In this paper, an efficient algorithm is presented for solving the 2-D optimization problem which is associated with computing the robustness measures of a number of linear time-invariant (LTI) system properties such ...
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In this paper, an efficient algorithm is presented for solving the 2-D optimization problem which is associated with computing the robustness measures of a number of linear time-invariant (LTI) system properties such as the controllability radius, the decentralized fixed-mode radius, and the minimum-phase radius. Unlike methods such as gradient search methods, the proposed algorithm works well independent of the initial trial point, and obtains the minimum with a high level of confidence that it is indeed global. A numerical example is included.
This paper presents a new design and implementation tracking and balancing controller for ball and beam system using a digital camera as a ball position sensor. A new setup, including vision feedback and employing xPC...
This paper presents a new design and implementation tracking and balancing controller for ball and beam system using a digital camera as a ball position sensor. A new setup, including vision feedback and employing xPC targetreg makes it easy to implement various controllers. System identification and controller design is conducted in real time manner. New arrangement can be used in a tele-lab operation for educational and research purposes. A Simulinkreg model is developed to do both simulation (analysis, synthesizes and controller design) and real time implementation. Indeed, the proposed method has hardware in the loop property. Ball and beam system is severely nonlinear, so we utilize two stage controller to manage with this problem. Simulation and experimental results show the effectiveness of the proposed controller and exploit rapid prototyping property of the setup as well.
This paper presents an optimum approach to design input-output feedback linearization (IOFL) controller for a rotary inverted pendulum (RIP) using the Binary Genetic Algorithm. Genetic Algorithms (GAs) are stochastic ...
This paper presents an optimum approach to design input-output feedback linearization (IOFL) controller for a rotary inverted pendulum (RIP) using the Binary Genetic Algorithm. Genetic Algorithms (GAs) are stochastic global search methods that emulate the process of natural evolution and because of their simplicity and robustness, they are more popular and applicable. The primary design goal is to minimize the integral absolute error of system angles and velocities and balance the pendulum in the inverted position by minimizing overshoot, settling time and rise time of step response. An objective function using these indexes is established. Then by minimizing the objective function using Binary Genetic algorithm, the optimal controller parameters can be assigned. Simulation results verified capable and competent characteristics of proposed optimal feedback linearization controller. The proposed method can be considered as a promising way for control of various similar nonlinear systems.
The paper presents some spectral analysis results of acoustic emission observed during ultrasound driven round bottomed flask with fresh insulating oil inside. At suitable value of signal amplitude and frequency many ...
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ISBN:
(纸本)9784886860057
The paper presents some spectral analysis results of acoustic emission observed during ultrasound driven round bottomed flask with fresh insulating oil inside. At suitable value of signal amplitude and frequency many of cavitation bubbles were observed. Collapsing bubbles were responsible for broadband noise included in acoustic emission signal spectra. To represent the cavitation intensity a simple cavitation indicator based on power spectral densities of acoustic emission signal was proposed.
The paper presents streaming current distributions measured in an overflow system in both laminar and turbulent conditions. For lower values of Reynolds number the profile of current is parabolic. For higher values of...
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ISBN:
(纸本)9784886860057
The paper presents streaming current distributions measured in an overflow system in both laminar and turbulent conditions. For lower values of Reynolds number the profile of current is parabolic. For higher values of Reynolds number the profile is flattened. In this paper also charge density distributions were determined in both cases. In the turbulent regime the volume charge density is distributed in the pipe more evenly compared with the laminar regime.
This paper presents a robust adaptive control design methodology for multi-input multi-output (MIMO) plants based on Quantitative Feedback Theory (QFT) and Externally Excited Adaptive System (EEAS), both of which are ...
This paper presents a robust adaptive control design methodology for multi-input multi-output (MIMO) plants based on Quantitative Feedback Theory (QFT) and Externally Excited Adaptive System (EEAS), both of which are the novel ideas of Horowitz. Self Oscillating Adaptive Systems (SOAS) are proposed to mainly overcome the problem of large gain variations, which is important in certain applications. To further improve the SOAS design, the idea of EEAS was developed. Finally, combined QFT and EEAS proposed a robust adaptive controller for SISO uncertain plants. However, due to the complex design nature of the proposed combined methodology and the difficulty of an optimal design, this line of Horowitz's research was not followed further. In this paper, to overcome the above mentioned problems the design procedure is reformulated as a set of cost functions and constraints. Genetic Algorithms are then used to solve the optimal design. Also, QFT/EEAS design is extended to multivariable uncertain plants. Sufficient conditions are derived to assure the achievement of given off-diagonal performance. Then, the given main channel performance could be achieved by using SISO QFT/EEAS method. Simulation studies indicate the effective performance of the proposed QFT/EEAS MIMO design methodology. It is shown that the proposed approach can handle large plant parameter uncertainties with lower loop bandwidths.
In both industrial and research areas of electronic engineering,Sound Source Localization for robot control has always been an interesting subject to be further *** some dangerous situation,especially when a special d...
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In both industrial and research areas of electronic engineering,Sound Source Localization for robot control has always been an interesting subject to be further *** some dangerous situation,especially when a special driver is required to implement a particular task,the device should be able to combine robotics control technology with Sound Source Localization,and take actions according to the different response *** this research project,a multifunc-tional model driver,named "Mobile Island",has been designed and built up by integrating the Emulator 8051 micro-controller,Intel 8255 interfaces,some components and other necessary *** intelligent Mobile Island imple-mented by C language programs can operate under three control *** the sound control Mode 1,the model driver can detect and track a target by Sound Source Localization and then turn and move toward the *** the keypad control Mode 2,it can be controlled by a manual *** the free run Mode 3,Mobile Island can move and turn by *** finding an object in front,it will turn away before moving forward again,so that it can avoid crashing on the obstacle.
Temperature is very important parameter of the human body. By measuring the body temperature early diagnoses of the simple diseases such as fever are possible. In patient suffering from a fever the body temperature ha...
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The main goal of this study is to afford an involvement to the control problem of horizontal axis wind power plants by means of neural network approach. The current paper is a part of a research plan to study the dyna...
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The main goal of this study is to afford an involvement to the control problem of horizontal axis wind power plants by means of neural network approach. The current paper is a part of a research plan to study the dynamics and control of horizontal axis wind turbines. This work presents a novel methodology to control wind power plants. It makes use of an adaptive neural networks self-tuning control system of medium scale wind turbine system, through different operating conditions. The planned control system consists of neural networks forward and inverse identifiers, which are used to model their dynamics, and to adapt neural controller parameters. A reference model is used to enhance the training course and neural controller which is used to produce control signal to the pitch angle actuator. The planned control system carry out high-quality performance which reveal that the proposed control system is in fact an innovative contribution in the control field of horizontal axis wind turbine power generation systems judge against with previous works.
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