Nonlinear multi-input-multi-output neural network control of DC motor drive with field weakening

Mataušek, Miroslav R.; Miljković, Dubravko; Jeftenić, Borislav

doi:10.1109/41.661322

Cited by 15 publications

(7 citation statements)

References 2 publications

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“…High level control is based on methods described in [18], which suggested high rehabilitation potential, but required a sophisticated haptic platform. Here the PT is used as a lookup table to determine velocity set point, based on current movement phase and performance.…”

Section: The R3-beg Robot Assistantmentioning

confidence: 99%

“…The low level control is based on two single-input-single-output MIMC linear digital controllers [17] to control the shoulder and the elbow of the system. The essential characteristics of the MIMC design and tuning concept from [18] are: it is well suited to exploit the benefits of prior knowledge and experience gained from the open-loop dynamics of the plant; the control system structure is directly obtainable from the model used to approximate process dynamics; a small number of tuning parameters, with clear meaning, followed by simple tuning rules, enough easy to apply. This concept also allows scalability of the presented solution, as it is suitable for designing multiple-input multipleoutput (MIMO) neural network (NN) digital controllers [19].…”

Section: The R3-beg Robot Assistantmentioning

confidence: 99%

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Modified internal model control for a therapeutic robot

2017

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We present the use of the modified internal model controller (MIMC) and the ?Probability Tube? (PT) action representation for robot-assisted upper extremities training of hemiplegic patients. The robot-assisted training session has two phases. During the first "demonstration" phase the robot learns from the therapist the target path through examples. In the second "exercise" phase the robot assists a patient to follow the target path. During this process, the control limits the interface force between the robot and the hand to be below the preset threshold (F = 50 N). The system allows the assessment of the range of movement, the positional error between the target and the reached position, the amount of added assistance (the interface force between the hand and the robot). We demonstrate the operation in two hemiplegic patients. The patients and therapist suggested after the tests that the new system is straightforward and intuitive for clinical applications. [Projekat Ministartsva nauke Republike Srbije, br. RS35003]

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Section: The R3-beg Robot Assistantmentioning

confidence: 99%

Section: The R3-beg Robot Assistantmentioning

confidence: 99%

Modified internal model control for a therapeutic robot

2017

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“…Neural network: The version of the algorithm used was based on [45] and was implemented using the R package neural net [46].…”

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confidence: 99%

An Integrated Turning Movements Estimation to Petri Net Based Road Traffic Modeling

Riouali

Benhlima

Bah

2019

JSAN

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The tremendous increase in the urban population highlights the need for more efficient transport systems and techniques to alleviate the increasing number of the resulting traffic-associated problems. Modeling and predicting road traffic flow are a critical part of intelligent transport systems (ITSs). Therefore, their accuracy and efficiency have a direct impact on the overall functioning. In this scope, a new approach for predicting the road traffic flow is proposed that combines the Petri nets model with a dynamic estimation of intersection turning movement counts to ensure a more accurate assessment of its performance. Thus, this manuscript extends our work by introducing a new feature, namely turning movement counts, to attain a better prediction of road traffic flow. A simulation study is conducted to get a better understanding of how predictive models perform in the context of estimating turning movements.

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“…1). For drive applications requiring high dynamic control performance, it is necessary to take the full-order electromechanical motor system with nonlinearities into account in the closed-loop control design.There has been recent interest in the study of advanced approaches for dealing with the SEDCM drive with eld weakening by adaptive gain scheduling and neural network controllers [5,6]. These approaches appear to be valuable in the situation…”

mentioning

confidence: 99%

“…There has been recent interest in the study of advanced approaches for dealing with the SEDCM drive with eld weakening by adaptive gain scheduling and neural network controllers [5,6]. These approaches appear to be valuable in the situation…”

mentioning

confidence: 99%

Nonlinear Load-Adaptive MIMO Controller for DC Motor Field Weakening

Muhammad

2000

Electric Machines & Power Systems

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Control problem of eld weakening for a separately excited DC motor system, modeled in nonlinear diOE erential equations, is tackled in this paper. A novel constant power eld weakening controller, based on nonlinear load-adaptive multi-input multi-output (MIMO) linearization technique, is developed to achieve high-performance speed tracking through rejecting load disturbance. The eOE ects of decoupling and linearization permit the controller to be implemented and operated at desired eld weakening point of operation. Computer simulations are presented to demonstrate the eOE ectiveness of the proposed controller for a speci c motor. It has been shown that the proposed controller provides higher dynamic performance in comparison with traditional PI controllers, whereas the motor system is run over wide dynamic eld weakening regimes.Implementation of eld weakening is combined with armature voltage control to give a very wide speed range in separately excited DC motor (SEDCM) drive applications. Typical examples of these applications are extensively found in rolling mills, paper mills, robotics, and machine tools. An SEDCM system is modeled by three nonlinear diOE erential equations in eld-weakening region (! ! N ). Therefore, it is di cult to apply the linear control techniques, based on the linearized model about a nominal set point, to the nonlinear system [1,2]. For example, it is clear that the motor speed response becomes worse when it is operated by the traditional linear PI implemented control scheme shown in [2-4] over wide dynamic eld-weakening regimes (Fig. 1). For drive applications requiring high dynamic control performance, it is necessary to take the full-order electromechanical motor system with nonlinearities into account in the closed-loop control design.There has been recent interest in the study of advanced approaches for dealing with the SEDCM drive with eld weakening by adaptive gain scheduling and neural network controllers [5,6]. These approaches appear to be valuable in the situation

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Nonlinear multi-input-multi-output neural network control of DC motor drive with field weakening

Cited by 15 publications

References 2 publications

Modified internal model control for a therapeutic robot

Modified internal model control for a therapeutic robot

An Integrated Turning Movements Estimation to Petri Net Based Road Traffic Modeling

Nonlinear Load-Adaptive MIMO Controller for DC Motor Field Weakening

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