Operator-Based Robust Nonlinear Control Analysis and Design for a Bio-Inspired Robot Arm with Measurement Uncertainties

2019 ◽  
Vol 31 (1) ◽  
pp. 104-109
Author(s):  
Aihui Wang ◽  
Zhengxiang Ma ◽  
Jianmin Luo ◽  
Keyword(s):  
Experimental Data ◽  
Sufficient Conditions ◽  
Control Analysis ◽  
Robot Arm ◽  
Factorization Approach ◽  
Motion Mechanism ◽  
Analysis And Design ◽  
Design Scheme ◽  
Nonlinear Tracking ◽  
Measurement Uncertainties

In this paper, a robust nonlinear tracking control design for a bio-inspired robot arm with human-like motion mechanism is investigated, and the bio-inspired operator controller based on human multi-joint viscoelastic properties is designed by using operator-based robust right coprime factorization approach. The motion mechanism of human multi-joint arm is used, and the measurement uncertainties of human multi-joint arm viscoelasticity are considered in designing bio-inspired operator controller. Based on the proposed design scheme, the sufficient conditions for the robust stability are derived in considering the coupling effects and measurement uncertainties, and the output tracking performance is realized. The effectiveness of the proposed design scheme was confirmed by the simulation results based on experimental data, and the time-varying estimated experimental data of human multi-joint arm viscoelasticity is used in simulation.

scholarly journals OpenHPL for Modelling the Trollheim Hydropower Plant

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2303
Author(s):  
Liubomyr Vytvytskyi ◽  
Bernt Lie
Keyword(s):  
Experimental Data ◽  
Renewable Energy Sources ◽  
Friction Model ◽  
Hydropower Plant ◽  
Francis Turbine ◽  
Model Parameters ◽  
Control Analysis ◽  
Script Language ◽  
Hydro Power ◽  
Analysis And Design

An increase of tightly integrated, renewable energy sources with highly varying production leads to a greater need for flexible hydropower plants to “balance” the intermittent production from these sources. From a systems perspective, the intermittency aspect constitutes a disturbance, while the tight integration leads to a multivariable systems, both of which causes increased challenges for good control. This instigates the need for a model based analysis and synthesis tool which can describe dynamic phenomena, supports multiphysics problems, and allows for immediate use in advanced control analysis and design. Previously, an open source Hydro Power Library (OpenHPL) have been developed within the multiphysics Modelica eco-system which satisfies the above requirements: OpenHPL contains a set of model units relevant for hydropower systems, as well as examples of tools for analysis of these models for control purposes. Thus far, OpenHPL has been validated by comparison against other simulation tools. However, a real test of OpenHPL is to use it to describe a real hydropower plant using minimal plant information, to tune model parameters against experimental data, and to validate the model. As a case study, experimental data from the Trollheim hydropower plant in Norway have been made available, and used to test OpenHPL. By flow sheeting a hydropower model in OpenModelica using OpenHPL, the model can be simulated from within a script language (Python via the OMPython API, Julia via the OMJulia API) and further analyzed using analysis tools in the script language. Based on default model parameter suggestions from OpenHPL, least squares model fitting was carried out in Python, and the model was validated with good model fit. Important parts of the modelling phase were the development of a new friction model for the Francis turbine, and iterations on the description of the turbine outlet geometry. The results are complemented with a discussion of possible uses of the model.

scholarly journals A Microcontrolled System Applied to Process Control Analysis and Design

1997 ◽  
Vol 30 (7) ◽  
pp. 463-467
Author(s):  
Márcio G. Faccin ◽  
Julio C.S. Vicente ◽  
Moisés M.B. Pontremoli ◽  
Romeu Reginatto
Keyword(s):  
Process Control ◽  
Control Analysis ◽  
Analysis And Design

The Modelling of Hysteresis in Magnetorheological Dampers Using a Generalised Prandtl-Ishlinskii Approach

