Electrical and computer engineering

A path planning method for mobile robots based on two dimensional cellular automata is proposed. The method can be applied for environments with both concave and convex obstacles. It is also appropriate for multi-robot problems as well as dynamic environments. In order to develop the planning method, environment of the robot is decomposed to a rectangular grid and the automata

Selection of dynamic dividers in CMOS PLLs for GHzs applications allows remarkable reduction in power loss without affecting phase noise and power supply sensitivity. Frequency dividers are combination of classic TSPC logic (true-single-phase-clock) and E_TSPC logic (extended TSPC). The designed PLL with % 8/9 prescaler is used for wireless LAN applications and synthetic of frequencies between 5.14 to 5.70 GHz. In this paper a % 8/9 prescaler has designed at 0.25 micrometers process for 2.5_3 GHz band width. This prescaler has been designed with 2.5v power supply with using E_TSPC logic. In this circuit in addition to decrement of power consumption, divider can work in a nearly high speed. Subsequently the dimensions of transistors have been improved and power consumption has been reduced from 3.8mw to 2.9mw. Then, the layout of circuit has been designed with L-Edit software. The simulation results of are identical to that we expect according to earlier Spice simulations.

A learning mechanism based on Powell's optimization algorithm is proposed to optimize walking behavior of a passivity based biped robot. To this end, a passivity-based biped robot has been simulated in MSC ADAMS and a control policy inspired from humanoid walking is adopted for a stable walking of the robot. Linear controllers try to control the joints of robot in each walking phase to implement the gait proposed by the control policy. Learning is employed using Powell's optimization algorithm to adjust the control parameters so that the robot enters to an optimum limit cycle in a finite time. The fitness function is defined to evaluate the robot's optimum behavior. The results are verified by simulations in SIMULINK+ADAMS.

In this paper an optimal PID controller is proposed. To adjust the parameters of the controller a fitness function in terms of transient, steady state parts of response and control energy characteristics of system is introduced. A genetic algorithm is employed to minimize the fitness function to achieve a satisfactory response for system as well as minimizing energy. The results are verified by some simulations.

A low power and high speed 8/9 CMOS programmable dynamic frequency divider has been designed. It contains a control bit by which can obtain 1/9 and 1/8 input frequency in output. In spite of the variations in size and structure of circuit, the 53% improvement in power dissipation has been achieved. Power dissipation about 1.6 mw in a 2.78 GHz Frequency Rate, 2.5 volt power supply circuit is verified by HSPISE simulation.

A Honey Bee Mating Optimization (HBMO) technique is proposed for the optimal tuning of the Power System Stabilizer (PSS) in this paper. The design problem of robustly selecting PSS parameters is formulated as an optimization problem according to the time domain-based objective function which is solved by the HBMO technique that has a strong ability to find the most optimistic results. To achieve desired level of robust performance and improve power system low frequency oscillations damping, The design process takes a wide range of operating conditions. The effectiveness of the proposed HBMO based PSS is demonstrated on a Single-Machine Infinite-Bus (SMIB) power system through the nonlinear time domain simulation and some performance indices under different operating conditions in comparison with the genetic algorithm based tuned stabilizer and conventional PSS. Results evaluation show that the designed HBMO based PSS has an excellent capability in damping power system low frequency oscillations and enhance greatly the dynamic stability of the power systems.

Dynamic manipulation of polygonal objects by an array of one degree of freedom arms is studied from kinematics and planning points of view. In the studied manipulation method, an object is manipulated to its goal configuration by a sequence of juggles. A kinematic model of an object throwing task is driven and a method for object manipulation by a sequence of throws is proposed. The method, called Backward Throws Method (BTM), is based on throwing an object backward towards the arm pivot. Based on the developed model, a planning algorithm is proposed for BTM. In addition, the only existing similar method to BTM, which is based on forward throws-named FTM in this paper-is reformulated for implementation by a series of arms and compared with the proposed method. Analytical investigations, simulation results, and experimental outcomes show that BTM meets the desired requirements. Moreover, in comparison to FTM, BTM requires fewer number of throws and lower release velocity. In addition, the object's maximum height of flight is much lower in BTM which results in lower catching impact. According to the experimental results, although the proposed method has no feedback from object position, accumulated position error is very small. This fact is directly related to the attained decrease in catching impact which causes small object slippage and rebound on catching. Furthermore, there is no restriction on the arm geometry in BTM while in FTM an arm with negative offset is needed.

In this paper a new method for placement of DG (distributed generation) units in distribution networks has been presented. This method is based on two factors: analysis of power flow continuation and determination of the most sensitive voltage buses to collapse voltage. This method has been executed on a typical 34-Bus test system. Efficiency of proposed method in improvement of voltage profile and reduction of power losses is verified by analytical and simulation results. Also the method may cause to increase of capacity saving, maximum loadability voltage stability margin.

A learning mechanism based on Powell's optimization algorithm is proposed to optimize walking behavior of a passivity based biped robot. To this end, a passivity-based biped robot has been simulated in MSC ADAMS and a control policy inspired from humanoid walking is adopted for a stable walking of the robot. Linear controllers try to control the joints of robot in each walking phase to implement the gait proposed by the control policy. Learning is employed using Powell's optimization algorithm to adjust the control parameters so that the robot enters to an optimum limit cycle in a finite time. The fitness function is defined to evaluate the robot's optimum behavior. The results are verified by simulations in SIMULINK+ADAMS.

Because of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.

Anthelmintic resistance is an important problem in most sheep-producing countries of the world. Studies in this field are performed by clinical tests. Identification of anthelmintic resistant nematodes without clinical test can help farmers to save money and time; on the other hand it can help them to avoid inefficient treatment and probable outcomes. In this study a multilayered neural network has been proposed to detect anthelmintics resistance nematodes in sheep flocks.

