#### DMCA

## AUTOMATIC CONTROL (2007)

### Cached

### Download Links

Citations: | 3 - 0 self |

### Citations

1036 |
Optimal Filtering
- Anderson, Moore
- 2005
(Show Context)
Citation Context ...relationship between the references rmi and the outputs θmi, θai are needed as described in Sec. IV. III. ESTIMATION ALGORITHMS In this paper the extended Kalman filter (EKF) is used, see for example =-=[2]-=-. The arm-angle estimation is based on the results presented in [9], where different versions of the EKF as well as a deterministic observer described in [7] are investigated and evaluated experimenta... |

545 |
Robust and Optimal Control
- Doyle, Glover
- 1996
(Show Context)
Citation Context ...sponds to the case where ILC is applied to a system Tu where no structural knowledge of the components of the error are known. A model of Tu can, for example, be found using system identification. In =-=[26]-=- different types of model errors are discussed and [5], [23] show examples applied to ILC. Introducing the model (23), the frequency-domain convergence criterion (9) results in |1−L(eiω)(1+∆(eiω))T̂u(... |

442 | A Kinematic Notation for Lower-Pair Mechanisms Based on Matrices - Denavitt, Harternberg - 1955 |

237 |
Robot Modeling and Control
- Spong, Hutchinson, et al.
(Show Context)
Citation Context ...1 is simple compared to an accurate model of an industrial robot, but it still captures some of the principle behaviours that can be confirmed from experiments performed with a robot, see for example =-=[21]-=-, [25] and [24]. The system can be described by Jmq̈m(t) =− fmq̇m(t)− rgk ( rgqm(t)−qa(t) ) −rgd ( rgq̇m(t)− q̇a(t) ) + kτu(t), Jaq̈a(t) = k ( rgqm(t)−qa(t) ) +d ( rgq̇m(t)− q̇a(t) ) , (1) where the p... |

213 |
Bettering operation of robots by learning
- Arimoto, Kawamura, et al.
- 1984
(Show Context)
Citation Context ...is measurable. The position of the second mass, referred to as the arm position, is only used as an evaluation variable that should follow the desired arm trajectory. The ILC method was introduced in =-=[2]-=-, [6] and [7], and robotic applications have been an important field of application for ILC ever since, see for example [14] and [22]. The reason for this is that in many robotic applications the robo... |

198 | A robotics toolbox for MATLAB - Corke - 1996 |

124 |
Modeling and control of elastic joint robots
- Spong
- 1987
(Show Context)
Citation Context ... position, velocity and acceleration and hence be able to improve the control performance. In many publications the subject of estimation and control of flexible robots are discussed, see for example =-=[17]-=-. In [10] the states for a robot with flexible joints are estimated using an observer based on only the motor angles. Examples when the extended Kalman filter (EKF) are used in the estimation are [11]... |

50 |
Iterative learning control – an expository overview
- Moore
- 1999
(Show Context)
Citation Context ...LC ever since, see for example [14] and [22]. The reason for this is that in many robotic applications the robot performs the same trajectory repeatedly, starting from the same initial conditions. In =-=[17]-=- a detailed overview over the ILC research area is given together with a categorisation of much of the publications from 1984 until 1998. Publications between 1998 and 2004 are covered in [1], while a... |

49 |
etc. A survey of Iterative Learning Control
- Bristow
(Show Context)
Citation Context ...s given together with a categorisation of much of the publications from 1984 until 1998. Publications between 1998 and 2004 are covered in [1], while a résumé of recent publications can be found in =-=[3]-=-. This paper discusses robustness and performance aspects when an ILC algorithm is applied to a flexible system, such as the system shown in Fig. 1. In [15] and [12] ILC is applied to flexible systems... |

49 |
Iterative learning control and repetitive control for engineering practice
- Longman
- 2000
(Show Context)
Citation Context ...t should follow the desired arm trajectory. The ILC method was introduced in [2], [6] and [7], and robotic applications have been an important field of application for ILC ever since, see for example =-=[14]-=- and [22]. The reason for this is that in many robotic applications the robot performs the same trajectory repeatedly, starting from the same initial conditions. In [17] a detailed overview over the I... |

45 | Iterative Learning Control – Analysis, Design, Integration and Applications - Bien, Xu - 1998 |

37 |
Adaptive Control of Manipulators Through Repeated Trials
- Craig
- 1984
(Show Context)
Citation Context .... The position of the second mass, referred to as the arm position, is only used as an evaluation variable that should follow the desired arm trajectory. The ILC method was introduced in [2], [6] and =-=[7]-=-, and robotic applications have been an important field of application for ILC ever since, see for example [14] and [22]. The reason for this is that in many robotic applications the robot performs th... |

