Parameter Identification of a Substitution Model for a Flexible Link

Nissing, Dirk; Polzer, Jan

doi:10.1016/s1474-6670(17)39829-4

Cited by 4 publications

(5 citation statements)

References 3 publications

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“…Additionally the model is overdetermined as the thermal battery model contains more coefficients than substitution parameters. Hence an indirect approach is applied [20]. The errors at the time are stored in an error vector…”

Section: Parameter Identificationmentioning

confidence: 99%

Thermal Model Parameter Identification of a Lithium Battery

Nissing

Mahanta

Sterkenburg

2017

Journal of Control Science and Engineering

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The temperature of a Lithium battery cell is important for its performance, efficiency, safety, and capacity and is influenced by the environmental temperature and by the charging and discharging process itself. Battery Management Systems (BMS) take into account this effect. As the temperature at the battery cell is difficult to measure, often the temperature is measured on or nearby the poles of the cell, although the accuracy of predicting the cell temperature with those quantities is limited. Therefore a thermal model of the battery is used in order to calculate and estimate the cell temperature. This paper uses a simple RC-network representation for the thermal model and shows how the thermal parameters are identified using input/output measurements only, where the load current of the battery represents the input while the temperatures at the poles represent the outputs of the measurement. With a single measurement the eight model parameters (thermal resistances, electric contact resistances, and heat capacities) can be determined using the method of least-square. Experimental results show that the simple model with the identified parameters fits very accurately to the measurements.

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Section: Parameter Identificationmentioning

confidence: 99%

Thermal Model Parameter Identification of a Lithium Battery

Nissing

Mahanta

Sterkenburg

2017

Journal of Control Science and Engineering

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“…These issues can be dealt with in different ways and the aim here is to point out some possible solutions. The two algorithms that will be studied here are given by 1 (…”

Section: Covariance Matrix Update Equationsmentioning

confidence: 99%

“…Recent examples of off-line robot identification in general are given in, e.g., [9], [1], and [2]. Off-line identification of the parameters in the type of physically parameterized robot models studied here is presented in [11].…”

Section: Introductionmentioning

confidence: 99%

“…This paper deals with recursive identification of the parameters in a physically parameterized model of a flexible robot arm. Recent examples of off-line robot identification in general are given in, e.g., [1], [2], and [3]. Off-line identification of the parameters in the type of physically parameterized robot models studied here is presented in [4].…”

Section: Introductionmentioning

confidence: 99%

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Recursive Identification of Physical Parameters in a Flexible Robot Arm

Östring

Gunnarsson

2004

Asian Journal of Control

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Recursive identification of physically parameterized models of continuous time systems is considered. As an example a model of a single link flexible robot arm is considered. The aim of the identification is to generate on-line estimates of physical parameters that can be used for, e.g., diagnosis purposes. For evaluation the algorithm is applied to data from an industrial robot, and three important parameters are identified using only measurements of the motor angle. Keywords: Robotics, Recursive identification, Physical parameters AbstractRecursive identification of physically parameterized models of continuous time systems is considered. As an example a model of a single link flexible robot arm is considered. The aim of the identification is to generate on-line estimates of physical parameters that can be used for, e.g., diagnosis purposes. For evaluation the algorithm is applied to data from an industrial robot, and three important parameters are identified using only measurements of the motor angle.

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“…Kozlowski (1998). Of particular interest here is identification of robots containing flexibilities, and this problem has previously been addressed in for example Dépincé (1998), ElMaraghy et al (1994), and Nissing and Polzer (2000). The aspects of robot identification that are claimed to be new here are first that the identification is based on closed-loop data collected with the control system operating, and second that the physical parameters are estimated directly instead of determining them indirectly via the parameters of a black-box model.…”

Section: Introductionmentioning

confidence: 99%

Closed-loop identification of an industrial robot containing flexibilities

Östring

Gunnarsson

Norrlöf

2003

Control Engineering Practice

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Closed loop identification of an industrial robot of the type ABB IRB 1400 is considered. Using data collected when the robot is subject to feedback control and moving around axis one linear black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities and it is found that the dynamics of the robot can be well approximated by a model consisting of three-masses connected by springs and dampers. It also found that the results of the identification depend on the properties of the input signal. Keywords: identification, robotics, flexible arms Closed Loop Identification of an Industrial Robot Containing FlexibilitiesMånsÖstring, Svante Gunnarsson * , Mikael Norrlöf Department of Electrical Engineering, Linköping University, SE-58183 Linköping, Sweden AbstractClosed loop identification of an industrial robot of the type ABB IRB 1400 is considered. Using data collected when the robot is subject to feedback control and moving around axis one linear black-box and physically parameterized models are identified. A main purpose is to model the mechanical flexibilities and it is found that the dynamics of the robot can be well approximated by a model consisting of three-masses connected by springs and dampers. It also found that the results of the identification depend on the properties of the input signal.

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Parameter Identification of a Substitution Model for a Flexible Link

Cited by 4 publications

References 3 publications

Thermal Model Parameter Identification of a Lithium Battery

Thermal Model Parameter Identification of a Lithium Battery

Recursive Identification of Physical Parameters in a Flexible Robot Arm

Closed-loop identification of an industrial robot containing flexibilities

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