Abstract:
The work presented in this thesis addresses the dynamical control systems regarding
manufacturing, industrial processing and transportation, in local and distributed
environment adapting simplified design techniques. This enhances the control
strategies giving multi-agents based autonomous capabilities. A new design model of
fuzzy logic discrete event (DEV) control system under time constrain is proposed and
implemented for industrial applications. Three systems: grinding and mixing fuzzy
logic time control system, liquids mixing fuzzy logic time control system, and multi-
dimensional supervisory control industrial processing system using fuzzy time control
are designed. In this regard, a simplified design approach is adapted to reduce the
complexity of memory based fuzzy systems and to enhance the controllability and
stability of the systems. Design of: fuzzifier, inference engine, rule base, deffuzifiers,
and DEV control system, is discussed. Time control fuzzy rules are formulated,
applied and tested using MATLAB simulation for the systems. The simulation results
of each proposed application are found in agreement with the design based calculated
results. For vehicles automation, multi-agents based autonomous railway vehicles
control model is designed. In this regard, a new speed scheduling, management and
control model is established to meet the requirements of modern autonomous train
systems. This research work proposes to develop a novel control system to enhance
the efficiency of the vehicles under constraints of various conditions: hard conditions;
junction track condition, track clearance, and crossing gates condition, flexible
conditions; environment monitoring, track condition, and tilting condition. Various
development techniques to establish the multi-agents based autonomous railway
vehicles control system are discussed and proposed for implementation using high
tech microelectronics technology.
The design and simulation work is carried out at the laboratories of GC University
Lahore Pakistan, and The School of Electronics and Engineering-SEE, Edinburgh
University U.K during research fellowship to work with system level integration
group SLIg using MATLAB-simulink, and Xilinx 10.1 suit for ISE and DSP tools.