37 | Iterative Learning Control: Analysis, Design and Experiments. Thesis no. 653, Linköpings universitet
- Norrlöf
- 2000
(Show Context)
Citation Context ...N number of samples. Finally, Tr(q) and Tu(q) are stable discrete-time filters. System and measurement disturbances are not included here, but can be easily treated in this framework, see for example =-=[13]-=-. The update for a general first-order ILC algorithm is uk+1(t) = Q(q) ( uk(t)+L(q)ek(t) ) , (12) where the linear filters Q(q) and L(q) are possibly noncausal. The error ek(t) = r(t)− yk(t), (13) is ... |

31 |
Adaptive iterative learning control for robot manipulators
- Tayebi
- 2004
(Show Context)
Citation Context ...follow the desired arm trajectory. The ILC method was introduced in [2], [6] and [7], and robotic applications have been an important field of application for ILC ever since, see for example [14] and =-=[22]-=-. The reason for this is that in many robotic applications the robot performs the same trajectory repeatedly, starting from the same initial conditions. In [17] a detailed overview over the ILC resear... |

28 | Iterative learning control: brief survey and categorization
- Ahn, Chen, et al.
(Show Context)
Citation Context ...ons. In [17] a detailed overview over the ILC research area is given together with a categorisation of much of the publications from 1984 until 1998. Publications between 1998 and 2004 are covered in =-=[1]-=-, while a résumé of recent publications can be found in [3]. This paper discusses robustness and performance aspects when an ILC algorithm is applied to a flexible system, such as the system shown i... |

24 | Formation of High-Speed Motion Pattern of a Mechanical Arm by Trial." Trans. of Society of Instrument and Control Engineers 1 " (Japan) 19: (5)706-712 - York, Uchiyama, et al. - 1978 |

23 |
Present and future robot control development - An industrial perspective
- Brogardh
(Show Context)
Citation Context ...ies cannot be assumed to be only in the joints, see [20] and [16]. A good model of an industrial robot therefore includes joint as well as arm flexibilities and requires up to 50 spring-mass elements =-=[4]-=-. τ(t), qm(t) qa(t) Jm Ja k, d rg fm Fig. 1. A flexible two-mass model of the dynamics in a single robot joint, characterised by spring k, damper d, viscous friction fm, gear ratio rg, moments of iner... |

19 |
A mathematical theory of learning control for linear discrete multivariable systems
- Phan, Longman
- 1988
(Show Context)
Citation Context ... ILC algorithm is uk+1 = Q(uk + Lek), (13) where the linear filters Q and L are possibly non-causal and ek = r − yk, (14) is the error at iteration k. The system (12) can be described in matrix form, =-=[16]-=- was among the first users of the description in the ILC community. Let yk = ( yk(0) . . . yk(N − 1) )T , (15) and define r and uk similarly, which gives yk = Trr + Tuuk. (16) This system description ... |

18 | On D-type Iterative Learning Control - Chen, Moore |

17 | Time and frequency domain convergence properties in iterative learning control
- Norlöf, Gunnarsson
- 2002
(Show Context)
Citation Context ...k(t), (8) is the difference between motor-angle reference and measured motor angle at iteration k. The update equation (7) implies the standard frequency-domain convergence criterion, see for example =-=[19]-=-, |1−L(eiω)Tu(eiω)|< |Q−1(eiω)|, ∀ω, (9) where Tu denotes the transfer function from the applied ILC input uk(t) to the measured output yk(t). The criterion shows that the filter Q can be used to impr... |

17 |
On the design of ILC algorithms using optimization
- Gunnarsson, Norrlöf
(Show Context)
Citation Context ... will directly affect the robustness properties of the ILC algorithm. The next contribution is to compare a classical non-causal P-ILC algorithm to a modelbased ILC algorithm designed by optimisation =-=[10]-=-, when the ILC update equation only uses the motor position. The performance of the two design methods is compared and the robustness is evaluated when model errors are introduced in the system. The m... |

16 |
A learning procedure for the control of movements of robotic manipulators
- Casalino, Bartolini
- 1984
(Show Context)
Citation Context ...asurable. The position of the second mass, referred to as the arm position, is only used as an evaluation variable that should follow the desired arm trajectory. The ILC method was introduced in [2], =-=[6]-=- and [7], and robotic applications have been an important field of application for ILC ever since, see for example [14] and [22]. The reason for this is that in many robotic applications the robot per... |

15 | Robotica: a Mathematica package for robot analysis - Nethery, Spong - 1994 |

