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Aims The complexity of today`s urban issues are such that researchers and urban designers can not manage to to focus on all topics simultaneously and explain the consequences of their decisions and their designs in urban spaces. Space syntax logic, which is one of the mechanisms that can help in overcoming these types of problems, uses software that has high accuracy in mathematical calculations and presentation of graphic maps. The purpose of this research is to investigate the qualities of the spatial dimension and the experience of pedestrians in Resalat Square, Tehran.

Methodes in this study, while using DepthMap software due to observations and interviews with residents, retailers and pedestrians and observing the problems of citizens' access to different parts of the square, the technical weaknesses of software related to space syntax logic were identified and the strengths and weaknesses were achieved through SWOT technique.

Findings After reviewing the preliminary results and observing the methodological contradictions, the field survey was renewed inorder to reveal the additional requirements. The results can be considered in two aspects. Firstly, raising additional awareness to refine space syntax logic, mathematical cognition, and DepthMap software, and secondly, achieving comprehensive cognition of Resalat Square in spatial structure.

Conclusion The human experience of the city can be different from the quantitative results obtained. The final results indicate that the south and southwest areas of Resalat Square have the best state of integration and connection with other urban spaces and consequently have the greatest potential for development.
 

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Parallel manipulators are mechanisms with closed kinematic chains which have been developed in different forms, but these manipulators have several drawbacks such as small workspace, existence of singular points in their workspace, and complex kinematics and dynamics equations that lead to increase of difficulty in their control. In spite of this, this mechanism has been being conventionally used in many different industrial applications such as machining, motion simulators, medical robots, etc. To overcome these drawbacks, design and manufacturing of a manipulator with three translational degrees of freedom are provided. Design of this manipulator was based on the possibility of three translational motions for its end-effector. The manipulator degrees of freedom are obtained via screw theory. Basic features, consisting of forward and inverse kinematics, workspace and singularity analyzes and also velocity analysis, are considered in this paper. A numerical algorithm is implemented to determine the workspace regarding applied joint limitations and the design parameters were extracted based on to achieving to the desired workspace. The robot motion is created by using of pneumatic actuators which receive their command from a pneumatic servo valve. After design steps, the required elements were provided and assembled in a robotic lab. Finally, the simulation results have transparently approved the improved robots.

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This paper presents the control of a quadrotor using nonlinear approaches based on the experimentally measured sensors data. The main goal is the control and closed loop simulation of a quadrotor using feedback linearization and sliding mode algorithms. First, a nonlinear model of quadrotor is derived using Newton-Euler equations. To have a more realistic simulation the sensors noise performance were measured using a setup. sensors data was measured under on engines. Since the experimental data for sensor had error and noise, a Kalman filter was used to reduce sensors noise effect. Results demonstrate good performance for Kalman filter and controllers. Results showed that feedback linearization and sliding mode controllers performance was good but angles changes were smoother on feedback linearization controller. With increasing uncertainty, feedback linearization performance was away desired mode from this aspect The time to reach the goal situation while increasing uncertainty was no significant impact on the performance of sliding mode controller.Thus feedback linearization controller added PID is Appropriate to Maintain the quadrotor attitude while sliding mode controller has better performance to angles change and transient situations.

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In this paper, constraint equations are derived based on the kinematic model of the robot and Lagrange method is applied to derive the dynamic equations. In order to control the robot position on planned reference trajectories, in presence of uncertainties of the dynamic model, an adaptive robust controller with uncertainty estimator is designed which is robust against the uncertainties and induced noises. The proposed controller consists of an approximately known inverse dynamics model output as model-based part of the controller, an estimated uncertainty term to compensate for the un-modeled dynamics, external disturbances, and time-varying parameters, and also a decentralized PID controller as a feedback part to enhance closed-loop stability and account for the estimation error of uncertainties. Performance of the designed controller is simulated and evaluated in different conditions including the presence of noise and parameters variation. In this regard, a comparison has been made between the response of the proposed adaptive robust controller and response of a feedback linearization controller, indicating their capabilities in noise rejection and compensation of parameters variation. Also, the results show that the proposed sliding mode controller has a desirable performance in tracking the reference trajectories in presence of the model uncertainties and noises for this kind of parallel mechanism.

