CONTROL OF MECHANICAL SYSTEMS

CONTROL OF MECHANICAL SYSTEMS
2 YEAR
1 semester 9 CFU
Riccardo MARINO Since 2019-20
Code: 8039823
SSD: ING-INF/04

LEARNING OUTCOMES:

Ability to understand scientific papers on the control of mechanical systems

KNOWLEDGE AND UNDERSTANDING:

Knowledge of dynamic modeling of mechanical systems. Knowledge of basic feedback control techniques for single input single output systems and of decoupling techniques for multi input multi output nonlinear systems

APPLYING KNOWLEDGE AND UNDERSTANDING:

Ability to simulate using Matlab Simulink complex controlled mechanical systems

MAKING JUDGEMENTS:

Ability to evaluate stability, robustness, and performance of a control system

COMMUNICATION SKILLS: Ability to present and discuss an autonomous design project

LEARNING SKILLS: Ability to fully understand a scientific paper on the control of mechanical systems

SYLLABUS:

BASIC CONTROL TOOLS
Bounded- input bounded- output linear systems. Pole placement theorem for controllable and observable linear systems. Luenberger observers for observable systems. Design of dynamic compensators for linear systems. Integral feedback control to reject constant disturbances. PID control. System inverses for minimum phase linear systems. The combination of feedback and feedforward control actions.
ADVANCED CONTROL TOOLS
Linear approximations of nonlinear control systems about operating conditions. The definition of region of attraction for an operating condition. Output feedback compensators with integral actions to control nonlinear systems about a given operating condition. Liapunov matrix equations to determine quadratic Liapunov functions and assess the region of attraction. The definition of the sensitivity transfer function and its properties. The gang of four: sensitivity, complementary sensitivity, load sensitivity and noise sensitivity functions. How to determine the robustness of a control loop using the gang of four functions. Bode’s integral formula and the limitations imposed by unstable open loop poles. Youla parametrization to design stable compensation. Kalman filters, Riccati equations and robust control design.

CONTROL DESIGN FOR MULTIVARIABLE NONLINEAR SYSTEMS
Relative degree for a single input single output nonlinear system. State feedback control design for input-output linearization. State feedback linearization when the relative degree is equal to the state space dimension. The definition of nonlinear inverse systems. Relative degrees or decoupling indices for multivariable (multi-input, multi-output) nonlinear systems. The definition of the decoupling matrix. State feedback control design for input-output linearization when the decoupling matrix is full rank using the Penrose pseudoinverse. State feedback linearization when the sum of relative degrees is equal to the state space dimension and the decoupling matrix is full rank.

CASE STUDIES OF NONLINEAR MECHANICAL CONTROL SYSTEMS
Control of bycicles, robots, vehicles and aircrafts

ROBOT MECHANICS

ROBOT MECHANICS
1 YEAR (Blocks B|C)
2 YEAR (Blocks A|D|E)
1 semester 9 CFU
Marco Ceccarelli (6/9 cfu)

Matteo Russo (3/6 cfu)

A.Y. 2021-22

A.Y. 2022-23

Matteo Russo A. Y. 2023-24
A.Y. 2024-25
Code: 8039785
SSD: ING-IND/13

LEARNING OUTCOMES: This course will provide students with the knowledge and tools needed to model and analyse robotic manipulators in terms of mechanical performance. Students will learn how to design, evaluate, and control industrial and service robots.

KNOWLEDGE AND UNDERSTANDING: The student will learn to analyse robotic systems by modelling their kinematics and dynamics and thus finding their key operational parameters. Furthermore, the student will learn how to design a manipulator from its operational requirements, such as workspace, velocity, and payload.

APPLYING KNOWLEDGE AND UNDERSTANDING: The student will apply this knowledge to design, model, and evaluate robots with examples of use cases. Once identified the joints and bodies that compose a robot, the student will be able to numerically characterize its operation and mobility. Furthermore, the student will be able to critically select a robot type for a given manipulation task.

MAKING JUDGEMENTS: The student will demonstrate their understanding of robot operation by developing and presenting a practical use case, in which they will examine autonomously and critically the challenges behind robot design and application.

COMMUNICATION SKILLS: During the course, students discuss key topics, working on a written project on manipulation analysis of their own choice. Project results are then presented at the end of the course.

LEARNING SKILLS: During the course, students are involved in the lecture for a continuous stimulus to verify their understanding of robot mechanics. The knowledge acquired during the course is also verified in the final project on manipulation analysis.

REQUIREMENTS: The student should have already attended the fundamental courses on calculus, geometry, and physics. The understanding of rigid body mechanics and basic programming skills (MATLAB) are required, as well as knowledge of mechanism design and analysis.

PROGRAMME:

  1. Architecture and classification of industrial and service robots
    1. Definitions: kinematic chains, joints, mobility
    2. Manipulation analysis
    3. Types of manipulators
  2. Kinematics
    1. Reference frames
    2. Denavit-Hartenberg notation
    3. Forward kinematics
    4. Inverse kinematics
    5. Jacobian and singularities
    6. Workspace
    7. Path planning
  3. Statics and dynamics
    1. Equilibrium
    2. Equation of motion
    3. Grasp mechanics
  4. Other designs
    1. Actuation technologies
    2. Parallel robots
    3. Compliant robots
    4. Soft and continuum robots

EXAM:

The exam is divided into a written and oral test. The written test consists of three exercises regarding practical use-cases of industrial and service robots. In alternative, a project report developed during the course can be evaluated. In the oral test, the student will discuss with a critical perspective robot functioning. In alternative, the developed project on manipulation analysis can be presented and discussed.