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International Conference on Instrumentation control and Automation (ICA)

作者： Augie Widyotriatmo A. K. Pamosoaji G.-Y. Hong Keum-Shik Hong Instrumentation and Control Institut Teknologi Bandung Bandung Indonesia School of Mechanical Engineering Pusan National University Busan South Korea Department of Cogno-Mechatronics Engineering Pusan National University Busan South Korea

This paper presents the architecture of autonomous material handling vehicles. The centralized coordination of multiple vehicles and three-layer architecture (deliberative, sequencing, and reflexive layers) are adopted. The navigation controls, including configuration control, visual servoing, path tracking, and collision avoidance, are developed. The finite state machine (FSM) that supervises the control modules to complete the material handling task is elucidated. The experimental results of a forklift transporting a pallet from an initial to a desired goal configuration are demonstrated.

关键词： Tracking Laser applications Handheld computers Instruments Universal Serial Bus Vehicles

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New simplified model for an under-actuated quadruped robot in bounding motion

New simplified model for an under-actuated quadruped robot i...

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International Conference on control, Instrumentation, and Automation

作者： Hamed Kazemi Vahid Johari Majd Majid M. Moghaddam Intelligent Control Systems Laboratory School of Electrical and Computer Engineering Tarbiat Moalem University Tehran Iran Intelligent Control Systems Laboratory Tarbiat Modares University Tehran Iran Robotics and Mechatronics Laboratory Mechanical Engineering Department Tarbiat Moalem University Tehran Iran Mechanical Engineering Department Tarbiat Modares University Tehran Iran

In this paper, a quadruped robot is studied in bounding motion. A new simplified model of quadruped robot in bounding motion with four actuated and two unactuated joints is developed. The kinetic and potential energies of the under-actuated mechanical model of the quadruped robot are obtained and the dynamics of the robot model is derived using the Lagrangian method. It is shown that the dynamical equation of the proposed simplified model belongs to a class of second-order nonholonomic mechanical systems. The main motivation of this paper is to obtain quadruped model in bounding motion such that one can apply different control methods directly or after transformation in the obtained dynamic equations. Utilizing MATLAB, dynamics of the planar model has been simulated in backward and forward states. Physical parameters of the Little-Dog robot as an instance of the quadruped robot are considered in simulation The simulation is without control and therefore is unstable but it illustrates robot's manner in bounding motion before instability.

关键词： Mathematical model Legged locomotion Dynamics Equations Joints Robot kinematics

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A novel type of trigonometric neural network trained by Extended Kalman Filter

A novel type of trigonometric neural network trained by Exte...

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International Workshop on Advanced Computational Intelligence (IWACI)

作者： M. Norouzi M. Mansouri M. Teshnehlab M. Aliyari Shoorehdeli Faculty of Engineering Department of Computer Engineering Science and Research Branch Islamic Azad University Iran Intelligent System Laboratory (ISLAB) Faculty of Electrical Engineering Control Department K.N. Toosi University of Technology Tehran Iran Faculty of Electrical Engineering Department of Mechatronics Engineering Advanced Process Automation &Control Laboratory (APAC) K.N. Toosi University of Technology Tehran Iran

In this study, a new type of trigonometric neural network is presented by adding frequency and phase to trigonometric activation functions. The proposed trigonometric neural network has more flexibility in comparison with conventional trigonometric neural networks and even other types of neural networks. Due to the low convergence rate and high posibility of trapping in a local minimum of backpropagation algorithm, Extended Kalman Filter algorithm is used to train the neural network's parameters which they appear in a nonlinear form. The Simulation of the suggested neural network based on the prediction of Mackey-Glass time series and identification of a nonlinear dynamic ystem reveals the efficiency of the proposed network. To show the efficiency of this method, the results are compared with the results of the others.

关键词： Biological neural networks Kalman filters Equations Neurons Vectors Covariance matrix Mathematical model

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Ischemia Prediction via ECG using MLP and RBF predictors with ANFIS Classifiers

Ischemia Prediction via ECG using MLP and RBF predictors wit...

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2011 Seventh International Conference on Natural Computation(第七届自然计算国际会议 ICNC 2011)

作者： Hoda Tonekabonipour Ali Emam Mohamad Teshnelab Mehdi Aliyari Shoorehdeli Mechatronics Department Qazvin Islamic Azad University Qazvin Iran Electrical Engineering K.N.Toosi University of Technology Tehran Iran Advanced Process Automation and Control (APAC)