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In this paper, dynamic modeling and control of a three-degrees-of-freedom parallel robot with pure translational motion is performed. Constraint equations are derived based on the kinematic model of the robot and Lagrange method is applied to derive the dynamic equations. In order to control the robot position on planned reference trajectories, in presence of uncertainties of the dynamic model, a sliding mode controller is designed which is robust against the uncertainties and induced noises. Performance of the designed controller is simulated and evaluated in different conditions including the presence of noise and parameters variation. In this regard, a comparison has been made between the response of the proposed sliding mode controller and response of a feedback linearization controller, indicating their capabilities in noise rejection and compensation of parameters variation. Also, the effect of defining different sliding surfaces on the performance of the sliding mode controller, and using the integral of error instead of the error itself, have been studied and examined. Results show that the proposed sliding mode controller has a desirable performance in tracking the reference trajectories in presence of the model uncertainties and noise for this kind of parallel mechanism.

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In this paper, design of an adaptive controller, as a combination of feedback linearization technique and Lyapunov stability theory, is presented for a parallel robot. Considering a three degree-of-freedom parallel mechanism of the robot, which serves pure translational motion for its end-effector, kinematic and constraint equations are derived. Then the dynamic model of the constrained system is extracted via Lagrange’s method to be used in the robot control. Two optimized trajectories are designed for the end-effector in the presence of some obstacles using harmony search algorithm to be tracked by the robot. An objective function is defined based on achieving to the shortest path and also avoiding collisions to the obstacles keeping a marginal distance from each. The first trajectory is a 2D path with four circular obstacles and the second is a 3D path with three spherical obstacles. Performance of the designed controller is simulated and studied in conditions including external disturbances and varying system parameters. The results show that the proposed adaptive controller has a suitable performance in control of the end-effector to track the designed trajectories in spite of external disturbances and also uncertainty and variation of the model parameters.

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In this paper, dynamic modeling and position control of a nonlinear servo – hydraulic actuator system under variable loads is proposed. In dynamic model of the under studied system, governing equation of valve, leakage and friction is considered. To achieve to the desired performance of the system under variable loads with extend variation amplitude, a one control method is applied which is robust in the presence of the variation. Also, as a nonlinear servo hydraulic actuator system has a nonlinear dynamics and the extracted dynamic model is not accurate to proposed behavior of the system, one controller can be required which is robust against the nonlinearity and uncertainty effects. The controller should be having an appropriate response, more accuracy and stability. Regarding to position control of the nonlinear servo hydraulic actuator system in presence of variable loads, nonlinear controllers are designed using feedback linearization and sliding mode techniques. In addition, in order to show the robustness of proposed controllers, a time varying disturbance and noise are applied in the simulation and results of the simulation are compared with classical PID controller. Controller parameters is optimized using harmony search algorithm and simulation results show the outperforming of sliding mode control in spite of variable loads against feedback linearization technique and PID controllers.

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In this paper, an optimal adaptive sliding mode controller of an Omni-Directional Mobile Robot (ODMR) is proposed using harmony search algorithm. First, kinematic model of the robot is derived and then, governing equations of dynamic model have been obtained using linear and angular momentum equilibrium. Since the derived model is not an exact definition of the system, it includes some uncertainties. To compensate them, a tracking control method has been offered. The proposed controller consists of an approximately known inverse dynamic model output as the model-based part of the controller, an estimated uncertainty term to compensate for the un-modeled dynamics, external disturbances, and time-varying parameters to enhance closed-loop stability and account for the estimation error of the uncertainties. In order to compare the results of the proposed controller, an optimal feedback linearization and sliding mode controllers are designed and then, a cost function has been defined by combining the variation rate of control signal and the integral error index. This cost function has been minimized using harmony search algorithm, resulting in optimum control parameters. Finally, the performance of the designed controller in different conditions, such as in presence of disturbance and system parameter variation has been simulated and discussed.

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Container crane is an under-actuated system, which is why it is much more difficult to control such systems. In this paper, partial feedback linearization and sliding mode controllers are employed to control a 2D container crane with varying cable length. Since, the dynamic model of the system cannot present the real one and the system contains some uncertainties, a controller is designed to reduce the effect of model uncertainties and external disturbances. Since the considered system is under-actuated, in order to design controller, first, dynamics of the system is divided into two parts, actuated and under-actuated. Then, stability of the controllers is discussed. An objective function is considered as the combination of integral of absolute error and rate of variation of control signal. The introduced objective function is minimized employing Harmony Search and particle swarm optimization algorithms and optimum values for parameters of the designed controllers are determined to make it possible to compare performance of the mentioned controllers in their optimum conditions. Simulation results show suitable performance of the designed controllers by harmony search algorithm for the 2D crane in the presence of mass uncertainty, actuator disturbances and sensor noises.