15 |
Synthesis of a robust iterative learning controller using an H∞ approach
- Roover
- 1996
(Show Context)
Citation Context ...error is closer to zero after convergence, as can be seen in, for instance, [9]. C. Optimisation-based ILC design The optimisation-based ILC design is based on [10], and similar work are presented in =-=[8]-=- and [13]. The matrix formulation (11) is used and the learning filters or matrices are derived by minimising the quadratic criterion Jk+1 = eTk+1W eek+1+u T k+1W uuk+1, (14) subject to the constraint... |

15 | Experimental comparison of some classical iterative learning control algorithms
- Norrlöf, Gunnarsson
- 2002
(Show Context)
Citation Context ...erence ra(t) is filtered by Fr . III. ILC ALGORITHMS Two algorithms are presented in this section. The first is a standard non-causal P-type ILC algorithm, the design is here referred to as heuristic =-=[18]-=-. The second is an optimisationbased design and the algorithm uses explicitly a model of the system. A. General system description The general system description when an ILC algorithm is applied to a ... |

15 | Learning accurate path control of industrial robots with joint elasticity - Lange, Hirzinger - 1999 |

14 | Multi-Loop Control Approach to Designing Iterative Learning Controllers - Moore - 1998 |

11 | D-uppsats □⊠ Övrig rapport Serietitel och serienummer Title of series, numbering ISSN - C-uppsats |

10 | Design strategy for iterative learning control based on optimal control - Tousain, Meché, et al. - 2001 |

10 |
Robust iterative learning control design is straightforward for uncertain LTI systems satisfying the robust performance condition
- Tayebi, Zeremba
- 2003
(Show Context)
Citation Context ... no structural knowledge of the components of the error are known. A model of Tu can, for example, be found using system identification. In [26] different types of model errors are discussed and [5], =-=[23]-=- show examples applied to ILC. Introducing the model (23), the frequency-domain convergence criterion (9) results in |1−L(eiω)(1+∆(eiω))T̂u(eiω)|< |Q−1(eiω)|, ∀ω. (24) In this paper T̂u is assumed to ... |

10 | Exponential convergence of a learning controller for robot manipulators - Horowitz, Messner, et al. - 1991 |

9 |
A benchmark problem for robust control of a multivariable nonlinear flexible manipulator
- Moberg, Öhr, et al.
- 2008
(Show Context)
Citation Context ...ix motors. The joints (gear transmissions) are described by nonlinear spring torque τs, linear damping d and friction torque f . A. Original nonlinear robot model The model used is fully described in =-=[13]-=-. Each link has rigid body characteristics described by mass m, link length l, center of mass ξ and inertia j with respect to center of mass. The links are actuated by electrical motors, connected to ... |

8 | Pathcorrection for an industrial robot - Gunnarsson, Norrlof, et al. - 2000 |

8 |
Position estimation and modeling of a flexible industrial robot
- Karlsson, Norrlöf
- 2005
(Show Context)
Citation Context ...states for a robot with flexible joints are estimated using an observer based on only the motor angles. Examples when the extended Kalman filter (EKF) are used in the estimation are [11] and [12]. In =-=[15]-=- the acceleration of the tool is measured and two solutions for the state estimation problem are discussed, using EKF and particle filters, respectively. In this paper EKF and ILC are combined for a r... |

8 |
Simple learning controls made practical by zero-phase filtering: Applications to robotics
- Elci, Longman, et al.
- 2002
(Show Context)
Citation Context ...toff frequency of the robustifying low-pass filter Q means a filter near the ideal filter Q= 1, and thereby also a that the error is closer to zero after convergence, as can be seen in, for instance, =-=[9]-=-. C. Optimisation-based ILC design The optimisation-based ILC design is based on [10], and similar work are presented in [8] and [13]. The matrix formulation (11) is used and the learning filters or m... |

8 | Experimental comparison of observers for tool position estimation of industrial robots
- Henriksson, Norrlöf, et al.
(Show Context)
Citation Context ...respectively. In this paper EKF and ILC are combined for a realistic two-link robot model with mechanical flexibilities. The methods for estimating the robot tool position are further investigated in =-=[9]-=-, upon which the work in this paper is based. To the best of the authors knowledge, estimation techniques and ILC have only been combined in a few publications. One example is [8], where the ILC algor... |

8 | Observer based control for elastic joint robots - Jankovic - 1995 |

7 | ILC applied to a flexible two-link robot model using sensor-fusion-based estimates - Wallén, Gunnarsson, et al. - 2009 |

