Lecture 26. Control of the Diver In order for a diver to do what he or she does the diver applies effective torques at the joints We want to find a recipe.

Slides:



Advertisements
Similar presentations
First Order Linear Differential Equations
Advertisements

Lecture 6: Constraints II
LIAL HORNSBY SCHNEIDER
Lecture 5: Constraints I
Lecture 7 Rolling Constraints The most common, and most important nonholonomic constraints They cannot be written in terms of the variables alone you must.
Lecture 2. A Day of Principles The principle of virtual work d’Alembert’s principle Hamilton’s principle 1 (with an example that applies ‘em all at the.
Manipulator’s Inverse kinematics
Lecture 19. The Method of Zs When problems get complicated numerical complexity makes computation SLOW The method of Zs speeds the computation up We will.
Physics 430: Lecture 16 Lagrange’s Equations with Constraints
Lecture 9 Hamilton’s Equations conjugate momentum cyclic coordinates Informal derivation Applications/examples 1.
Mechanics of Machines Dr. Mohammad Kilani
Algebra Problems… Solutions Algebra Problems… Solutions © 2007 Herbert I. Gross Set 22 By Herbert I. Gross and Richard A. Medeiros next.
Linear functions 1. From the figure, we can find that the values of f(x) are in the interval [−1,∞[ 2.
A second order ordinary differential equation has the general form
Lagrangian and Hamiltonian Dynamics
Ch 7.8: Repeated Eigenvalues
Ch 7.9: Nonhomogeneous Linear Systems
Symmetry. Phase Continuity Phase density is conserved by Liouville’s theorem.  Distribution function D  Points as ensemble members Consider as a fluid.
15 PARTIAL DERIVATIVES.
Dynamical Systems Analysis I: Fixed Points & Linearization By Peter Woolf University of Michigan Michigan Chemical Process Dynamics.
Inverse Kinematics How do I put my hand here? IK: Choose these angles!
Dynamical Systems Analysis II: Evaluating Stability, Eigenvalues By Peter Woolf University of Michigan Michigan Chemical Process Dynamics.
II–2 DC Circuits I Theory & Examples.
Ch 5.5: Euler Equations A relatively simple differential equation that has a regular singular point is the Euler equation, where ,  are constants. Note.
Lecture 20: Putting it all together An actual mechanism A physical abstraction: links, springs, wheels, motors, etc. A mathematical model of the physical.
Definition of an Industrial Robot
ME 407 Advanced Dynamics We will learn to model systems that can be viewed as collections of rigid bodies Common mechanical systems Robots Various wheeled.
Linear Equations in Linear Algebra
1 Lecture 27. Two Big Examples The eleven link diver The Stanford Arm (Kane & Levinson)
Ch. 6 Single Variable Control
1 Lecture 25: Modeling Diving I. 2 What do we need to do? Figure out what and how to simplify Build a physical model that we can work with Once that is.
Lecture 13: Stability and Control I We are learning how to analyze mechanisms but what we’d like to do is make them do our bidding We want to be able to.
5-4 Elimination Using Multiplication aka Linear Combination Algebra 1 Glencoe McGraw-HillLinda Stamper.
Lecture 8: Rolling Constraints II
Sect 5.4: Eigenvalues of I & Principal Axis Transformation
Lecture 14: Stability and Control II Reprise of stability from last time The idea of feedback control Remember that our analysis is limited to linear systems.
Lecture 18. Electric Motors simple motor equations and their application 1.
The Wrench: Let’s suppose that we have already reduced a complicated force system to single (resultant ) force,, and a single couple with the moment,,
ECE 8443 – Pattern Recognition ECE 8423 – Adaptive Signal Processing Objectives: Deterministic vs. Random Maximum A Posteriori Maximum Likelihood Minimum.
Lecture 23 The Spherical Bicycle II 1 The story so far: We found the constraint matrix and the null space matrix We “cheated” a little bit in assessing.
Slide 5- 1 Copyright © 2006 Pearson Education, Inc. Publishing as Pearson Addison-Wesley.
LURE 2009 SUMMER PROGRAM John Alford Sam Houston State University.
Slide 9- 1 Copyright © 2006 Pearson Education, Inc. Publishing as Pearson Addison-Wesley.
Manipulator’s Forward kinematics
Chaos in a Pendulum Section 4.6 To introduce chaos concepts, use the damped, driven pendulum. This is a prototype of a nonlinear oscillator which can.
UNIVERSAL COLLEGE OF ENGINEERING AND TECHNOLOGY. FIRST ORDER LINEAR DIFFERENTIAL EQUATION PRESENTED BY ANVI VIRANI ENROLL NO:
Mathe III Lecture 7 Mathe III Lecture 7. 2 Second Order Differential Equations The simplest possible equation of this type is:
Lagrangian Mechanics A short overview. Introduction Previously studied Kinematics and differential motions of robots Now Dynamic analysis Inertias, masses,
Outline: Introduction Solvability Manipulator subspace when n<6
Phy 303: Classical Mechanics (2) Chapter 3 Lagrangian and Hamiltonian Mechanics.
Ch 9.2: Autonomous Systems and Stability In this section we draw together and expand on geometrical ideas introduced in Section 2.5 for certain first order.
1 Lecture 15: Stability and Control III — Control Philosophy of control: closed loop with feedback Ad hoc control thoughts Controllability Three link robot.
Stability Analysis . A system is BIBO stable if all poles or roots of
Lecture 10 Reprise and generalized forces The Lagrangian Holonomic constraints Generalized coordinates Nonholonomic constraints Euler-Lagrange equations.
Two-Dimensional Rotational Dynamics 8.01 W09D2 Young and Freedman: 1.10 (Vector Product), , 10.4, ;
Central Force Umiatin,M.Si. The aim : to evaluate characteristic of motion under central force field.
Optimal parameters of satellite–stabilizer system in circular and elliptic orbits 2nd International Workshop Spaceflight Dynamics and Control October 9-11,
1 Lecture 24: Controlling the Uncontrollable Building the Unbuildable How do we deal with this uncontrollable system? Can we extend the method of Zs to.
Lecture 22 The Spherical Bicycle 1. 2 Some relative dimensions with the wheel radius and mass as unity sphere radius 2, mass 50 fork length 4, radius.
Ch 9.6: Liapunov’s Second Method In Section 9.3 we showed how the stability of a critical point of an almost linear system can usually be determined from.
First Order Linear Differential Equations Any equation containing a derivative is called a differential equation. A function which satisfies the equation.
A few illustrations on the Basic Concepts of Nonlinear Control
Autonomous Cyber-Physical Systems: Dynamical Systems
Copyright © Cengage Learning. All rights reserved.
Linear Equations in Linear Algebra
Outline: Introduction Solvability Manipulator subspace when n<6
Chapter 4 . Trajectory planning and Inverse kinematics
Linear Equations in Linear Algebra
Chapter 7 Inverse Dynamics Control
Presentation transcript:

