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Multiple use of the fractional-order differential calculus in the model predictive control

Multiple use of the fractional-order differential calculus i...

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international conference on methods and models in automation and robotics (MMAR)

作者： Stefan Domek Faculty of Electrical Engineering West Pomeranian University of Technology Szczecin Poland

In the paper a multiple use of the fractional-order differential calculus theory in the model predictive control is proposed. First, the principle of the integer-order linear predictive control and theoretical foundations of the fractional-order differential calculus are reminded. Using the presented theoretical foundations attention is focused further on the possibility of developing the fractional-order model predictive control with an internal process model and a fractional-order cost function. the introduction of the fractional-order differential calculus at the stage of synthesizing the control algorithm offers an additional degree of freedom in tuning a control loop. the discussion is illustrated with results of some laboratory experiments.

关键词： Predictive control Calculus Cost function Predictive models Prediction algorithms Computational modeling Vectors

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A new output feedback adaptive input time-delay compensation scheme for uncertain systems

A new output feedback adaptive input time-delay compensation...

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international conference on methods and models in automation and robotics (MMAR)

作者： Boris Mirkin Per-Olof Gutman Yuri Shtessel Faculty of Civil and Environmental Engineering Technion – Israel Institute of Technology Haifa Israel University of Alabama in Huntsville Huntsville Alabama USA

Design of output feedback model reference adaptive control (MRAC) for a class of systems with input delay based only on the lumped-delays is developed. To overcome the difficulty to directly predict the plant output, a control design is proposed based on new approach. the approach relies on a decomposition of the adaptive control design procedure where a “generalized error”, and auxiliary linear filters with adjustable gains are introduced. the effect of such a decomposition is to pull the input delay out of first step of the design procedure.

关键词： Delays Adaptation models Adaptive control Equations Delay effects Mathematical model Transfer functions

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Modeling of distributed parameter processes with neural networks

Modeling of distributed parameter processes with neural netw...

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9th international conference on Modeling and Optimization of the Aerospace, robotics, Mechatronics, Machines-Tools, Mechanical Engineering and Human Motricity Fields, OPTIROB 2014

作者： VǍlean, Honoriu Abrudean, Mihail Ungureşan, Mihaela Ligia Clitan, Iulia Mureşan, Vlad Technical University of Cluj-Napoca Automation Department 26-28 Bariţiu Street 400027 Cluj-Napoca Romania Technical University of Cluj-Napoca Physics and Chemistry Department 103-105 Muncii Street 400641 Cluj-Napoca Romania

ISBN: (纸本)9783038351115

In this paper an original solution for the modeling of distributed parameter processes using neural networks is presented. the proposed method represents a particular alternative to a very accurate modeling-simulation method for this kind of processes, the method based on the matrix of partial derivatives of the state vector (Mpdx), associated with Taylor series. In order to compare the performances generated by the two methods, a distributed parameter thermal process associated to a rotary hearth furnace (R.H.F) from the technological flow of producing seamless steel pipes is considered. the main similarities and differences between the two methods are highlighted in the paper. the treated solution represents a premise for the usage of the neural networks in the automatic control of the distributed parameter processes domain. © (2014) Trans Tech Publications, Switzerland.

关键词： automation

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Modeling and identification of a fractional-order discrete-time SISO Laguerre-Wiener system

Modeling and identification of a fractional-order discrete-t...

引用

international conference on methods and models in automation and robotics (MMAR)

作者： Rafal Stanisławski Krzysztof J. Latawiec Marcin Gałek Marian Łukaniszyn Department of Electrical Control and Computer Engineering Opole University of Technology Opole Poland

this paper presents a new implementable strategy for modeling and identification of a fractional-order discrete-time nonlinear block-oriented SISO Wiener system. the concept of modeling of a linear dynamics by means of orthonormal basis functions (OBF) is employed to separate linear and nonlinear submodels, which enables a linear regression formulation of the parameter estimation problem. Finally, discrete-time Laguerre filters are uniquely embedded in modeling of the fractional-order dynamics, eliminating the disastrous bilinearity issue. Simulation experiments show a very good identification performance for a fractional-order Laguerre-based Wiener model, both in terms of low prediction errors and accurate reconstruction of the actual system characteristics.

关键词： Computational modeling Mathematical model Nonlinear dynamical systems Predictive models Adaptation models Stability analysis Approximation methods

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Speed calculation methods in electrical drive with non-ideal position sensor

Speed calculation methods in electrical drive with non-ideal...

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international conference on methods and models in automation and robotics (MMAR)

作者： Dominik Łuczak Krzysztof Nowopolski Krzysztof Siembab Bartłomiej Wicher Institute of Control and Information Engineering Poznan University of Technology Poznan Poland

In this paper three methods of electric motor angular speed calculation are compared. the source of the measurement signal is a 14-bit absolute encoder. the authors compared the well-known classic methods M with more advanced approaches. First of the complex methods is based on utilization of phase loop lock system in an estimation process using on-line system model. the third method discussed in the paper is focused on application of Chebyshev filter. Short description of all of the mentioned method is followed by simulation and experimental results. the results are presented on an instance of permanent magnet synchronous motor drive, with both speed controller and speed calculation algorithms implemented in a digital signal processor system.

关键词： Phase locked loops Low-pass filters Transfer functions Digital filters Position measurement Chebyshev approximation Mathematical model

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A gain-scheduled multivariable LQR controller for permanent magnet synchronous motor

A gain-scheduled multivariable LQR controller for permanent ...