7 |
On Kinematic Modelling and Iterative Learning Control of Industrial Robots
- Wallén
- 2008
(Show Context)
Citation Context ...pared to an accurate model of an industrial robot, but it still captures some of the principle behaviours that can be confirmed from experiments performed with a robot, see for example [21], [25] and =-=[24]-=-. The system can be described by Jmq̈m(t) =− fmq̇m(t)− rgk ( rgqm(t)−qa(t) ) −rgd ( rgq̇m(t)− q̇a(t) ) + kτu(t), Jaq̈a(t) = k ( rgqm(t)−qa(t) ) +d ( rgq̇m(t)− q̇a(t) ) , (1) where the parameter values... |

6 | An automated symbolic and numeric procedure for manipulator rigidbody dynamic significance analysis and simplification - Corke - 1996 |

6 | Learning control of actuators in control systems - Garden - 1967 |

5 |
Arm-side evaluation of ILC applied to a six-degrees-of-freedom industrial robot
- Wallén, Norrlöf, et al.
(Show Context)
Citation Context ...imple compared to an accurate model of an industrial robot, but it still captures some of the principle behaviours that can be confirmed from experiments performed with a robot, see for example [21], =-=[25]-=- and [24]. The system can be described by Jmq̈m(t) =− fmq̇m(t)− rgk ( rgqm(t)−qa(t) ) −rgd ( rgq̇m(t)− q̇a(t) ) + kτu(t), Jaq̈a(t) = k ( rgqm(t)−qa(t) ) +d ( rgq̇m(t)− q̇a(t) ) , (1) where the paramet... |

5 | An acceleration-based state observer for robot manipulators with elastic joints
- Luca, Schröder, et al.
- 2007
(Show Context)
Citation Context ...lman filter (EKF) is used, see for example [2]. The arm-angle estimation is based on the results presented in [9], where different versions of the EKF as well as a deterministic observer described in =-=[7]-=- are investigated and evaluated experimentally. For the details regarding the estimation, tuning process and robustness of the methods, the reader is directed to [9]. Given a general nonlinear discret... |

5 | Extended Kalman Filtering Applied to a Two-axis Robotic Arm with Flexible Links,” Int
- Lertpiriyasuwat, Berg, et al.
- 2000
(Show Context)
Citation Context ...[17]. In [10] the states for a robot with flexible joints are estimated using an observer based on only the motor angles. Examples when the extended Kalman filter (EKF) are used in the estimation are =-=[11]-=- and [12]. In [15] the acceleration of the tool is measured and two solutions for the state estimation problem are discussed, using EKF and particle filters, respectively. In this paper EKF and ILC ar... |

5 |
End-Point Sensing and State Observation of a Flexible-Link Robot
- Li, Chen
- 2001
(Show Context)
Citation Context ...[10] the states for a robot with flexible joints are estimated using an observer based on only the motor angles. Examples when the extended Kalman filter (EKF) are used in the estimation are [11] and =-=[12]-=-. In [15] the acceleration of the tool is measured and two solutions for the state estimation problem are discussed, using EKF and particle filters, respectively. In this paper EKF and ILC are combine... |

4 | A toolbox for teaching and researching robotics - Bienkowski, Kozlowski - 1998 |

4 | Symbolic algebra for manipulator dynamics - Corke - 1996 |

4 |
On the use of accelerometers in iterative learning control of a flexible robot arm
- Gunnarsson, Norrlöf, et al.
- 2007
(Show Context)
Citation Context ...ve the result could be to use the model of the system and to estimate the arm position from motor torque and position measurements. The estimate could then be used by the ILC algorithm as proposed in =-=[11]-=-. To include arm side measurements in the ILC algorithm is of course a natural next step, but in the industrial application this is not straightforward, mainly from a safety and a cost perspective. VI... |

4 | Optimization-based iterative learning control for trajectory tracking - SCHÖLLIG, D’ANDREA - 2009 |

4 |
Design of quadratic criterion-based iterative learning control
- Lee, Lee
(Show Context)
Citation Context ... closer to zero after convergence, as can be seen in, for instance, [9]. C. Optimisation-based ILC design The optimisation-based ILC design is based on [10], and similar work are presented in [8] and =-=[13]-=-. The matrix formulation (11) is used and the learning filters or matrices are derived by minimising the quadratic criterion Jk+1 = eTk+1W eek+1+u T k+1W uuk+1, (14) subject to the constraint (uk+1−uk... |

4 |
A DAE Approach to Feedforward Control of Flexible Manipulators
- Moberg, Hanssen
- 2007
(Show Context)
Citation Context ...d body models that are used in classical robot control. The trend is towards more flexible robots and it is also a fact that the flexibilities cannot be assumed to be only in the joints, see [20] and =-=[16]-=-. A good model of an industrial robot therefore includes joint as well as arm flexibilities and requires up to 50 spring-mass elements [4]. τ(t), qm(t) qa(t) Jm Ja k, d rg fm Fig. 1. A flexible two-ma... |