Lecture 26. Control of the Diver In order for a diver to do what he or she does the diver applies effective torques at the joints We want to find a recipe for doing this that will cause the simulated diver to execute the diver This is a control problem 1

2 Tomorrow’s office hours will be 1:30 to 3:30 I have to leave at 3:30

We have a special case of nonlinear control here and I want to explore that, beginning with some discussion and then some simpler models 3

4 Suppose we want the solution of a second order system to follow some prescription We can write the second order system The errorcan be made to satisfy the homogeneous equation by the proper choice of f(t)

5 choose then is the desired error equation

6 This can be extended to a quasilinear system, which is what we typically have converts the nonlinear equation to the linear form that yields a decaying error given this choice for f(t) This is called feedback linearization

7 What are we doing here? We are asking thatbecome and we choose the forcing function to make this happen This is cool, but it’s only 1D — what happens in a coupled system?

8 For the class of problems we are considering, which includes divers and some robots, we can choose the generalized coordinates such that each external force appears in only one reduced Hamilton equation This is not necessary, but it cleans up the algebra and I’ll assume we’ve taken the trouble to do that, so my simplest coupled case is

9 substitute into the system and solve for f 1 and f 2 When these are substituted back into the original equations we obtain

10 and if the system is not singular then the identical parenthetical equations must equal zero: the errors vanish asymptotically

11 This looks like magic, but it isn’t To make this work we have a necessary condition: as many forces as controlled variables There’re more, but I can’t give them all to you. It works for sufficiently simple systems with only revolute joints — divers and many robots (not the Stanford arm) I’d like to look at the inverted double pendulum from this perspective before moving on to more complicated systems

12 Planar inverted double pendulum: base fixed to the ground parameters: l 1, l 2 m 1, m 2 I treat them as slender members

13 We know how the double pendulum goes Six holonomic constraints to restrict it to the x = 0 plane Four connectivity constraints relating CMs to the ground Apply all ten constraints and define a two dimensional q

14 We can form a Lagrangian

15 There are no additional constraints, so we can let qdot equal u We can find p and then the pieces of Hamilton’s equations

16

17 We have four differential equations and seven algebraic equations (We can actually look at these in the Mathematica notebook) The next issue is designing the control so by assigningwe assign

18 We can look at various desired angles, both steady and time-dependent Here’s the algorithm for vertical stabilization

19 and the result

20 Here we ask both links to follow sinusoidal paths out of phase

21 and here’s the result of that

22 Here are the torques required to perform the tracking shown on the previous slide

23 How about a simple diving problem — a three link diver?

24 Three links —> 18 variables Confine to the x constant plane —> nine variables Four connectivity constraints —> five variables Number the links from the bottom to the top and select the middle link as the reference link

25 There are two torques — one at each joint — as shown in the sketch and we want to choose our variables accordingly

26 We get the Lagrangian as usual

27 This is a fancy torque, suitable for 3D but of course only two of the components actually do anything The important thing is that the choice of q has isolated the two torques

28 Note that we have written this in terms of the desired qs, not the  i The next slide shows the development of the Zs and their gradients

29

30 We need the symbolic versions to build the equations we intend to integrate

31

32 The two internal angles start at zero, go to a maximum of 2π/3, and back to zero in the time interval t f Midway through the ends of the two outboard links should touch We can do this integration and see what the results are We can start by looking at the closest approach, when the two links are to touch

33

34

35

36

37

38 It is now probably worth looking at the Mathematica notebooks