The genus Trichoderma acts as an important antagonist against phytopathogenic fungi. This paper proposes a software-based identification tool for recognition of different species of Trichoderma. The method uses the morphological features for identification. Morphological-based species recognition is common method for identifying fungi, but regarding the similarity of morphological features among different species, their manual identification is difficult, time-consuming and may bring about faulty results. In this paper it is intended to identify different species of Trichoderma by means of neural network. For this purpose, 14 characteristics are used including 5 macroscopic and 9 microscopic characteristics. After quantifying qualitative features and training a multilayer perceptron neural network with quantified data, 25 species of Trichoderma are recognized by using the network. Totally, identification of Trichoderma species as one useful fungus is achieved by using the trained network.

Original scientific paper Object manipulation is a basic task in robotics and automation. Active manipulation by grasp is conventional approach in object manipulation. However, in many cases, grasp-less manipulation can be beneficial in terms of cost, minimalism and extension of workspace. On the other hand passive mechanisms are advantageous from the energy saving viewpoint. In this paper we combine these ideas to develop a dynamic passive object manipulation mechanism to achieve manipulation in more than one dimension and simultaneously change position and orientation of the object. In developed mechanism the manipulation platform is a simple inclined surface. The object is composed of two wheels with different radiuses and an axle connecting the wheels to each other. The object moves passively along a circular path on the platform. Kinematic equations of the motion are devised, dynamic analyses are performed and no-slippage conditions are extracted. Modelling in CATIA and simulations in MSC.ADAMS are performed and experimental set up is built to verify the analysis.

Distributed planning and decision making can be beneficial from the robustness, adaptability and fault tolerance in multi-robot systems. Distributed mechanisms have not been employed in three dimensional transportation systems namely aerial and underwater environments. This paper presents a distributed cooperation mechanism on multi robot transportation problem in three dimensional environments. The cooperation mechanism is based on artificial capital market, a newly introduced market based negotiation protocol. In the proposed mechanism contributing in transportation task is defined as asset. Each robot is considered as an investor who decides if he is going to invest on some assets. The decision is made based on environmental constraint including fuel limitation and distances those are modeled as capital and cost. Simulations show effectiveness of the algorithm in terms of robustness, speed and adaptability.

Original scientific paper The process of empowering muscles in order to make them to a normal and common value is an expensive and prolonged work, in common available methods. There are some commercial exercise machines used for this purpose called rehabilitation systems. However, due to their insufficient motion freedom and prospect of being expensive, these machines have limited usage. Hence, it is clearly necessary that Mechatronic technologies should be used in this area. In this paper, an algorithm and an improved rule are presented for controlling a rehabilitation system of lower limbs which is implemented on a 6-Degree Of Freedom (DOF) Stewart parallel robot. Impedance control and adaptive control are used for this purpose. Estimation and optimization of control parameters will be done by artificial neural networks and genetic algorithms, respectively (intelligent strategy). Safety is guaranteed since some of controller parameters can be adapted under the stability conditions given by using Routh stability theory. Thereafter, the results of simulations are presented by defining a physiotherapy standard mode on a desired trajectory. MATLAB/SIMULINK is used for simulations. Finally, a comparative discussion between this strategy and common methods is devised.

In this paper we are interested to multi-agent foraging, where a team of agents search environment until they find some interested objects and return to nest. Apart from existing models for foraging, we consider a multi-agent system that the agents are restricted with fuel consumption. Additionally, interested objects in environments are in motion all the time. Then, the foraging problem is constrained with complex conditions of agents' and the environment's requirements. A Contract-Net model is proposed to solve this foraging considering all the constraints related with fuel consumption as well as dynamic environment conditions. Contract-Net is a well-known negotiation protocol where each agent (or node in the agents net) can be in role of a manager or contractor. Efficiency of the proposed model is investigated by some simulation experiments. Bu çalışmada biz çoklu etmen (yiyecek) arama sistemi ile ilgileniyoruz, ki bir ekip etmen çevrede bazı ilgi çeken nesneleri bulup yuva götürmeye kadar arama yapıyor. Arama için mevcut modellerin dışında, biz birçok etmen sistemi içinde etmenler yakıt tüketimi ile sınırlı olması durumu değerlendirmeyi göz önüne aldık. İlaveten, ilgi çeken nesneleri her zaman harket halinde. Bu durumda, arama sorunu etmenlere dayalı karmaşık koşullar ve çevre şartları ile sınırlanmıştır. Arama sorununu çözmek için bir Sözleşme-Ağ modeli yakıt tüketimi yanı sıra dinamik çevre koşulları ile ilgili tüm kısıtları göz önüne alarak önerilmiştir. Sözleşme-Ağ bir iyi tanınmış müzakere protokolüdür ki her etmenin (veya etmenler ağı içerisinde her düğümün) bir yönetici veya üstlenici rolü olabilir. Önerilen modelin verimliliği bazı simülasyon deneyleri ile incelenmiştir.

Multi-agent systems have origin in computer engineering however, they have found applications in different field. One of the newly emerged problems in multi-agent systems is multi-agent control. In multi-agent control it is desired that the control is done in distributed manner. That is the controller of each agent should be implemented based on local feedback. In this a mechanism is introuded as a test bed for multi-agent control systems. The introduced mechanism is balancing of a ball on link located on a planar mobile robot. Dynamic equations of the mechanism is derived and the control task is distributed among two agents. For each agent a two loop controller designed wherein external loop is a LQR controller and inner loop is a simple proportional controller. Regulation and fault tolerance performance of controller scheme is evaluated by simulations.