2010 ◽  
Author(s):  
Kun Wang ◽  
Ying Zhang ◽  
Richard W. Jones
Keyword(s):  
Mr Damper ◽  
Control Analysis ◽  
Sigmoid Function ◽  
Magnetorheological Dampers ◽  
Operating Characteristics ◽  
Major Drawback ◽  
Analysis And Design ◽  
Force Velocity ◽  
Play Operator ◽  
Fidelity Model

The major drawback of magnetorheological dampers (MR) lies in their non-linear and hysteretic force-velocity response. To take full advantage of the operating characteristics of these devices a high fidelity model is required for control analysis and design. In this contribution the ability of a generalised PI operator-based model to represent the characteristics of a commercially available MR damper is examined. This approach allows the user to define the PI operator to best match the hysteresis characteristics. For the MR damper the force-velcoity hysteresis characteristic is ‘S’ shaped and constrained. Two possibilities will be examined here for the generalised play operator; an hyperbolic tan function and a symmetric sigmoid function.

Semianalytical compressive strength criteria for unidirectional composites

2017 ◽  
Vol 37 (4) ◽  
pp. 238-246
Author(s):  
Uri Breiman ◽  
Jacob Aboudi ◽  
Rami Haj-Ali
Keyword(s):  
Experimental Data ◽  
Compressive Strength ◽  
Volume Fraction ◽  
Unidirectional Composite ◽  
Fiber Volume ◽  
Unidirectional Composites ◽  
Analysis And Design ◽  
Composite Systems ◽  
Wide Range ◽  
Laminated Structures

The compressive strength of unidirectional composites is strongly influenced by the elastic and strength properties of the fiber and matrix phases, as well as by the local geometrical properties, such as fiber volume fraction, misalignment, and waviness. In the present investigation, two microbuckling criteria are proposed and examined against a large volume of measured data of unidirectional composites taken from the literature. The first criterion is based on the compressive strength formulation using the buckling of Timoshenko’s beam. It contains a single parameter that can be determined according to the best fit to experimental data for various types of polymeric matrix composites. The second criterion is based on buckling-wave propagation analogy using the solution of an eigenvalue problem. Both criteria provide closed-form expressions for the compressive strength of unidirectional composites. We propose modifications of the two criteria by a fitting approach, for a wide range of fiber volume fractions, applied to four classes of unidirectional composite systems. Furthermore, a normalized form of the two models is presented after calibration in order to compare their prediction against experimental data for each of the material systems. The new modified criteria are shown to give a good match to a wide range of unidirectional composite systems. They can be employed as practical compression failure criteria in the analysis and design of laminated structures.

Analysis and Design of Associative Memories Based on Recurrent Neural Networks with Linear Saturation Activation Functions and Time-Varying Delays

2007 ◽  
Vol 19 (8) ◽  
pp. 2149-2182 ◽  
Author(s):  
Zhigang Zeng ◽  
Jun Wang
Keyword(s):  
Neural Networks ◽  
Recurrent Neural Networks ◽  
Sufficient Conditions ◽  
Time Varying ◽  
Activation Functions ◽  
Analysis And Design ◽  
Design Procedures ◽  
The Neural Network ◽  
Saturation Region ◽  
The Neural Networks

In this letter, some sufficient conditions are obtained to guarantee recurrent neural networks with linear saturation activation functions, and time-varying delays have multiequilibria located in the saturation region and the boundaries of the saturation region. These results on pattern characterization are used to analyze and design autoassociative memories, which are directly based on the parameters of the neural networks. Moreover, a formula for the numbers of spurious equilibria is also derived. Four design procedures for recurrent neural networks with linear saturation activation functions and time-varying delays are developed based on stability results. Two of these procedures allow the neural network to be capable of learning and forgetting. Finally, simulation results demonstrate the validity and characteristics of the proposed approach.

scholarly journals Control Analysis and Design for Statistical Models of Spiking Networks

2018 ◽  
Vol 5 (3) ◽  
pp. 1146-1156 ◽  
Author(s):  
Anirban Nandi ◽  
Mohammad Mehdi Kafashan ◽  
ShiNung Ching
Keyword(s):  
Statistical Models ◽  
Control Analysis ◽  
Analysis And Design ◽  
Spiking Networks
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