In this paper, a new algorithm is presented in using Multi Layer Perceptron (MLP) and Radial Base Function (RBF) to predict Ischemia diseases by Electrocardiogram (ECG) signals. The process would be very difficult due to non-stationary and nonlinear characteristics of ECG signals. MLP and RBF algorithms are well known in predicting the problems. However, they have not been used for real time prediction through signals, especially bio signals such as ECG. Pre-processing is necessary for ECG signal in order to detect QRS complex. Regarding the extract influential features in Ischemia disease, the baseline wandering and noise suppression are done. MLP and RBF, the predictors, are employed to foresee the further next beats in ECG signals. The validity of predictor accuracy is evaluated by Root Mean Square Error (RMSE) criterion. After the prediction stage, The predicted beats are classified by Adaptive Neuro-Fuzzy network (ANFIS) classifier as ischemic and normal. MLP and RBF are tested for their abilities in order to predict Ischemic Heart Disease (IHD) upon ECG signals. The performances of classified beats are evaluated based on computed Sensitivity (Se) and Specificity (Sp). In this study several ECG signals recorded by European Society of Cardiology for ST-T database are used. By applying prediction methods (Direct and Recursive Predictions) 48 steps can be predicted ahead in ECG signal. Then the predicted beats are classified as Ischemic or normal beats. Therefore, the ischemic beats can be predicted in 48 steps ahead. By comparing the results obtained in this study, the MLP and RBF networks are evaluated for their capabilities in predicting Ischemia. According to this comparison, MLP shows better results and the results of ANFIS as a classifier has been satisfactory enough in classification of Ischemic beats. Therefore, these results can be used for early diagnosis of Ischemic Heart Disease (IHD).

关键词： RBF MLP ANFIS Neuro-Fuzzy ECG Prediction Classification.

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Improved integral fuzzy sliding mode control for a class of nonlinear uncertain systems

Improved integral fuzzy sliding mode control for a class of ...

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Chinese control Conference (CCC)

作者： Wen-Qiang Li Peng Li Lian Li Yi Zhang Department of Control Engineering Naval Aeronautical and Astronautical University Yantai P. R. China College of Mechatronics Engineering and Automation National University of Defense Technology Changsha P. R. China

For the conventional sliding mode control of a class of nonlinear uncertain systems, the ranges of sliding mode error and steady-state error are deduced. In order to reduce the steady-state error while anti-windup, an improved integral sliding surface is designed, and an improved integral fuzzy sliding mode control approach is proposed based on this sliding surface. In this approach, the integral action is reduced through adjust factor when the sliding variable outside the boundary layer. Then, the large overshoots due to the large initial errors can be avoided. When sliding variable inside the boundary layer, the integral action is conventional in order to reduce the steady-state error. The adjust factor is automatically tuned by real time fuzzy inference. Finally, an inverted pendulum control is used to illustrate the effectiveness and robustness of the proposed approach.

关键词： Steady-state Integral equations Sliding mode control Robustness Switches Transient analysis Laplace equations

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Designing flexible neuro-fuzzy system based on sliding mode controller for magnetic levitation systems

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International Journal of Computer Science Issues 2011年第4 4-1期8卷 160-171页

作者： Mohammadi, Zahra Teshnehlab, Mohammad Shoorehdeli, Mahdi Aliyari Electrical Engineering Department Science and Research Branch of Islamic Azad University Tehran Iran Faculty of Electrical Engineering Department of Control Engineering K. N. Toosi University of Technology Tehran Iran Faculty of Electrical Engineering Department of Mechatronics Engineering K. N. Toosi University of Technology Tehran Iran

This study presents a novel controller of magnetic levitation system by using new neuro-fuzzy structures which called flexible neuro-fuzzy systems. In this type of controller we use sliding mode control with neuro-fuzzy to eliminate the Jacobian of plant. At first, we control magnetic levitation system with Mamdanitype neuro-fuzzy systems and logical-type neuro-fuzzy systems separately and then we use two types of flexible neuro-fuzzy systems as controllers. Basic flexible OR-type neuro-fuzzy inference system and basic compromise AND-type neuro-fuzzy inference system are two new flexible neuro-fuzzy controllers which structure of fuzzy inference system (Mamdani or logical) is determined in the learning process. We can investigate with these two types of controllers which of the Mamdani or logical type systems has better performance for control of this plant. Finally we compare performance of these controllers with sliding mode controller and RBF sliding mode controller.

关键词： controllers

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Intelligent control of human prosthetic eye movements system for the emotional support by a huggable pet-type robot via Gaussian RBF neural network based on sliding mode control

Intelligent Control of human prosthetic eye movements system...

