedure used in the derivation of predictive control algorithms is considered. The performance index associated with the generalized predictive controller (GPC) is examined and compared with the linear quadratic (LQ) optimal control formulation used in preview control. A new performance index and consequently a new algorithm is proposed dynamic performance predictive controller (DPPC) that combines the features of both GPC and preview controller. This algorithm minimizes the performance index through a dynamic optimization. A simple example illustrates the features of the three algorithms and prompts a discussion on what is actually minimized in predictive control. The DPPC algorithm, derived in this paper, provides for a minimum of the predictive performance index. The differences and similarities between the preview control and the predictive control have been discussed and optimization approach of predictive control has been explained.

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