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In this paper, a method for distributed control of temperature distribution in a thick rectangular functionally graded plate is proposed. In this way, the linear nonhomogenous conduction which its governing dynamics is a linear partial differential equation (PDE) with spatially varying coefficients is considered and actively controlled. For this purpose, firstly, this PDE is converted into a set of ordinary differential equations (ODEs) using the modified wavenumber methodology. This apporach is based on the combination of the fast Fourier transform (FFT) and finite difference techniques. Secondly, in order to stabilize each of these ODEs, linear optimal state feedback controller is utilized by minimizing a predefined performance index. The proposed controller is modified by adding a feedforward term to have a good tracking performance for the proposed method. The designed control inputs which are in the Fourier domain, are transfers to physical domain using the inverse Fast Fourier transform (IFFT). In order to solve the linear nonhomogenous conduction heat equation, a combination of finite difference and Runge-Kutta methodologies is implemented. Simulation studies show the performance of the proposed method, for example the smaller settling time, overshoot and also steady-state error.

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Human walking is one of the most robust and adaptive locomotion mechanisms in nature, involves sophisticated interactions between neural and biomechanical levels. It has been suggested that the coordination of this process is done in a hierarchy of levels. The lower layer contains autonomous interactions between muscles and spinal cord and the higher layer (e.g. the brain cortex) interferes when needed. Inspiringly, in this study, we present a hierarchical control architecture in order to control under-actuated and high degree of freedom systems with limit cycle behavior and it is implemented for the walking control of a 3-link biped robot. In this architecture, the system is controlled by independent control units for each joint at the lower layer. In order to stabilize the system, these units are driven by a sensory feedback from the posture of the robot. A central stabilizing controller at the upper layer arises in case of failing the units to stabilize the system and take the responsibility of training the lower layer controllers. We show that using this architecture, a highly unstable system can be stabilized with identical simple controller units even though they do not have any feedback from all other units and the robot.

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Vastness of operation airspace and uncertain environment in aerial search missions, makes utilizing multiple intelligent agents more preferable to integrated centralized systems due to robustness, parallel computing structure, scalability, and cost optimality of distributed systems. Cooperative search missions require the search space to be divided properly between agents. In order to minimize the uncertainty, the agents will calculate the best path in the assigned space partition. According to the communication topology, environmental information and the near-future decisions are shared between agents. In this paper, cooperative search using multiple UAVs has been considered. First, mathematical representation of the search space, kinematic and sensor model of UAVs, and communication topology have been presented. Then, an approach has been proposed to update and share information using the Bayes’ rule. Afterwards, path planning problem has been solved using different optimization algorithms namely First-order Gradient, Conjugate Gradient, Sequential Quadratic Programming, and Interior Point Algorithm. Finally, the performance of these algorithms have been compared according to mean uncertainty reduction and target detection time.

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The main purpose of this paper is to the distributed formation tracking for fractional order multi agent systems with the leader-follower approach. First, it discusses the Lyapunov candidate function used to check the stability of the controlled system. The introduced candidate function is based on the properties of the matrix representing the desired system graph of the system. In this phase, the Lyapunov direct method is used to determine the stability of fractional order systems. Then, using sliding mode control, a decentralized controller design for tracking in fractional multi agent systems is presented in which it introduces and verifies the introduced control inputs. In the model, the input system is also considered as a disturbance type, and the control efficiency designed in turbulence mode is shown. In this section, it is shown that the controller introduced in the previous section has a desirable efficiency due to the sliding mode control. In the second section, the stability of the system, such as the first section, is investigated. at the end of this paper, several simulation examples are developed for controlling the performance of the controller.