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Nariman Mahdavi,Mohammad Bagher Menhaj 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.1
In this paper, we consider a Hopfield like Chaotic Neural Networks which have both self-coupling and non-invertible activation functions. We show that the interactions between neurons can be used as a means of chaos generation or suppression to neuron’s outputs when more adaptability or stability is required. Furthermore, a new set of sufficient conditions based on coupling weights is proposed so that the synchronization of all neuron’s outputs with each other is guaranteed, when all neuron’s have identical activation functions. Finally, the effectiveness of the proposed approach is evaluated by performing simulations on three illustrative examples.
Structure Learning in Bayesian Networks Using Asexual Reproduction Optimization
Ali Reza Khanteymoori,Mohammad Bagher Menhaj,Mohammad Mehdi Homayounpour 한국전자통신연구원 2011 ETRI Journal Vol.33 No.1
A new structure learning approach for Bayesian networks based on asexual reproduction optimization (ARO) is proposed in this paper. ARO can be considered an evolutionary-based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter, the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem: This leads to the fitter individual. The convergence measure of ARO is analyzed. The proposed method is applied to real-world and benchmark applications, while its effectiveness is demonstrated through computer simulations. Results of simulations show that ARO outperforms genetic algorithm (GA) because ARO results in a good structure and fast convergence rate in comparison with GA.
Davood Allahverdy,Ahmad Fakharian,Mohammad Bagher Menhaj 대한전기학회 2019 Journal of Electrical Engineering & Technology Vol.14 No.6
In this study, back-stepping integral sliding mode control (BISMC) with iterative learning control (ILC) algorithm are presented for nonlinear translational and rotational dynamics of the Quadrotor UAVs. The proposed controller (BISMC) can track desired trajectories and (ILC) is responsible for inclining the accuracy and robustness of the control strategy. In order to prove the stability of the closed loop system, Lyapunov theorem is used. The simulation results indicate that the proposed control strategy has high accuracy, suitable robustness, disturbance rejection, good trajectory tracking and fast transient responses for the Quadrotor UAVs despite the uncertainties and external disturbances.
Ali Ghasemi,Javad Askari,Mohammad Bagher Menhaj 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.2
In this paper, under the complex-weighted directed communication topology, the problem of distributedfault tolerant control (FTC) for a class of second-order multi-agent systems (MAS) in the presence of actuator faultsis studied. The faults can simultaneously occur in more than one agent. First, a real representation of the secondorderdynamic agent with the complex weighted graph is proposed. Second, based on the proposed representation,distributed finite-time convergent observer is proposed for each agent to estimate the state and fault in a finite time. Then, using the fault information obtained online, an adaptive FTC protocol is proposed to compensate for thefailure effects and to enable all the agents to achieve the control goal. Also, we show that the closed-loop systemcan be guaranteed to be asymptotically stable in the presence of faults. Finally, an illustration example is given todemonstrate the effectiveness of the proposed scheme.
3D Trajectory Tracking Control for a Thrust-Propelled Vehicle with Time-varying Disturbances
Meisam Kabiri,Hajar Atrianfar,Mohammad Bagher Menhaj 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.8
This paper discusses trajectory tracking for a class of under-actuated thrust-propelled vehicle in thepresence of two time-varying disturbances. A saturated estimator based on equivalent output injection slidingmode disturbance observer is employed to accommodate for the adverse effect of the translational disturbance. Tohandle the rotational disturbance, we make use of a sliding mode controller. The stability of the overall systemis investigated by means of Lyapunov function theory. A numerical simulation is included in the paper to showeffectiveness of the proposed control scheme.
Robust Adaptive Dynamic Surface Control of Nonlinear Time-varying Systems in Strict-feedback Form
Mojgan Elmi,Heidar Ali Talebi,Mohammad Bagher Menhaj 제어·로봇·시스템학회 2019 International Journal of Control, Automation, and Vol.17 No.6
In this paper, the problem of robust adaptive control for nonlinear systems with unknown time-varying parameters and disturbance is considered. For this purpose, an indirect adaptive controller based on the Dynamic Surface Control (DSC) is proposed where an adaptive scheme is presented to provide estimations of unknown time varying parameters. First, the parameters are approximated in terms of polynomials with unknown coefficients using the Taylor series expansion. Then, these unknown coefficients are estimated using a novel adaptive law. It is shown that the proposed control scheme guarantees the stability of the overall system and the tracking error can converge to a desired small residual. Finally, simulation results are given to demonstrate the effectiveness of the proposed method.