4 | Theory and implementation of a repetetive robot controller with cartesian trajectory description - Guglielmo, Sadegh - 1996 |

3 | Observer-based iterative learning control for a class of time-varying nonlinear systems - Tayebi, Xu - 2003 |

3 |
A statistical analysis of certain iterative learning control algorithms”, Accepted by the International Journal of Control
- Butcher, Karimi, et al.
(Show Context)
Citation Context ...where no structural knowledge of the components of the error are known. A model of Tu can, for example, be found using system identification. In [26] different types of model errors are discussed and =-=[5]-=-, [23] show examples applied to ILC. Introducing the model (23), the frequency-domain convergence criterion (9) results in |1−L(eiω)(1+∆(eiω))T̂u(eiω)|< |Q−1(eiω)|, ∀ω. (24) In this paper T̂u is assum... |

2 | On robot modelling using Maple - Wallén - 2006 |

2 |
Adjoint-Type Iterative Learning Control for a Single Link Flexible
- KINOSHITA, SOGO, et al.
- 2002
(Show Context)
Citation Context ...recent publications can be found in [3]. This paper discusses robustness and performance aspects when an ILC algorithm is applied to a flexible system, such as the system shown in Fig. 1. In [15] and =-=[12]-=- ILC is applied to flexible systems but it is assumed that the position of the arm is measurable, while here it is assumed that only the position of the motor is available. It is assumed that the syst... |

2 |
Repositioning control of a two-link flexible arm by learning
- Lucibello, Panzieri, et al.
- 1997
(Show Context)
Citation Context ...sumé of recent publications can be found in [3]. This paper discusses robustness and performance aspects when an ILC algorithm is applied to a flexible system, such as the system shown in Fig. 1. In =-=[15]-=- and [12] ILC is applied to flexible systems but it is assumed that the position of the arm is measurable, while here it is assumed that only the position of the motor is available. It is assumed that... |

2 | Identification of flexibility parameters of 6-axis industrial manipulator models
- Öhr, Moberg, et al.
- 2006
(Show Context)
Citation Context ...onal rigid body models that are used in classical robot control. The trend is towards more flexible robots and it is also a fact that the flexibilities cannot be assumed to be only in the joints, see =-=[20]-=- and [16]. A good model of an industrial robot therefore includes joint as well as arm flexibilities and requires up to 50 spring-mass elements [4]. τ(t), qm(t) qa(t) Jm Ja k, d rg fm Fig. 1. A flexib... |

2 |
Application study on iterative learning control of high speed motions for parallel robotic manupilator
- Abdellatif, Feldt, et al.
- 2006
(Show Context)
Citation Context ...vates the choice of ILC algorithm in this paper seen in Sec. V, is that the simple linear algorithm can achieve asymptotic convergence also for quite complicated nonlinear non-affine MIMO systems. In =-=[1]-=- three different approaches; heuristic, modelbased, and frequency-response based method are discussed when deriving the linear ILC algorithm with the structure uk+1 = uk +QLek. The heuristic ILC desig... |

1 | Industriell robotteknik - Bolmsjö - 1992 |

1 | Derivation of kinematic relations for a robot using Maple - Wallén, Gunnarsson, et al. |

1 | Adaptive control of manipulators through repeated trials - Autom - 1984 |

1 |
New iterative learning control approaches for nonlinear non-affine MIMO dynamic systems
- Xu, Tan
(Show Context)
Citation Context ...ing ILC for MIMO systems. As pointed out in [4], extensions of the matrix form to square MIMO systems are generally straightforward, which will be illustrated in the example in next section. The work =-=[19]-=- discusses various aspects regarding MIMO ILC algorithms applied to nonlinear non-affine-in-input systems. Although the system in this paper is affine with respect to the input, the result in [19] is ... |

1 |
URL: http://www.abb.se, accessed
- ABB
- 2008
(Show Context)
Citation Context ...onfirmed from experiments performed with a robot, see for example [16], [17]. A modern industrial robot is flexible, due to Fig. 1. A commercial industrial ABB robot IRB1400 performing plasma cutting =-=[1]-=-. Tool position and orientation cannot be measured due to practical and economical reasons. The control objective is however to follow a desired tool path, whereas the measured variables are the motor... |

1 | Open public archive of robot images - ABB - 2007 |

1 | On the use of acceleormeters in iterative learning control of a flexible robot arm - Gunnarsson, Norrlöf, et al. - 2007 |