This course provides a comprehensive overview of robotics for postgraduate level study. The course covers the fundamental concepts and methods to analyze, model, and control of robotic mechanisms. Specific topics include kinematics, inverse kinematics, dynamics, trajectory generation, individual and multivariable control, interaction force control, and sensors. Students will also involve in hands-on programming project to reinforce the basic principles developed in lectures as well as develop robot algorithm implementation skillsets. The course will also expose students to the latest and advanced developments in robotics such as medical robotics, dynamic parameter identification. (Equivalent to BMEG5100.)

Linear system theory and design is the core of modern control approaches, such as optimal, robust, adaptive and multivariable control. This course aims to develop a solid understanding of the fundamentals of linear systems analysis and design using the state space approach. Topics covered include state space representation of systems; solution of state equations; stability analysis; controllability and observability; linear state feedback design; observer and compensator design, advanced multivariable control systems design, decoupling and servo control. This course is a must for higher degree students in control engineering, robotics or servo engineering. It is also very useful for those who are interested in signal processing and computer engineering.

This course provides a broad overview of microfabrication and microelectromechanical systems. Topics include introduction to basic micromaching techniques such as photolithography; isotropic and anisotropic wet etching; dry etching; physical and chemical vapor deposition; electroplating; metrology; statistical design of experiments; MEMS release etching; stiction; and MEMS device testing. The course also reviews important microsensors, microactuators and microstructures. Topics include accelerometers; pressure sensor; optical switches; cantilever beams; thin-film stress test structures and bulk micromaching test structures. Lastly, the course introduces the fundamentals of central dogma of molecular biology; cell and tissue biology; and principles of transduction and measurements of molecules, cells and tissues.

Geometric computing tools have been widely used in modern product design and realization, such as all kinds of Computer-Aided Design (CAD), Computer-Aided Manufacturing (CAM) and Computer-Aided Engineering (CAE) software systems. However, the capability of simply using these CAD, CAM and CAE software systems is not sufficient for future products design and manufacturing. This course aims to help students in understanding the principles of geometric computing behind CAD, CAM and CAE systems, and provides students with deep understanding of computational techniques and practical experience in developing novel computational design and manufacturing applications.

This course consists of two parts. The first part is analysis of nonlinear systems, which includes state space description of nonlinear control systems, phase plane analysis of second order dynamic systems, Lyapunov‘s stability theory such as Lyapunov’s first method, second method, Barbalat’s lemma, and total stability. The second part is design of nonlinear control systems, which includes Jacobian linearization, feedback linearization, sliding mode control, and backstepping method.

The contents of this course include overview of smart materials technology, characteristics of smart materials such as piezoelectric materials, magnetorheological fluids, and shape memory alloys. It covers smart actuators and sensors; structural modelling and design; dynamics and control for smart structures; integrated system analysis; and applications in biomedical devices, precision machinery, transportation, and buildings.

This course aims to teach students a range of classical and state-of-the-art topics through a series of examples. The focus will be on how different fundamental topics, such as linear and non-linear control, optimization, path planning, visual servo control, robot kinematics and dynamics, and machine learning, are applied through practical applications within robotics. Different application scenarios that may be used to show different fundamental topics include: mobile manipulation, bio-inspired and humanoid robots, robotic walking, rehabilitation robotics, medical and surgical robots, cable-driven robots, and autonomous ground, water and aerial vehicles.

The field of quantum information science includes quantum control and quantum information. It is a new area of inter-disciplinary research involving physicists, computer scientists, mathematicians and engineers. The course is an introduction to this rapidly expanding field. It covers basic quantum mechanics including quantum entanglement and quantum measurement; the modeling and control of quantum mechanical systems; quantum error correction; quantum communication and quantum information theory.

This course provides both fundamental knowledge of nanomaterials and nanotechnology and advanced topics related to applications. These topics cover basic principles, which include the scaling law, the surface science for nanomaterials, observation and characterization tools for nanomaterials, the nanofabrication techniques, building blocks for nanodevices and systems, etc. In the second half of this course, advanced topics on applying nanomaterials and nanotechnology for applications in mechanical engineering, energy engineering and biomedical engineering will be covered.

Mechanics is the foundation of many emerging research and engineering topics. With the rapid advancement in computing power, numerical methods are preferred to solve differential equations governing the physical process. It opens a whole new domain in industrial design, manufacturing process analysis, material behaviour prediction, etc. This course covers theoretical fundamentals in computational mechanics, including continuum mechanics, finite element methods, and computational plasticity. In addition, the course will also introduce practical skills to applying computational mechanics in research, including multi-physics simulation and advanced finite element simulation techniques.

This course focuses on a suite of materials characterization techniques that are useful in energy and environmental sciences. The main targets of these techniques include functional materials that are used in energy and environmental applications as well as solid, liquid, and gas samples that are involved in energy production and conversion, and pollution monitoring and control. The techniques include mass spectrometry (MS), gas chromatography (GC), high performance liquid chromatography (HPLC), nuclear magnetic resonance (NMR), infrared (IR) spectroscopy, Raman spectroscopy, X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), electron microscopy, and X-ray absorption fine structure (XAFS) spectroscopy. Students will receive lectures on the theory and operation principle of each technique as well as its limitations, and obtain hands-on experience with some of the techniques in supplemental lab sessions.

