What Will Learn?

• Course Aims

  Course Aims This course aims to: • Help the students to understand the hybrid control systems as applied on the hierarchical motion control and the DCS. • Understand the basic principles of state space and discrete time and event control systems. • Understand the coupling between logic-based components and continuous physical systems • Modeling, analysis, and design of systems that combine continuous dynamics with discrete logic • Presenting a modeling framework for hybrid systems that combines elements from automata theory and differential equations. • Present an overview of simulation tools for hybrid systems. For example, Simulink/Stateflow (MATLAB), Statechart (Labview), PN Simulators, …..etc.

Requirements

MCT211

Description

• English Description
  
  Introduction to hybrid control systems: basic concepts, time-driven versus event driven control systems, discrete event system, finite-state automata, hybrid control architecture. Review on modelling and automatic control fundamentals. Digital controllers design techniques in Z-domain and state space using pole placement. Design and control of discrete event mechatronic systems, GRAFCET, SFC, Petri-nets: basics, comparison of petri-nets and automata, control using Petri-nets. Design of fault diagnosis and supervisory control systems. Examples on hybrid system model and basic representation of mixed logical dynamical model. Case studies and applications of hybrid system applications in modelling, industrial and manufacturing.
• Arabic Description
  
  Introduction to hybrid control systems: basic concepts, time-driven versus event driven control systems, discrete event system, finite-state automata, hybrid control architecture. Review on modelling and automatic control fundamentals. Digital controllers design techniques in Z-domain and state space using pole placement. Design and control of discrete event mechatronic systems, GRAFCET, SFC, Petri-nets: basics, comparison of petri-nets and automata, control using Petri-nets. Design of fault diagnosis and supervisory control systems. Examples on hybrid system model and basic representation of mixed logical dynamical model. Case studies and applications of hybrid system applications in modelling, industrial and manufacturing.