فهرست مطالب mohammad reza jahed motlagh

Designing a walking gait for biped robots, that can preserve stability against a known range of disturbances, is very important in real applications. In the area of biped robots with point-feet, designing an exponentially stable walking gait with desired features has been recently done by an online reinforcement learning method called PI^2-WG. However, the designed gait might not be robust enough against disturbances. Therefore, we extend a robust version of PI^2-WG to design an exponentially stable walking gait which is robust against modeling errors/disturbances and we call it R-SPI^2-WG. It is done by minimizing the costs of worst rollouts which are generated in presence of different modeling errors/disturbances. We study the ability of the proposed method to adapt the controller of RABBIT, which is a planar biped robot with point-feet, for some robust applications. The simulation results show that the designed gaits are exponentially stable and robust against modeling errors/disturbances in a feasible range.

Based on the recent Internet advances, congestion control is considered as an important issue and has spurred a significant amount of research. In this study, second-order sliding mode control is used to adjust the average queue length and maintain the closed-loop system performance. The control law is obtained in two steps. First, the nonlinear state-space form of the network is extracted based on state variables as the average queue length and congestion window size. Then, the proportional-Integrator-derivative and proportional- derivative sliding surface are defined according to the tracking error. Also, in order to avoid chattering, the derivative of the sliding surface is considered and the closed-loop system stability is investigated based on Lyapunov theory. The proposed scheme renders good tracking specifications and closed-loop system robustness. The simulation results show that the proposed methods outperform proportional integral (PI) and proportional integral derivative (PID) schemes. Also, robustness to disturbances increases and chattering and transient response degradation are avoided.

Sliding mode control technique is one of the well-recognized non-linear control methods. This method has an advantage like robustness against uncertainties. However, chattering phenomenon constraints the performance of closed loop system. To increase its efficiency, a fuzzy compensator is used along with this method. The fuzzy compensator weights are updated by using adaptive rules. The adaptation rate acts as a controlling coefficient. Therefore, the bigger amount of it increases the adaptation speed of weights which leads to the improvement of closed loop system performance. As a result, the probability of instability of closed loop system increases, too. In this study, it has been proposed to use a parallel fuzzy system along with the main fuzzy system in order to control its weight's adaptation. Moreover, a non-linear model of the electro-hydraulic system has been introduced as a case study. Finally, the performance of closed loop system and the efficiency of the proposed methods have been investigated by using numerical simulations.

In this paper a controller has been presented based on the predictive control to drive and control the bipedal Nao robot. One of the challenges in the practical applying of these types of controllers is their high computational loading and the time-consuming control operations in each time step, in which it is suggested to use Laguerre Functions to reduce the computational loading of the predictive controller. In this study, at first using the conventional methods for the identification, and via the real data obtained from the Nao robot in Mechatronics research center of Qazvin Azad University, a proper model is proposed for walking the Nao robot which is considered as a two-dimensional motion in the plane. Then a controller will be designed to control the robot motion using the model based predictive controller. The purpose of this control approach in the first place is to stabilize the walking of the robot and then to guide and keep it on the desired trajectory, so that this trajectory tracking can be performed well as much as possible. Moreover, in order to evaluate the efficiency of the proposed controller, this controller has been compared with a proportional-integral-derivative controller and will be studied. The simulation results show the effectiveness of the proposed controller performance in the robot trajectory tracking, which finally comparing the obtained results from both of the control approaches, indicates the efficiency and different capabilities of the proposed method in this study.

In this paper, estimation of second order polynomial systems’ domain of attraction via rational Lyapunov function is investigated. One of the methods for estimating DA is to find the greatest level set. In this study, in order to obtain the greatest level set, cost function based on increasing the region enclosed to the level set has been offered instead of using shape factor. Estimating DA has been converted into solving bilinear matrix inequality optimization problem. Capacity of this method compared to other methods in recent studies has been shown through some examples.

