Non-Linear Control of Manipulators
Robot Control System
2025
Robot Control System Non-Linear Control of Manipulators 2025
Outline
1
Introduction
2
MULTI-INPUT, MULTI-OUTPUT CONTROL SYSTEMS
3
Control Design
Robot Control System Non-Linear Control of Manipulators 2025
Introduction to Nonlinear Control
Solution of nonlinear systems are difficult to obtain.
Local linearization can be used to derive approximations of nonlinear
equations in the neighborhood of an operating point
Manipulator control problem not well suited to this approach because
manipulators constantly move among regions of their workspace
widely
Move the operating point with the manipulator as it moves, always
linearizing about the desired position of the manipulator
The result of this sort of moving linearization is a linear, but
time-varying, system
A more complicated control law, in which the gains are time-varying
is used
It uses a nonlinear control term to ”cancel” a nonlinearity in the
controlled system, so that the overall closed loop system is linear
Robot Control System Non-Linear Control of Manipulators 2025
The servo law for a multidimensional system becomes
F
′
=
¨
Xd+kv
˙
E+kpE
where and are nownxnmatrices, which are generally chosen to be
diagonal with constant gains on the diagonal. E and E arenx1
vectors of the errors in position and velocity.
Robot Control System Non-Linear Control of Manipulators 2025
Control Law Design for Nonlinear Spring
Controller reads sensor input and computes actuator output
Figure:
Robot Control System Non-Linear Control of Manipulators 2025
Consider nonlinear friction characteristics shown:
Figure:
nonlinear coloumbian friction is described byf=bcsgn( ˙x)
Robot Control System Non-Linear Control of Manipulators 2025
The open loop equation is
m¨x+bcsgn( ˙x) +kx=f
The partitioned control law isf=αf
′
+β
whereα=m,β=bcsgn( ˙x) +kxandf
′
= ¨xd+kv˙e+kpe
Robot Control System Non-Linear Control of Manipulators 2025
Example : Consider the single-link manipulator shown in Fig. It has one
rotational joint. The mass is considered to be located at a point at the
distal end of the link, and so the moment of inertia isml2. There is
Coulomb and viscous friction acting at the joint, and there is a load due to
gravity.
Figure:
Robot Control System Non-Linear Control of Manipulators 2025
The model of the manipulator is,
τm=ml
2¨
θ+v
˙
θ+csgn(
˙
θ) +mlgcos(θ) (1)
The control system has two parts, the linearizing model-based portion and
the servo-law portion. The model-based portion of the control is
f=αf
′
+β.
α=ml
2
β=v
˙
θ+csgn(
˙
θ) +mlgcos(θ)
f
′
=¨θd+kv˙e+kpe
(2)
The values of the gains for servo portion are calculated from some desired
performance specification.
Robot Control System Non-Linear Control of Manipulators 2025
The method to design a nonlinear controller is
Compute a nonlinear model-based control law that ”cancels” the
nonlinearities of the system to be controlled.
Reduce the system to a linear system that can be controlled with the
simple linear servo law developed for the unit mass.
The linearizing control law implements an inverse model of the
system being controlled.
The nonlinearities in the system cancel those in the inverse model;
this, together with the servo law, results in a linear closed-loop
system.
We must know the parameters and the structure of the nonlinear
system.
Robot Control System Non-Linear Control of Manipulators 2025
MIMO Systems
A vector of desired joint positions, velocities, and accelerations is
given, and the control law must compute a vector of joint-actuator
signals
Partitioning the control law into a model-based portion and a servo
portion, it now appears in a matrix—vector form
The control law takes the formF=αF
′
+β
Where, for a system ofndegrees of freedom,F,F
′
, and arenxl
vectors
αis annxnmatrix that is chosen to decouple thenequations of
motion
Ifαandβare correctly chosen, then, from the F’ input, the system
appears to be n independent unit masses
The model-based portion of the control law is called a linearizing and
decoupling control law
Robot Control System Non-Linear Control of Manipulators 2025
THE CONTROL PROBLEM FOR MANIPULATORS
The rigid-body dynamics has the form
Figure:
Typically, a trajectory can be generated by solving following differential
equation,
τ=M(θ)¨θ+V(θ,˙θ) +G(θ)
Robot Control System Non-Linear Control of Manipulators 2025
Robotic Manipulator
whereM(θ) is thenxninertia matrix of the manipulator,V(θ,˙θ), is
annx1 vector of centrifugal and Coriolis terms, andG(θ) is annx1
vector of gravity terms
Each element ofM(θ) andG(θ) is a complicated function that
depends on (θ), the position of all the joints of the manipulator
Each element ofV(θ,
˙
θ) is a complicated function of bothθand
˙
θ
Incorporate a model of friction which is a function of joint positions
and velocities, above equation takes the form
τ=M(θ)¨θ+V(θ,˙θ) +G(θ) +F(θ,˙θ)
Robot Control System Non-Linear Control of Manipulators 2025
Partitioned control law can be used to control the system using
controller designτ=ατ
′
+β
Whereτis thenx1 vector of joint torques
If we chooseα=M(θ) andβ=V(θ,˙θ) +G(θ) +F(θ,˙θ)
With servo law
τ
′
=¨θd+kv
˙E+kpE
WhereE=θd−θ
The closed-loop system is characterized by the error equation
¨Ed+kv
˙E+kpE= 0
The matricesKpandKvare diagonal,
Robot Control System Non-Linear Control of Manipulators 2025
Figure:
Robot Control System Non-Linear Control of Manipulators 2025
The ideal performance represented by (14) is unattainable in practice
because,
The discrete nature of a digital-computer implementation, as opposed
to the ideal continuous-time control law
Inaccuracy in the manipulator model
Robot Control System Non-Linear Control of Manipulators 2025
CURRENT INDUSTRIAL-ROBOT CONTROL SYSTEMS
An industrial robot with a high-performance servo system is shown in Fig.
Figure:
Robot Control System Non-Linear Control of Manipulators 2025
Individual-joint PID control
Most industrial robots nowadays have a control scheme described by
α=I
β=0
τ
′
=¨θd+Kv
˙E+KpE+Ki
Z
Edt
(3)
HereKp,KVandKiare diagonal matrices.
This type of PID control scheme is simple because each joint is
controlled as a separate control system.
One microprocessor per joint is used to implement control law.
The performance of a manipulator controlled in this way is not simple
to describe.
Robot Control System Non-Linear Control of Manipulators 2025
No decoupling is being done, so the motion of each joint affects the
other joints. These interactions cause errors, which are suppressed by
the error-driven control law.
It is impossible to select fixed gains that will critically damp the
response to disturbances for all configurations. Therefore, ”average”
gains are chosen, which approximate critical damping in the center of
the robot’s workspace.
It is important to keep the gains as high as possible, so that the
inevitable disturbances will be suppressed quickly.
Effect of gravity is nullified by adding compensation term in the
control law.
Robot Control System Non-Linear Control of Manipulators 2025
LYAPUNOV STABILITY ANALYSIS
Robot Control System Non-Linear Control of Manipulators 2025