| CODE | SCE5204 | ||||||||||||
| TITLE | Adaptive and Intelligent Control | ||||||||||||
| UM LEVEL | 05 - Postgraduate Modular Diploma or Degree Course | ||||||||||||
| ECTS CREDITS | 5 | ||||||||||||
| DEPARTMENT | Systems and Control Engineering | ||||||||||||
| DESCRIPTION | This study-unit presents two different but complementary methodologies for analyzing and designing controllers which exhibit self-regulation or self-learning properties; namely Adaptive Control and Intelligent Control. These controllers can guarantee good levels of performance despite the presence of uncertain dynamics in the system being controlled. The uncertainty can be due to complexity or unpredictable variations in the system's physical structure and parameters. Intelligent Control methods can handle higher levels of uncertainty than Adaptive Controllers and make use of techniques derived from Computational Intelligence such as neural networks and fuzzy logic. These two types of controllers endow the system with characteristics that are normally attributed to human adaptability and intelligence, thereby leading to sophisticated and accurate levels of control. Study-Unit Aims The aims of this study-unit are to: - distinguish between and motivate the use of Adaptive Control and Intelligent Control; - present the two main approaches to Adaptive Control namely: Model Reference Adaptive Control and Self-tuning Control; - address issues concerning robustness of adaptive controllers in the presence of disturbances and time-varying parameters; - present applications of Adaptive Control and case studies; - distinguish between functional uncertainty and parametric uncertainty and explain the levels of complexity which justify the use of Intelligent Control as opposed to classical control or Adaptive Control; - present the three main approaches to Intelligent Control namely: neural network control, fuzzy logic control and genetic adaptive control; - present applications of Intelligent Control and case studies. Learning Outcomes 1. Knowledge & Understanding By the end of the study-unit the student will be able to: - distinguish between non-adaptive, adaptive and intelligent control methodologies; - recognize scenarios which require the use of Adaptive or Intelligent Control design; - explain and distinguish between functional and parametric uncertainty, adaptation and learning; - comprehend and select the appropriate adaptive or intelligent control design technique(s) to be applied when presented with a control problem whose plant is subject to unpredictable uncertainty. 2. Skills By the end of the study-unit the student will be able to: - select, explain and design an appropriate controller when presented with a control scenario whose plant is subject to uncertainty and which needs to be controlled autonomously; - design and implement the following Adaptive Controllers: Model Reference Adaptive Control, Self-tuning Control, Adaptive Predictive Control; - design and implement the following Intelligent Controllers: Neural Network Control, Fuzzy Logic Control, Genetic Adaptive Control. Main Text/s and any supplementary readings Main Texts: - K. Astrom, B. Wittenmark, 2008. Adaptive Control (2nd ed), Dover Publications. - K. Passino, 2004. Biomimicry for optimization, control and automation, Springer. |
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| LECTURER/S | Simon G. Fabri |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2024/5. It may be subject to change in subsequent years. |
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