In systems with hysteresis behavior like Shape Memory Alloy (SMA) actuators and Piezo actuators, an accurate modeling of hysteresis behavior either for performance evaluation and identification or controller design is essentially needed. One of the most interesting hysteresis none-linearity identification methods is Preisach model which the hysteresis is modeled by linear combination of hysteresis operators. In spite of good ability of the Preisach model to extract the main features of system with hysteresis behavior, due to its numerical nature, it is not convenient to use in real time control applications. In this paper a novel artificial neural network (ANN) approach based on the Preisach model is presented which provides accurate hysteresis none-linearity modeling. It is shown that the proposed approach can represent hysteresis behavior more accurately in compare with the classical Preisach model and can be used for many applications such as hysteresis non-linearity control, hysteresis identification and realization for performance evaluation in some physical systems such as magnetic and SMA materials. It is also greatly decrease the extremely large amount of calculation needed to numerically implement the Preisach hysteresis model. For evaluation of the proposed approach an experimental apparatus consists of one-dimensional flexible aluminum beam actuated with a SMA wire is used. It is shown that the proposed ANN based Preisach model can identify hysteresis none-linearity more accurately than the classical Preisach model besides to its reduction in the simulation and computation time.

There are two ways of using SMAs as actuators for shape control of flexible structures; they can be either embedded within composite laminates or externally attached to the structures. Since the actuator can be placed at different offset distances from the beam, external actuators produce more bending moment and, consequently, more shape change. Such a configuration also allows introduction of fast convection cooling, very important in shape control applications that require a high-frequency response of SMA actuators. Although combination and modeling of externally-attached SMA actuator wires and strips have been widely considered by some researchers, these studies have some weaknesses that neglecting them would yield theoretically and experimentally erroneous results. In this work, the aforementioned limitations of attaching actuators to the smart structures have been removed and the modeling of a large deflection flexible beam actuated by two active SMA actuators is carried out. The Brinson constitutive equations for SMA materials are coupled with the nonlinear beam behavior and the coupled system of equations is numerically solved for some particular cases. The analysis method done in this paper can be easily extended to the complicated smart structures with externally-attached SMA wires.

The main contribution of this paper is to introduce a novel non-Lipschitz protocol that guarantees consensus in finite-time domain. Its convergence in networks with both unidirectional and bidirectional links is investigated via Lyapunov Theorem approach. It is also proved that final agreement value is equal to average of agents’ states for the bidirectional communication case. In addition effects of communication time-delay on stability are assessed and two other continuous Lipschitz protocols are also analyzed.

The deployment of multi-agent systems in presence of obstacle deals with autonomous motion of agents toward a specified target by sensing each other and boundaries of obstacles. In this paper, asynchronous, scalable, distributed algorithm is used to deploy agents. Boundaries of obstacles are modeled by virtual agents. Algorithm was implemented by solving continuous n-median problem called generalized Fermat-Weber problem. It is shown that deployment is performed when position of real agents are the geometric median of their Voronoi cells. Simulation results show the validity of the proposed algorithm very well.

In this paper, on the basis of a robust algorithm for the analysis of the 6 DOF motion of an underwater vehicle in calm water, after presenting the dynamics model and simulating motion, the model is put in the closed loop control to perform a controlled mission. The mission is defined as to navigate the submarine toward a desired point in the vertical plane. In performing the mission, the least time and of course the least position error with respect to the target point is aimed. The designed controller based on fuzzy logic and thus adapted to the human patterns for navigation, with a simple structure, performs the mission accurately. The intelligent structure of the fuzzy controller, results in a spectacular capability in target finding; such that by the increase of mission duration, the submarine, which never completely stops in this modeling, reaches the target point multiple times. Several simulations of the controlled motion, changing the coordinates of target point, proved the controller effectiveness.

Wall walking robots are designed for different purposes, rescue operations, wall inspections and jobs such as painting and cleaning and fire fighting for tall buildings. These are some cases that these types of robots are extensively used. This paper describes a design of a new serial mechanism for wall climbing job. In deed we are seeking to define a minimum degree of freedom mechanism to be applied in a robot moving vertically on a surface. This mechanism has 5 links, but at any point it works with its 4 links, actually in each cycle of motion the linkage will be interchanged.

In this paper the combined optimal feedback-adaptive feedforward controller proposed to attain better performance of active vibration suppression of flexible structures subjected to different type of disturbances. The structure considered here is a cantilever beam actuated with a PZT patch actuator. The proposed controller consists of two individual parts, a filtered-x controller as a feedforward part and an optimal linear controller as a feedback part. Recursive Least Square algorithm (RLS) is used for the adaptive filtering scheme in Filtered-x adaptive feedforward controller. LQG optimal controller is also used in the feedback part of the controller. This research investigates the effectiveness of the proposed controller in comparison with other types of applied controllers. In this regard, the simulation study is performed on a finite element model to evaluate the performance of the proposed controller under different disturbances. It has been shown that this method can reduce the vibration caused by random disturbances due to its broad-band disturbance rejecting performance. Also, it can fully suppress the vibration caused by a harmonic disturbance in a small decay time because of its narrow-band disturbance rejecting performance with the fast parameter adaptation algorithm (RLS).