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In this paper, an optimal robust hybrid active force controller based on Harmony Search Algorithm is designed for a lower limb exoskeleton robot. Dynamic equations are derived using Lagrange method by considering three actuators on the hip, knee and ankle joints to track a specific trajectory. One of the major problems of exoskeleton robots is non-synchronization of movements and transfer of power between the robot and human body which affects the robot in form of disturbance. In order to mitigate the effect of disturbances and increase precision, combination of active force control (Corrective loop of control input) with position control is used as an effective and robust method. In the active force control, to elicit robust input control against disturbances, the moment of inertia of the links is estimated at each instant by minimizing the Criteria of ITAE and the control input rate, using the Harmony Search algorithm and the control input is modified. Also, two controllers are designed for the position control loop using sliding mode and feedback linearization methods. In order to validate the performance of the designed controllers, the robot is modeled in ADAMS and control inputs are applied to the Adams model. For appropriate comparison, all control parameters are optimized using the harmony search algorithm and then performance of position controllers are compared in hybrid and conventional (without the force control loop). Results indicate the outperforming of the hybrid sliding mode controller rather than to the other designed controllers.

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In this paper, an optimal robust nonlinear model predictive controller based on harmony search algorithm is designed for a type of 3-DOF translational parallel robot. Dynamic model of the mechanism is derived using Lagrange method and the model predictive controller augmented by uncertainty estimator is designed and stability is proved by Lyapanov theorem. Performance of the designed controller is evaluated in different conditions such as presence of disturbance and parameter variation. Furthermore, an optimal trajectory consisting four circular obstacles is designed as the reference trajectory of the robot. In order to obtain the optimum control parameters, a cost function combining control signal rate and error is considered and minimized by harmony search algorithm. In order to compare the performance of the designed controller with other nonlinear controllers, two controllers, an optimal sliding mode and a feedback linearization controller are also designed and their results are compared. Simulation results depict the desirable performance of the three controllers in spite of disturbance and model uncertainty, however, error criteria indicate priority of the robust nonlinear model predictive controller over the two other controllers.

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The flavonoid and phenolic compounds are among the main pharmaceutical components of medicinal plants. These compounds are considered as effective anti-oxidant sources. Five cyanobacterial extracts were used to stimulate the plant growth and increase production of specific secondary metabolites in Plantago major as a medicinal plant. These cyanobacteria were isolated from the growth bed of the plant in its natural habitats. Nitrate-free BG11 medium was used for preparing axenic monoalgal cultures. Pot experiments were performed by spraying cyanobacterial extracts on the soil of treated plants every 20 days from the time of planting. Growth of plants was evaluated by measuring growth parameters such as plant height, root length, dry and fresh weight of plant, leaf number, leaf area, as well as inflorescence characteristics 60 days after planting. In addition to growth factors, the total amount of phenol and flavonoid of plants was also assessed. Statistical analysis showed that there was a significant difference in the vegetative and reproductive characteristics compared to the control plants. Also, the methanolic extraction of treated and control plants displayed the highest total phenolic and flavonoid content 77.23±3.21 µg of GA mg^-1 and 389.67±34.43 µg of RU mg^-1 in plants treated with Cylindrospermum michailovskoence. Based on the obtained results, cyanobacterial fertilizers are suggested as the biological elicitors to improve the quantity and quality of medicinal plants products. As a result of this study, chemical content of cyanobacterial extracts and the production of plant growth stimulating substances such as phytohormones can be proposed as factors affecting plant growth parameters and metabolites production.
 

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In this paper, a finite-time fault tolerant controller based on sliding mode algorithm, as a robust control method, is presented to control the attitude stabilization of the quadrotor system in the presence of actuator fault and uncertainty. The controller is designed based on the nonlinear model of a quadrotor and its stability analysis is performed according to the Lyapunov stability theorem. Also, regarding some weaknesses of MEMS sensors such as partly high noise and bias error, an extended Kalman filter is designed and implemented in order to merge sensors data and reduce the noise effect on the outputs. To validate the controller performance, the experimental tests is implemented on a full-scale quadrotor in real-time. The evaluation of the designed strategy is carried out in different scenarios, no fault in the actuators and a partial loss of effectiveness of an actuator as well as uncertainty in the quadrotor parameters. The experimental results reveal the superiority of the sliding mode tolerant strategy over feedback linearization in the presence of various faults and uncertainty effects.