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international conference on methods and models in automation and robotics (MMAR)

作者： Michał Brasel Faculty of Electrical Engineering West Pomeranian University of Technology Szczecin Szczecin Poland

the paper presents a gain-scheduled LQR control system for a nonlinear model of permanent magnet synchronous motor (PMSM). the most popular cascade FOC (Field Oriented Control) structure including a few single-loop PI control systems is replaced with a single multivariable state feedback controller. Due to a nonlinear nature of the PMSM dynamics equations the developed gain-scheduled controller is tuned in relation to the changeable operating conditions of the motor. In order to ensure zero steady-state speed error the system synthesis is carried out by means of the LQ optimal control method with state vector augmentation. the presented simulation results show that the use of gain-scheduled controller may improve control quality.

关键词： Control systems Vectors Permanent magnet motors Rotors Torque Mathematical model Adaptation models

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Modelling an accelerometer for robot position estimation

Modelling an accelerometer for robot position estimation

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international conference on methods and models in automation and robotics (MMAR)

作者： Zdzisław Kowalczuk Tomasz Merta Faculty of Electronics Telecomm. and Informatics Gdańsk University of Technology Gdańsk Poland Dept. of Robotics and Decision Systems (ETI) Gdańsk University of Technology Gdańsk Poland

the article describes a new model of a MEMS accelerometer for usage in inertial measurement units (IMU). Such units allow to measure orientation and location of the sensor/system and therefore can be applied for systems positioning. the main purpose of the paper is to model pertinent accelerometer functions substantial in determination of the location of the sensor by means of double integration of acceleration. the model takes into account static and dynamic working conditions. Based on this model an estimator is constructed that allows us to test the developed system in terms of the effects of rotational dynamics. Computer simulations are applied to illustrate the performance of the estimator for simulated measurement signals. the results obtained show what conditions must be met in order to properly determine the linear acceleration with accelerometer measurements.

关键词： Acceleration Accelerometers Robot sensing systems Noise Gravity Micromechanical devices

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2D systems based iterative learning control design for multiple-input multiple-output systems

2D systems based iterative learning control design for multi...

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international conference on methods and models in automation and robotics (MMAR)

作者： Lukasz Hladowski thanh Van Dinh Krzysztof Galkowski Eric Rogers Chris T Freeman Institute of Control and Computation Engineering University of Zielona Gora Poland Electronics and Computer Science University of Southampton UK

Iterative learning control can be applied to systems that repeat the same task over a finite duration with resetting to the starting location once each one is complete. the novel feature is the use of information from previous executions of the task in order to update the control signal applied during the next one and thereby sequentially improve performance. Linear iterative learning control laws can be designed using 2D systems theory and recently experimental validation of such designs for single-input single-output examples has been reported. this paper gives the first results on extending this approach to systems with more than one input and output.

关键词： MIMO Vectors Stability analysis Asymptotic stability State-space methods Robots Convergence

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Estimating the time-varying parameters of SDE models by maximum principle

Estimating the time-varying parameters of SDE models by maxi...

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international conference on methods and models in automation and robotics (MMAR)

作者： Darya V. Filatova Andrzej Orłowski Vasilii Dicoussar Jan Kochanowski University in Kielce Kielce Poland Kielce Poland Dorodnicyn Computing Centre of RAS Moscow Russian Federation

We present a parameter estimation method of stochastic differential equations with time-varying coefficients, where data can be observed at discrete points of time. Our objective is to develop the uniform mathematical technique to solve the parameter estimation problem for stochastic differential equations with both ordinary and fractional Brownian motions. this estimation principle is based on the replacement of a stochastic differential equation by a system of ordinary differential equations, which present the moment functions, and on the application of the Pontryagin's maximum principle to find the optimal estimates of the time-varying coefficients of the initial equation. the key point is the constraints structural selection, which leads to major modifications of algorithms of analytical and numerical solutions. this estimation method is applied to study the North Atlantic herring population dynamics.

关键词： Estimation Equations Stochastic processes Differential equations Parameter estimation Optimal control Sociology

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Data-driven self-tuning control by iterative learning control with application to optimize the control parameter of turbocharged engines

Data-driven self-tuning control by iterative learning contro...

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international conference on methods and models in automation and robotics (MMAR)

作者： René Noack Torsten Jeinsch Adel Haghani Abandan Sari Nick Weinhold Adel Haghani Abandan Sari Institute of Automation University of Rostock Rostock Germany Universitat Rostock Rostock Mecklenburg-Vorpommern DE Department Powertrain Mechatronics Gasoline Engine Systems IAV GmbH Gifhorn Germany

the applications of iterative learning control (ILC) in control of modern process and mechatronic system have received more attentions in recent years. this is due the fact that ILC does not depend on physical model of the system. In the application of ILC in automotive industry, the restriction is that these methods calculate the input value and the tuning of an available controller with fixed structure is not possible. To solve this problem a method is proposed in this paper which consists of two main steps: the first step is the calculation of an input variable, based on an ILC algorithm, and the second step is the optimization of the given parameters of the feedforward controller. the performance and effectiveness of the proposed method are shown with experiments on a test vehicle with an one stage turbocharged gasoline motor with wastegate.

关键词： Vectors Feedforward neural networks Optimization Engines Tuning Atmospheric modeling Mathematical model

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