MICYCLE A self-balancing electric unicycle Andrew Kadis David Caldecott Andrew Edwards Matthew Haynes Miroslav Jerbic Rhys Madigan Supervisor: Assoc. Prof. Ben S. Cazzolato Co-Supervisor: Dr. Zebb Prime

Introduction 2  Submitted paper focused on developing the system dynamics and simulating them  The control response of the simulated and physical systems were then compared  This presentation has a slightly different focus, concentrates on the wider Micycle system

Literature review 3

Concept development 4  Incorporation of steering mechanism  Extensive research into steering mechanisms  Use of a rotary damper

Concept development (2) 5 Lego Mockup Preliminary Concept Model

Components Sensor Power supply Motor controller Motor Microcontroller 6

Mechanical design goals 7 Assembly of Micycle Damper Spring Fork Chassis assembly Steering mechanism Perspex covers Protective rubber

Major mechanical components 8  Chassis assembly  Simple plate chassis design  Protective Perspex covers  Protective rubber  Fork design  Rotary damper drive  Offset centre for motor  Dual bearing design  Chromoly steel Chassis plate assembly Plate chassis Perspex covers Protective rubber Fork Damper drive Bearing locations Offset centre

Steering mechanism 9  Uses a torsion spring and rotary damper  Makes the Micycle much easier to ride  Allowed steering angle ±15˚ Steering mechanism

Mechanical design approach 10 CoG Analysis Iterate design Drafting Structural analysis ANSYS Workbench ProE

Electrical system overview 11 IMU MOTOR CONTROLLER MICRO- CONTROLLER PERIPHERALS HUB MOTOR BATTERY DISTRIBUTION BOARD

Controller design Self-Balancing Unicycle Mechanical System Control Electrical System 12

Controller structure 13  PD controller structure used  Derivative signal taken directly from the IMU rather than differentiated to minimise latency in the sensor readings

System Dynamics 14  The Lagrangian approach of deriving the system dynamics was applied  The dynamics were derived in terms of:  φ – the rotation of the frame about the z-axis  θ – the rotation of the wheel relative to the z axis  Full details can be found in the paper  Developed simulation in Simulink from these dynamics

Controller benchmarking - methodology 15  Needed a methodology to produce repeatable results to benchmark control system  Attached a PD controller with same gains to simulated dynamics  Constrained the wheel  Point of comparison between physical and simulated control systems to examine response to disturbances Micycle with the wheel constrained

Controller benchmarking - results 16 Response of simulated system released from 30ºResponse of physical system released from 30º

Software functionality 17 Core Peripheral Safety

Fall 18

Failure modes and effect analysis (FMEA) 19  Comprehensive, iterative process  System engineering tool  Both a high and low level FMEA performed  Over 100 different cases considered  Full FMEA is approx. 30 pages long

Safety Control Safety Andrew Kadis - Software

Error codes 7 Safety Trip7 Segment Error Code Battery drained0 Vehicle speed too fast1 Excessive current through motor2 Pitch position outside safe range3 Angular velocity too fast4 General operational failure in the Maxon5 ADC outside expected bounds6 IMU did not initialise correctly7 Maxon did not initialise correctly8 IMU - abnormal power rating9 IMU - RS232 pin disconnectedA IMU - parity check failedB IMU - indeterminate communication errorC

Project outcomes 22  Designed, tested and built the Micycle  A fully rideable self-balancing electric unicycle which can be learnt to ride in 30 minutes to an hour  Comprehensive iterative FMEA process completed  8 hour battery life  Significant exposure to the wider community

Community exposure 23

24 Community exposure (2)

Future work 26  Use of a more powerful motor controller to reduce the chances of actuator saturation  Implementation of a model based controller  Incorporation of active control in the roll direction

Questions 27

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