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Title: Adaptive control and monitoring of a C.N.C. lathe using feed-force and machine-vision
Author: Daneshmend, Laeeque Khan
Awarding Body: University of London
Current Institution: Imperial College London
Date of Award: 1985
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This thesis examines some aspects of adaptive control and machine monitoring for Computer Numerically Controlled (CNC) lathes. The design and implementation of a distributed, axls-partioned, multi-microprocessor based CNC system is described in Chapter 2. This CNC system, retrofitted to a lathe, has been developed specifically as a test-bed for research into advanced control and machine monitoring techniques. Chapter 3 is a survey of adaptive control and monitoring techniques for machine tools in general. The next three chapters are devoted to the parameter adaptive control of feed force. Chapter 4 presents some basic analysis of the position and force control loops on the lathe. Chapter 5 looks at parameter adaptive control theory in general, and at a design technique for model reference adaptive control of discrete-time single-input/single-output plants in particular. This design technique is applied to the feed force regulation problem, using feedrate as the control input. Results of applying several feed force regulation algorithms, derived from the design technique of Chapter 5. are presented in Chapter 6. The use of machine vision for flank wear measurement of turning tools Is investigated in Chapter 7. Experimental results and Image processing algorithms are presented.
Supervisor: Pak, H. A. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available