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A parallel connection of Buck converters improves system reliability and efficiency. However, the open circuit fault, load, and supply voltage uncertainties, and interactions among the converters increase the complexity of output voltage control and balanced current sharing. Thus, in this paper, first, a decentralized backstepping sliding mode control strategy is designed to meet such challenges. However, this controller is quite conservative since the uncertainties and interaction bounds are not known. Moreover, the sliding mode based conti'ollers suffer from chattering phenomena which limits the practical applications. Therefore, a decentralized adaptive backstepping control strategy with wavelet neural network approximators is proposed. This strategy reduces the chattering and approximates the uncertainties and interactions by replacing the switcliing terms with wavelet neural networks. To show the effectiveness of the proposed controller, different numerical simulations have been performed in the presence of reference voltage changes, load, supply voltage variations, and open circuit faults. [ABSTRACT FROM AUTHOR]

Piezoelectric actuators are the most common choice for position control with ultra-high precision. Despite the significant advantages, the linear and nonlinear dynamics of these actuators, such as hysteresis, could decrease the precision of the control system. In this research, a controller based on the sliding mode method is proposed for position control of piezoelectric actuator. Sliding mode control is a model-based and useful method in nanopositioning systems. In this research, Bouc-Wen model is used for description of the actuator’s behavior. In this model, the linear dynamic is modeled with mass, stiffness and damping terms, and the hysteresis is modeled by its nonlinear dynamics. Usually, there are mismatch and uncertainty between the physical system and mathematical model. For stability analysis of the prevalent sliding mode control, the upper bound of uncertainty must be known. But, in practical systems, this is not possible, simply. On the other hand, selecting the large values for this bound, increases the controller gain and distances it from the optimum value. The proposed adaptive robust control eliminates the dependency to the upper bound of uncertainty. This is done by introducing an online adaptive law for estimating this bound. Proposing this law, asymptotic stability of the closed-loop control system is proven. Implementing the presented method on the laboratory setup and simulator software, its effectiveness is shown by simulation and experimental results. [ABSTRACT FROM AUTHOR]

This paper presents dynamic modeling, classical and nonlinear control of flight of mesicopter. First, nonlinear multiple-input multiple-output model is derived taking into consideration the body and rotor gyroscopic effects, then three classical control methods for fast response with high performance are used and compared with respect to control effort. Mesicopters are always affected by uncertainties. Classical approach is not able to properly compensate these effects. To overcome this problem, model reference adaptive control is used with three different types based on single-input single-output linear equations, multiple-input multiple-output linear equations and nonlinear multiple-input multiple-output equations. Based on the simulation results, the adaptive control method with estimation mechanism improved performance, attitude stabilization and control of system states in different conditions. Stability is guaranteed by Lyapunov stability theory. Results demonstrate good performance of adaptive control for parameter uncertainty compensation. [ABSTRACT FROM AUTHOR]

In this study, considering slippage between a robot end-effector and an object, adaptive control of a one-finger hand manipulating an object is explored. This system is a good sample to develop different techniques such as grasp analysis, grasp synthesis, stability analysis and designing different types of controller for cooperative manipulator systems. Due to the presence of inequality equations in frictional point contact modeling, a novel formulation is developed to replace the equality and inequality equations with a single second order differential equation with switching coefficients. Introducing this new friction contact model, an input-output conventional form is derived using the equality and inequality equations of motion of the system. Using this new form of motion equations, two adaptive controllers with simple update laws are proposed that both of them ensure the asymptotic convergence of the object position tracking as well as slippage control while compensating the system uncertainties. The first controller compensates the uncertain masses of the manipulator links and the object while the second one compensates the uncertain coefficients of friction. Numerical simulation is utilized to evaluate performance of the proposed controllers. [ABSTRACT FROM AUTHOR]