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In this paper, behavior of teleoperation systems with modeling error and delay time error in Smith predictor is discussed. In teleoperation systems, modeling error is inevitable. This paper discusses stability of teleoperation systems with modeling error. First, error of delay time in teleoperation systems by using of Internet as communication channel is considered and the performance of Smith predictor in teleoperation systems with delay time error is discussed. Next, a new structure for teleoperation system is proposed. An adaptive filter is integrated into the new structure for determination of delay time in communication channel. The new structure augments wave variables and Smith predictor to provide an effective method for teleoperation systems. Along with the adaptive filter, this new structure is shown to overcome instability due to the variability of the delay times. Simulations results show significant improvements in the system performance.

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In this paper, the effect of passengers on the chaotic vibrations of the full vehicle model is investigated. The vehicle system is modeled as a full nonlinear seven-degrees of freedom with an aditional one -degree of freedom for each passenger. Four passengers are added sequentially to the vehicle that produces eight, nine, ten and eleven degrees of freedom models, respectively. The effect of passengers on the chaotic vibrations of vehicle is studied for the above mentioned cases. The nonlinearities of the system is due to the nonlinear springs and dampers that are used in the suspension and tires. Roughness of the road surface is considered as sinusoidal waveforms with time delay for tires. The governing differential equations are extracted by Newton-Euler laws and are solved numerically via forth-order Runge-Kutta method. The analysis is conducted first by detecting the unstable regions of the system and then followed by a specific excitation frequency, where there is possibility of chaos. The dynamic behavior of the system is investigated by special nonlinear techniques such as bifurcation diagram, power spectrum, pioncare section and maximum lyapunov exponents. The obtained results represents different types of nonlinear dynamic absorbers in the vehicle with and without passengers. Consideration the passengers and increasing the mass of the system can resultes in a significant changes in the dynamic behavior where improves the chaotic vibration of the vehicle.

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This paper investigates the robust finite time stability and finite time stabilization for a class of uncertain switched systems which have time delay. The emphasis of the paper is on the cases where uncertainties are time varying and unknown but norm bounded. By using the average dwell time approach and multiple Lyapunov like functions, delay dependent sufficient conditions for finite time stability of uncertain switched systems with time delay in terms of a set of the linear matrix inequalities are presented. Then, the corresponding conditions are obtained for finite time stabilization of uncertain switched time delay systems via a state feedback controller. The controller is designed by virtue of the linear matrix inequalities and the cone complement linearization method. We solved the problem of uncertainty in uncertain switched time delay systems by resorting to Yakubovich lemma. Finally, numerical examples are provided to verify the effectiveness of the proposed theorem.
 

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In this paper, a novel methodology is proposed to improve performance of the Networked Control System (NCS) in the face of random time-delays, using Model Predictive Controller (MPC) approach. For this purpose, a new state-feedback MPC structure is developed to cope with random network time-delays when the system is subjected to uncertainties with state and control constraints. The main idea is to reduce the disturbing effect of random network time-delays on regulatory performance of the NCS using a new robust formulation in MPC design. A terminal penalty constraint has been added to the finite horizon objective function to guarantee the stability of the system stability. Finally, applicability of the presented method is evaluated in a real pilot plant within a NCS configuration, being realized by an industrial Ethernet and Foundation Fieldbus technology. It is demonstrated that the proposed online methodology is effective to provide a better performance, having faster response, smaller overshoot and stronger robustness compared to the conventional MPC method with less aggressive control actions.  

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This paper proposes a two phase strategy for proportional myoelectric control of Surena 3 humanoid robot which benefits from strength of two common myoelectric control methods, Pattern recognition base and simultaneous proportional control, for improving joint angle estimation. The aim of this research is to present a human-robot interface to create a mapping between electrical activities of muscles known as electromyogram (EMG) signals and kinematics of corresponding motion. First phase concerns with motion classification using Quadratic Discriminant Analysis (QDA) and Majority Voting (MV). Several common motion classification algorithms and feature vectors including time domain and frequency domain futures were investigated which lead to QDA and a superior feature vector with more than 97% classification accuracy. The second phase concerns with continuous angle estimation of shoulder joint motion classes using Time Delayed Artificial Neural Network (TDANN) with overall accuracy of 90% R2. QDA serves as a high level controller which decides between four TDANN correspond to each shoulder motion classes. QDA and TDANN models trained with several sets of offline data and were tested with online dataset. Online and offline data estimation accuracy and model robustness against disturbances show a significant improvement compared to similar methods in this field.

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In this paper, a robust discrete control law is presented, using a time delay control method for an omnidirectional mobile robot in the presence of system uncertainties. Although time delay control method has attracted the great attention of researchers due to its structure simplicity, the major part of these research have been performed by the assumption of continuous time delay control and infinitesimal time delay that is in contradict of physical nature of digital devices, as implementation tools of time delay controllers, which have finite and specific sample time. Also, the discretization of continuous-time systems has been usually done by Euler estimation method, which has sufficient accuracy for infinitesimal sample times. So, in this paper, after modeling the robot, considering the dynamics of robot motors, a new method for more accurate discretization of continuous nonlinear systems is presented and, then, a robust discrete control law is designed, using the backstepping technique at the voltage level of the robot motors. In the design of control law, a new adaptive sliding mode method is used to overcome the system uncertainties and stability of the closed-loop system is proved by error convergence to a small neighborhood of zero. The proposed controller is designed in the discrete domain without the necessity of being known the bound of system uncertainties and simulation results represent the desired performance of the controller in trajectory tracking.
 

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