This paper investigates the leader-follower formation control problem of nonholonomic mobile robots based on backstepping technique composed with the bio-inspired neurodynamics while avoiding collision with obstacles. Kinematics model of robot and nonholonomic constraint are introduced and formation control scheme is formed based on backstepping technique. In order to solve velocity jump in backstepping kinematics model, the bio-inspired neurodynamic approach is used. In most of the previous studies, researches are used separation-bearing approach and also supposed that desired separation and bearing are constant. In this paper this assumption is relaxed and desired separation and bearing are considered to be time varying. Error dynamics equations are derived and a new controller is proposed. Also an auxiliary reference angular velocity control law is proposed to guarantee global asymptotic stability of the followers and local asymptotic stability of the entire formation according to direct method of Lyapunov. A common example of changing the formation is obstacle avoidance, when an obstacle is located within a follower path and is not in its leader path. Time varying functions for desired separation and bearing are chosen and the new controller is developed with its proof of stability. Simulations results reveal that each follower robot can track its real time leader employing the proposed kinematic controller while avoiding obstacles. Furthermore control inputs at the start moment and also while avoiding obstacles, do not contain impractical jumps and are reasonable thanks to integrating bio-inspired neurodynamic with backstepping technique.

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.

Surge and rotating stall phenomena are two dynamic instabilities that occur in both axial and centrifugal compressors. Surge is the stream instability phenomenon in compressor that imposes severe damages to the compressors. Nowadays، suppressing surge phenomenon is one of the most important issues in oil and gas industries، especially when flow reduction or gas reflux is considered. This research seeks to extract the required technical information about control lines، surge lines، and to present a new combined method to determine the performance curve of 6 rows of gas compressors in Asmari Kupal gas pressure boost station (National Iranian South Oil Company) made in Germany by MAN BORSIG Company، and to design a smart controller in order to increase the reliability of the control system and improve the machine performance. Finally، the system performance validity is shown by simulating a surge characteristic curve and implementing two points of the compressor operation condition

Surge is one of the two destructive factors in compressors. surge is the stream instability phenomenon in compressor that imposes severe damages to the compressors. Nowadays، suppressingsurge phenomenon is one of the most important issues in oil and gas industries، especially when flow reduction or gas reflux is considered. According to Moore-Greitzer compressor model، this paper designs an active controller for surge control in constant speed centrifugal compressors. As such، the applied operator considered for surge control is Close Couple Valve (CCV) and it is designed to stabilize a centrifugal compressor system with disturbaces using nonlinear predictive controller. The proposed controller، without any information about the amount of Throttle Valve variations، could control the surge instability and reduce the distance between compressor operation point and the surge line. Finally، the compressor system with controller is simulated and the obtained results will show the efficiency of the designed nonlinear predictive controller

Fuzzy controllers are being used in various control schemes. The aim of this work was adjusting hemodialysis machine parameters utilizing a fuzzy logic controller (FLC) so that patient’s hemodynamic condition remains stable during hemodialysis treatment. For this purpose a comprehensive mathematical model of the arterial pressure response during hemodialysis, including hemodynamic, osmotic, and regulatory phenomena was used. The multi input multi output (MIMO) fuzzy logic controller receives three parameters from the model (heart rate, arterial blood pressure, and relative blood volume) as input. According to the changes in controller input values and its rule base, the outputs change so that the patient’s hemodynamic condition remains stable. The results of simulations illustrate that applying the controller can improve the stability of patient’s hemodynamic condition during hemodialysis treatment and also decreases treatment time. Furthermore with using fuzzy logic there is no need to have prior knowledge about the system under control and FLC is compatible with different patients.

In this paper, the dynamical model of the Lorenz hyperchaotic system is briefly introduced. An adaptive-sliding mode control scheme is proposed to stabilize the Lorenz hyperchaotic system in the presence of uncertainties, external disturbances, nonlinearity in the control inputs while parameters of the Lorenz system and the bounds of uncertainties and external disturbances are unknown. The mentioned control scheme is composed of two adaptive sliding surfaces and adaptation laws for unknown parameters. The Lyapunov stability theorem is used to prove the stability of sliding mode dynamics and guarantee the reaching condition. High frequency switching of control inputs is removed by substituting the sign function with a continuous sign-like function. Numerical simulations based on MATLAB software are used to verify the feasibility and effectiveness of the proposed controllers.