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International Conference on control, Instrumentation, and Automation

作者： Faezeh Farivar Mojtaba Rostami Kandroodi Mahdi Aliyari Shoorehdeli Department of Mechatronics Engineering Islamic Azad University Tehran Iran Control & Intelligent Processing Center of Excellence University of Tehran Tehran Iran Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran

In this study, intelligent control of human eye movements system for the emotional support by a huggable pet type robot via Gaussian RBF neural network based on sliding mode control is presented. Despite active research and significant progress in the last three decades on control of human eye movements, it remains challenging issue due to its applications in prosthetic eyes and robotics. The geometry and model of human eye movements system are investigated and this system is considered as a nonlinear control system. The specified model may only be an academic exercise. It can have scientific importance in understanding of the human movement system in general. Also, it can be useful for robotics. By using Gaussian RBF Neural Networks Based on Sliding Mode control, the control goal can be achieved. The adaptation laws of designed controllers are obtained based on sliding mode control methodology without calculating the Jacobian of the system. The proposed method is capable to control of human eye movements system. Intelligent methods such as artificial neural networks are proposed to control the human eye movements and numerical simulations are presented. It is concluded that the intelligent controls applied to control of human eye movements system are emulated from the neural controls in biological system.

关键词： Humans Robots Mathematical model Sliding mode control Intelligent control Geometry

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On the skew and sway control of container cranes

On the skew and sway control of container cranes

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International Conference on control, Instrumentation, and Automation

作者： M. Mahrueyan H. Khaloozadeh Mechatronics engineering K. N. Toosi University of Technology Tehran Tehran Iran Systems and control department K. N. Toosi University of Technology Tehran Tehran Iran

It is conventional to control the sway of the container cranes based on a two dimensional model. Unfortunately, two dimensional models are not capable of controlling the skew of container cranes. Moreover, the anti-sway controllers make the skew intensified. In this paper, we add another degree of freedom to a three dimensional container crane model by installing two wagons in the trolley to impose a couple force for regulating both its sways and skew to zero using State Dependent Riccati equation (SDRE) controller. As the couple force only have rotational effect on the container platform, and is a free vector it will not change the dynamic of the system. Furthermore, SDRE controllers are the extended version of LQR, they will lead into an optimal result while being simple in controlling a system with three inputs and being loyal to nonlinear characteristics of the system. We will simulate the controller on a 3D model with the trolley acceleration of 0.8.

关键词： Containers Cranes Mathematical model Solid modeling Force Equations control systems

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Gearbox Ripple Rejection of Robots Using Observer and Adaptive control Theory

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IFAC Proceedings Volumes 2011年第1期44卷 893-898页

作者： Sebastian Maier Johann Bals Marc Bodson Department of System Dynamics and Control Institute of Robotics and Mechatronics German Aerospace Center (DLR) 82234 Wessling Germany Muenchner Str. 20 Department of Electrical and Computer Engineering University of Utah 50 S Central Campus Dr. Salt Lake City UT 84112 USA

Abstract Robots are often run with permanent magnet synchronous motors (PMSM) with a high ratio gearbox. Both parts can produce parasitic oscillations (ripples), which let the robot shake at tool center point. The gearbox ripple problem is more complicated to be solved with control theory because only motor side sensors should be used. Due to the internal model principle gearbox side information is necessary to solve the problem. The first algorithm uses an observer to get gearbox side information where the second algorithm uses a gearbox side rate sensor. The algorithms are tested with a nonlinear SISO problem and with a nonlinear MIMO system. In both cases the ripples are canceled with an adaptive controller which estimates the phase and magnitude of the ripple. This adaptive controller is designed separately and is added to the existing basis controller. The algorithms are tested in simulation and on a testbed, which is an industrial application.

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A Complementary Modularized Ramp Metering Approach Based on Iterative Learning control and ALINEA

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IEEE Transactions on Intelligent Transportation Systems 2011年第4期12卷 1305-1318页

作者： Zhongsheng Hou Xin Xu Jingwen Yan Jian-Xin Xu Gang Xiong Advanced Control Systems Laboratory School of Electronic and Information Engineering Beijing Jiaotong University BJTU Beijing China Institute of Automation College of Mechatronics and Automation National University of Defense Technology Changsha China Department of Electrical and Computer Engineering National University of Singapore Singapore Automation Institute Chinese Academy of Sciences (CAS) Beijing China

Ramp metering is an effective tool for traffic management on freeway networks. In this paper, we apply iterative learning control (ILC) to address ramp metering in a macroscopic-level freeway environment. By formulating the original ramp metering problem as an output regulating and disturbance rejection problem, ILC has been applied to control the traffic response. The learning mechanism is further combined with Asservissement Linéaire d'Entrée Autoroutière (ALINEA) in a complementary manner to achieve the desired control performance. The ILC-based ramp metering strategy and the modified modularized ramp metering approach based on ILC and ALINEA in the presence of input constraints are also analyzed to highlight the advantages and the robustness of the proposed methods. Extensive simulations are given to verify the effectiveness of the proposed approaches.

关键词： Traffic control Mathematical model Convergence Learning systems Feedforward neural networks

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