The numerical control of machines. Control input data

2015 ◽  
1986 ◽  
Vol 108 (3) ◽  
pp. 215-222 ◽  
Author(s):  
L. K. Daneshmend ◽  
H. A. Pak

This paper applies the discrete-time single-input/single-output Model Reference Adaptive Control (MRAC) design technique of Landau and Lozano to the problem of regulating feed force on a lathe under varying cutting conditions. A first-order model is used to represent the relationship between feed force and the control input (feedrate). The MRAC scheme is implemented on a multi-microprocessor based computer-numerical-control system. Results of applying various algorithms derived from the MRAC design technique are presented.


2021 ◽  
Author(s):  
Quan-Fang Wang

In this work, time-depended Schrodinger equation described particles at matter (crystal, catalysis, metal) surface could be considered as propose of numerical control of quantum system. Accessing existing physical experimental results on the motion of particles (molecules, atoms) at surface, based on variational method of quantum control theory in Hilbert space, using density function theory (DFT), time-depended Schrodinger equation to proceed the investigation of computational approach. To do quantum calculation at surface, physically, first needs a concept as control goal: such as breaking a chemical bond as target; reducing energy of high intensity shaped laser pulse. Particles at surface is a kind of constrain control for spatial variable. Optimal control is to find and characterize the quantum optima for minimizing or maximizing the cost functional. Control methods contain selecting chemical reagent, designing chemical reaction, making control scope for a quantized system: time varying Schrodinger equation. Precisely, for general quadratic cost function, in two or three dimensional cases, a semi discrete (time continuous, spatial discrete) algorithm consisting of finite element method and conjugate gradient method, would be utilized for solving a numerical solution of state system, and obtaining quantum optimal control from a initial guess of control input. It is quite curious: what is the difference of control particles occurred at surface than control free particles? whether one can develop a suit of theory or methodology for quantum surface control? It is certainly expected to connect theoretical control, to numerical or computational control, and to experimental control as carrying out quantum system control of particles on the surface. It is desired that quantum control theory (QCT) for quantum dot at surface would be evidenced in visualization method, and attained confidential verification in the guidance of real-time computer-aided experiments in the viewpoint of chemistry and physics.


2021 ◽  
Author(s):  
Quan-Fang Wang

In this work, time-depended Schrodinger equation described particles at matter (crystal, catalysis, metal) surface could be considered as propose of numerical control of quantum system. Accessing existing physical experimental results on the motion of particles (molecules, atoms) at surface, based on variational method of quantum control theory in Hilbert space, using density function theory (DFT), time-depended Schrodinger equation to proceed the investigation of computational approach. To do quantum calculation at surface, physically, first needs a concept as control goal: such as breaking a chemical bond as target; reducing energy of high intensity shaped laser pulse. Particles at surface is a kind of constrain control for spatial variable. Optimal control is to find and characterize the quantum optima for minimizing or maximizing the cost functional. Control methods contain selecting chemical reagent, designing chemical reaction, making control scope for a quantized system: time varying Schrodinger equation. Precisely, for general quadratic cost function, in two or three dimensional cases, a semi discrete (time continuous, spatial discrete) algorithm consisting of finite element method and conjugate gradient method, would be utilized for solving a numerical solution of state system, and obtaining quantum optimal control from a initial guess of control input. It is quite curious: what is the difference of control particles occurred at surface than control free particles? whether one can develop a suit of theory or methodology for quantum surface control? It is certainly expected to connect theoretical control, to numerical or computational control, and to experimental control as carrying out quantum system control of particles on the surface. It is desired that quantum control theory (QCT) for quantum dot at surface would be evidenced in visualization method, and attained confidential verification in the guidance of real-time computer-aided experiments in the viewpoint of chemistry and physics.


1998 ◽  
Vol 120 (1) ◽  
pp. 111-116 ◽  
Author(s):  
Min-Shin Chen

This paper proposes a new tracking control design for linear time-varying systems. The proposed control input, which is in the span of finitely many preselected input data, minimizes the L2-norm of the output tracking error. The more input data is used, the less L2-norm of the tracking error is achieved. The design of the new controller, which consists of a feedforward controller and a discretized state feedback loop, requires a finite-time preview of the system parameters and the reference trajectory. It is shown that as long as the preview time is longer than a critical value, the closed-loop stability is maintained irrespective of the stability property of the system’s zero dynamics. When the system parameters are periodically time-varying, the proposed design can be solely based on a set of experimental input and output data instead of on the exact information of system parameters.


2019 ◽  
Vol 13 (5) ◽  
pp. 700-707
Author(s):  
Isamu Nishida ◽  
◽  
Keiichi Shirase

The present study proposed a method to automatically generate a numerical control (NC) program by referring to machining case data for each machine tool with only 3D-CAD models of a product and workpiece as the input data, and to select machine tools for machining the target removal region among several machine tools with different characteristics. The special features of the proposed method are described as follows. The removal volume can be automatically obtained from the total removal volume (TRV), which is extracted from the workpiece and product using a Boolean operation by dividing it on the XY plane. The removal region changed according to the determined machining sequence. The conditions for machining the removal region is automatically determined according to the machining case data, which is stored by linking the geometric properties of the removal region with the machining conditions determined by experienced operators. Furthermore, an NC program is automatically generated based on the machining conditions. The machine tools for machining the target region are selected according to the predicted machining time of each machine tool connected by a network. A case study was conducted to validate the effectiveness of the proposed system. The results confirm that machining can be conducted using only 3D-CAD models as input data. It was suggested that the makespan would be shortened by changing the machining sequence from the optimized machining sequence when machining a plurality of products.


Author(s):  
R.A. Ploc ◽  
G.H. Keech

An unambiguous analysis of transmission electron diffraction effects requires two samplings of the reciprocal lattice (RL). However, extracting definitive information from the patterns is difficult even for a general orthorhombic case. The usual procedure has been to deduce the approximate variables controlling the formation of the patterns from qualitative observations. Our present purpose is to illustrate two applications of a computer programme written for the analysis of transmission, selected area diffraction (SAD) patterns; the studies of RL spot shapes and epitaxy.When a specimen contains fine structure the RL spots become complex shapes with extensions in one or more directions. If the number and directions of these extensions can be estimated from an SAD pattern the exact spot shape can be determined by a series of refinements of the computer input data.


Sign in / Sign up

Export Citation Format

Share Document