COMP0128 Robotic Control Theory and Systems
This database contains the 2018-19 versions of syllabuses.
Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).
Robotic Control Theory and Systems
The students will gain insight into robotics and autonomous systems control theory and practice, specifically: Control loops. damping, feedback and stability analysis with a working understanding about how these are used for navigating a robot within an environment;Insight into developing a working prototype of a control system for a robot that solves a specific task.
On successful completion of the module, a student will be able to:
- understand control systems for robots
- understand control sensitivity and feedback problems
- understand optimization of controllers
- programme with Matlab or Python or C++ and ROS
Availability and prerequisites
This module delivery is available for selection on the below-listed programmes. The relevant programme structure will specify whether the module is core, optional, or elective.
In order to be eligible to select this module as optional or elective, where available, students must meet all prerequisite conditions to the satisfaction of the module leader. Places for students taking the module as optional or elective are limited and will be allocated according to the department’s module selection policy.
Programmes on which available:
There are no formal prerequisites.
The aim of this module is to provide the basic theory required for solving control problems in robotics and autonomous systems from a practitioner's point of view.
The module presents theory and methodology for analysis and modelling of systems and signals, and methods for design and synthesis of feedback controllers. Special emphasis is placed on:
- Control of systems with multiple inputs and outputs.
- Fundamental control performance and sensitivity and robustness in feedback systems.
- Synthesis of controllers through optimization.
- Predictive control with constraints.
In all cases, a theoretical treatment in lectures will be accompanied by corresponding practical exercises in either simulation or reality, in which students can exercise their skills.
An indicative reading list is available via http://readinglists.ucl.ac.uk/departments/comps_eng.html.
The module is delivered through a combination of lectures, tutorials, seminars, written and programming exercises, and project work.
This module delivery is assessed as below:
Written examination (2hrs)
Practical exercise 1
Practical exercise 2
Mathematical exercise 1
Mathematical exercise 2
Mathematical exercise 3
Mathematical exercise 4
In order to pass this module delivery, students must achieve an overall weighted module mark of 50%.