Control Systems is all about plant and processes (systems) how they behave when subjected to certain inputs (system response) and how to get them to do what we want (system control). Control Systems 301 introduces the student to the characteristics of systems commonly encountered in mechatronics.

1. Use Laplace transform techniques to predict and interpret second order system response to step and ramp inputs.
2. Find the steady-state response of a system to a sinusoidal input by the substitution of j for s in the transfer function.
3. Use Laplace transform techniques to find the transient and steady-state response of a system to a sinusoidal input.
4. Use block diagram algebra, especially Mason’s theorem, to reduce elementary control system diagrams to canonical form.
5. Establish system stability or instability by the plotting of poles and zeros on the complex plane
6. Implement and tune control systems using aPID control strategy.

Industrial Data communication is the manipulation of variables that can be implemented into the technology that automatically processes data. The technology under investigation include computers and other communications electronics that can collect, store, influence, formulate and allocate data to serve or control exact processes examples are motor control, electric switching, analogue to digital conversion, digital sampling.

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1. Demonstrate a basic a basic knowledge of digital circuitry using logic.
2. Interface sensors and transducers
3. Explain the function of analogue communication.
4. Describe high-pass low-pass and band-pass filters
5. Understand Analogue to digital conversion and digital to analogue conversion.
6. Demonstrate an understanding of digital motor control

This is an introduction to robotics that entails the mathematical modelling of robotic movement as well as the programming of key movements for the building and design of basic robots.

1. Choose and integrate hardware components for a simple robotic system.

2. Design and synthesize simple software control systems for individual robotic joints

3. Develop and implement mathematical models of multi-link robots to describe the relationship between individual joints and the position and velocity of the robot’s end effector

4. Apply elementary computer vision techniques to control an intelligent robot.

5. Program simple paths and tasks on articulated robotic arm platform.

6. Design and report development of practical robotic systems that incorporate all of the above.

The subject aims to give the student the skills to design and build Supervisory Control And Data Acquisition (SCADA) and distributed control systems software using graphical programming techniques

1. Acquire the necessary skills to produce visual models of real world events
2. Demonstrate a proficiency in the design and development of a HMI
3. Broaden a knowledge of the theory behind and techniques employed in program design
4. Use visual programming techniques (i.e. Labview) to interface with industrial hardware
5. Understand the function and application of networkingprotocols

6. Understand the deployment of SCADA software for the development of increasingly complex tasks.
7. Be able to implement remote telemetry over a Client/Server architecture.
8. Understand OPC Server and Client communication.

Professional Development and Employability is an impending graduate skills module that offers a variety of professional skills to support the development of the graduate's early career.

1. Undertake a critical audit of their skills and capabilities for their professional career

2. Employ the correct communication approach (presentation, poster, report) and use reference material correctly.

3. Demonstrate professional ethics in engineering, including the role of an engineer in society, environmental and health, safety & risk issues.

4. Interpret the roles of teams and leadership.

5. Prepare a personal development plan and work preparation plan (including CV, Cover letter).

This module introduces Lean and Six Sigma principles through the DMAIC methodology to improve quality in manufacturing, with a focus on the triple bottom line of people, planet, and profit. It also covers process validation and quality standards, alongside Design Thinking as a human-centered approach. Students will apply theoretical knowledge through case studies, site visits, and work experiences, linking classroom learning to real-world applications.

1. Relate the history of quality development to Lean, Six Sigma, Validationand Quality Management Standards

2. Evaluate and discuss the key principles of Six Sigma programmes and their application for manufacturing

3. Evaluate and discuss the key principles of Lean Manufacturing and their typical application for manufacturing.

4. Explain how validation principles are applied in a process validation.

5. Interpret the Quality Management StandardISO9001 and connect how Lean and Six Sigma work together with the process approach.

This module consists of topics from Integral and Differential Calculus, Linear Algebra and Complex Numbers. These topics include differential equations and applications, Laplace Transforms, De Moivre's Theorem, Fourier Transforms, Gaussian Elimination and z-transforms.

1. Solve first order differential equations using separable variables technique and the integrating factor method
2. Solve first and second order differential equations using Laplace transforms
3. Solve second order differential equations using the complementary function and particular integral methods.
4. Calculate powers of complex numbers using theorems of DeMoivre and Euler.
5. Solve linear systems using Gaussian Elimination and apply this to engineering problems

6. Be able to obtain the z-Transform of some standard functions and solve first order difference equations.
7. Evaluate eigenvalues and eigenvetors and solve matrix transformation problems

Control Systems is all about plant and processes (systems) how they behave when subjected to certain inputs (system response) and how to get them to do what we want (system control). Control Systems 302 introduces the student to analog and digital strategies for controlling these systems

1. Carry out practicals using analog control techniques on mechanical and fluid equipment.

2. Derive the difference equations for numerical integrators and differentiators.
3. Test for discrete system stability by location of the z-plane poles.
4. Design digital controllers using cancellation pole placement, one-step-ahead and Kalmanand Diophantine pole placement strategies.

5. Implement simple machine learning strategies in linear regression, logistic regression and neural networks using Matlab/Octave software.

6. Use software (e.g. LabView, Simulink) to tune PID controllers.

Review of Data Acquisition, Automation System Architecture – Hierarchical Levels, Functional Layered Models – OSI reference model, System engineering approach, Input / Output Structures, Control Unit Structure, Protocols, Communication principles and modes: network topology, transmission media, noise, cable characteristic and Instrumentation and control devices..

1. Understand the function of a bus protocol.
2. Perform the ID and IO check of an ASI Bus.
3. Explain alternating pulse modulation
4. Explain the functionality of Ethernet

5. Display an understanding of how the microprocessor computes data.
6. Demonstrate IEEE-488 devices and programming

7. Use LabVIEW client/server software

This module deals with various automation technologies ranging from:

Advanced PLC Programming

Scripting to interface with PLC

Embedding C# or other languages into PLC applications

Safety BUS PILZ stop buttons

Apply these technologies to routine industry scenarios

1. Apply advanced PLC programming

2. EmbedC# or other languages into PLC applications

3. Apply scripting to interface with PLC

4. Implement machinery safety using Pilz SafetyBUS p standard

5. Apply the above technologies to routine real-life industry scenario

This 10 credit module involves the design, construction and reporting of a mechatronics project which will typically involve the following elements:

1. Visual interface . e.g. computer screen, lcd readout, control panel with indicator lights

2. Data acquisition . i.e. measurement using appropriate sensors with conversion of signals where necessary from analog to digital and vice versa.

3. Control . The project should be capable of maintaining a measured property within defined limits and be able to cope with small disturbances. Alternatively there could be decision-making based on machine vision or counting/sorting functions. Switching something on and off is not sufficient.

1. Design a system typically incorporating a visual interface, data acquisition and control to meet a defined aim
2. Demonstrate the application of theory covered in Level 7 in the design of hardware for the project. Students are encouraged to use 3-D printing technology either in prototyping or the manufacture of final components.

3. Research and select components/software/control methods
4. Assess the potential safety hazards associated with the project and complete the corresponding risk assessment form.
5. Demonstrate the ability to plan and manage the project (inc.budget and time)
6. Build and test a system typically incorporating a visual interface, data acquisition and control to meet a defined aim
7. Evaluate the project and made recommendations as appropriate
8. Effectively communicate the project concept, project plan and design via areport, presentation and interview