This course will cover advanced topics in heat transfer and fluid mechanics including overview of macroscopic theory of heat transfer, microscopic picture of heat carriers and their transport, micro- and nanoscale energy transport in solids, chemical thermodynamics, chemical kinetics, multicomponent and multiphase mixtures, basic principles of computational fluid dynamics, turbulence modeling, and airflow simulation in enclosed environments.

This course provides a theoretical and practical guidance on how to design parts to gain the maximum benefit from what additive manufacturing (AM) can offer. It begins by describing the main AM technologies and their respective advantages and disadvantages. It then examines strategic considerations in the context of designing for additive manufacturing (DfAM), such as designing to avoid anisotropy, designing to minimize print time, and post-processing, before discussing the economics of AM. The course then focuses on computational tools for design analysis and the optimization of AM parts, part consolidation, and tooling applications. Both designing for polymer AM and metal AM and its corresponding design guidelines will be provided. The main benefit of the course is its combined theoretical and practical approach, which provides directly applicable, “hands-on” information and insights to help students adopt AM in their daily practice.

This course focuses on the technologies for the modeling and visualization of 3D objects. This includes topics on the transformation of objects and coordinate systems. Techniques for the representation of free form curves and surfaces including parametric cubic, Bezier, B-spline, and NURBS will be covered. Techniques for modeling trimmed surface will also be studied. The basic theory of solid modeling and representation schemes will be covered. The Constructive Solid Geometry and the Boundary Representation scheme will be studied. The basic concept for the generation of machining tool paths will be covered. There will also be an introduction to feature based design.

This course will be offered to cover the knowledge of computer interface, including sensor, actuators, haptics, and human-computer interaction methods. To support the usage of human-computer interface, methods for 3D object modeling, deformation and simulation will be taught to make an integrated interaction and simulation system.

This course provides students with theoretical backgrounds of computer vision. It will cover the following topics: imaging models; segmentation; pose estimation by visual means; 3D shape estimation by stereo vision; camera and stereo calibration; and motion tracking. A wide variety of case studies and practical applications in engineering are also included.

This course is designed to equip students with the knowledge of modern control systems analysis and design, and skills of control theory for practical applications of industrial automation systems. It will cover the following topics: state space representation, realizability, stability, controllability, observability; linear control design methods including pole placement, observer, asymptotic tracking and disturbance rejection, internal model design, and feedforward design; introduction to nonlinear systems. Various examples, e.g., robot control, satellite’s attitude control and servomechanism are included.

This course applies computationally intelligent algorithms to solve mechanical and automation problems. It consists of the following topics: various areas of emerging technologies of computationally intelligent systems; introduction and review of neural networks; support vector machines; fuzzy systems; simulated annealing, and genetic algorithms; the applications of intelligent systems to control, robotics, automation, manufacturing, and transportation systems.

This course is intended to provide basic concepts and methods to interface electro-mechanical parts and sensors to computers. It covers the following topics: analogue and digital circuitry; design of linear circuits with ICs and Op-amps; design of low-noise circuits.

This course covers the general introduction to micro-systems including integrated circuits, micromachine design, and microelectromechanical systems (MEMS) fabrication techniques. The second part of the course includes the scaling law, operational principles, design and analysis of microscale sensors and actuators, and the applications of micro sensors and actuators in robotic, biomedical, aerospace, and manufacturing industries.

This course will first give an introduction to robotics and its applications in industries and services; and then teach fundamentals in robotics including kinematics and dynamics of robot manipulators, sensors and actuators, motion control, and machine intelligence. Finally, examples of medical robotics and service robotics will be introduced.

The contents of this course include overview of smart materials technology, characteristics of smart materials such as piezoelectric materials, magnetorheological fluids, and shape memory alloys. It covers smart actuators and sensors; structural modelling and design; dynamics and control for smart structures; integrated system analysis; and applications in buildings, automobiles, trains, robots, manufacturing systems, and medical devices.

This course will discuss the global energy consumption and supply, thermodynamic principles of energy conversion and efficiency, fossil fuel usage, operation of nuclear power plant, emerging technologies utilizing renewable energy sources, energy harvesting and storage technologies, environmental impacts, energy systems management and government policy.

The course is designed to allow the post-graduate students to be kept abreast of the various key engineering systems and components for a modern railway. This includes operations and key components of modern railway systems; core systems including rolling stock, signaling, communication, control, AFC, traction power systems; project management; system Integration including System V&V process, project lifecycle modeling, system assurance and EMC management; railway development planning; and railway capacity modeling.

This course is designed to address the challenges of modern precision and high speed automation machinery design technology. It covers design methods, selection on components and systems, precision measurement and vibration control with industrial practical knowledge.

This course is designed to allow students to acquire a basic understanding and the skills of the practical aspects of the Mechanical and Automation Engineering profession. During the internship, the student must attach to a company in a study-related position for no less than 12 weeks.  The student will have an academic supervisor (as primary supervisor) and an industry co-supervisor from the company, both have the expertise to provide advice to the student.  To be qualified for award of the subject credit, the student must submit a report summarizing the internship experience at the end of the internship. Additional presentation may be required by the hosting company.

The internship should normally take place in the summer term after a student has finished the first two semesters of studies. Part-time students can decide to undertake the internship in the summer term of either the first or second year of studies.

Students are recommended to seek the Professor-in-Charge’s comment on potential internship opportunities before enrolling in the course.