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Research subject: It is not an easy task to get a suitable model of polymerization due to complex mechanism and kinetic of such processes. Polymerization temperature, as an intermediate variable between determining final polymer properties, is a good selection to be controlled. Fuzzy logic has ability to be applied to processes with unknown or less informed dynamics.
Research approach: In this research, control of semi batch poly(ethylene terephthalate) reactor temperature was studied. To do so, error and error variation were calculated using measured reactor temperature. Error and error variation were fuzzified using triangular membership functions. Five and three fuzzy sets were introduced to fuzzify error and error variation, respectively. Hence, fifteen rules were defined. Five fuzzy sets were defined to quantify these fifteen rules. Weight average defuzzification method was applied to calculate necessary heat to the reactor. Poly(ethylene terephthalate) was synthesized in a semi batch reactor based on a two steps method. It is possible to monitor temperature, pressure, rotation speed and mixing torque in this set up.
Main results: Produced water during esterification determines reaction advancement. In polycondensation step, mixing torque determines end of the process. Linguistic based fuzzy rules were applied to both steps. Reference temperatures were 230^oC and 260^oC, respectively. Reactor temperature was controlled with 1-2^oC precision. Control logic was applied using C#.net real time programming.

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This paper presents a fuzzy search controller approach along with the look-up tables, to optimize the efficiency of a pump-induction motor drive. The induction motor and the converter are modeled based on thermal loss; and for modeling the pump and the hydraulic system, which are non-linear and relatively complicated, the neural network is used. In the designed system, in order to optimize the efficiency of the pump and the hydraulic system, the amount of outflow is controlled by adjusting the pump’s rotating speed. Meanwhile by choosing the suitable switching frequency of the inverter and feeding the motor by proper amount of voltage and frequency, the loss amount of the drive system is minimized. Simulation results show that the proposed controller improving the efficiency of the drive system under flow-changing conditions, as well as it has improved the problems that existed in some of the classical efficiency optimization approaches, such as the slowness of the converging, and the oscillation around the optimal point.

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This paper proposes a new method of gain scheduling control design for a nonlinear system which is described as linear parameter varying form. A performance measure based on Linear Matrix Inequality is introduced. To consider stability and performance measures in design process, the H∞ loop-shaping method is used to design the local controllers, which can be described as state feedback observer based structure. By introducing the stability and performance covering condition for the linear parameter varying system, a new interpolation law is proposed, and it is proofed that the resultant controller can preserve the performance measure for the observer based structure for all values of the scheduling parameter. Also the closed loop stability is guaranteed. The method is successfully applied on the control of a well-known benchmark system, namely, the autopilot for a pitch-axis model of an air vehicle. The performance and effectiveness is evaluated against disturbances and parameter uncertainties using computer simulation.

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 to enhance the closed loop performance in presence of disturbance, uncertainties and delay a double loop mixture of MPC and robust controller is proposed. This double loop controller ensures smooth tracking for a 3-axis gyro-stabilized platform which has delay intrinsically. This control idea is suggested to eliminate high frequency disturbances and minimize steady state error with minimum power consumption in simulation and experiment. Proposed controller based on the combination of ℋ₂ and ℋ_∞ controllers in the inner control loop shows the robustness of the proposed methodology. In the outer loop to have a good tracking performance, an integrated MPC is used to handle delay in system dynamics. Also, the main idea for dealing with uncertainties is using integral and derivative of platform attitude. In the proposed platform, the ℋ_∞ controller is compared with ℋ_∞/ℋ₂ controller in KNTU laboratory in theory and experiment. Results of experimental set up shows the same reaction of two controllers against disturbance and uncertainties in delayed system.

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Microgrids are small-scale, low voltage (LV) power networks which employ renewable distribution energy resources (DERs) with power electronic interfaces (PEIs). Microgrids as single controlled units and active distribution networks require flexible control systems to ensure reliable and secure operation in different modes. These various operations of microgrid cause variations in voltage and frequency especially in island mode. In this paper, a new control method with two optimization algorithms (genetic algorithm (GA) & imperialist competitive algorithm (ICA)) are proposed to eliminate both voltage and frequency disturbances. Also, a new concept of conventional droop control in format of fast droop controller (FDC) is designed to guaranty the microgrid system reliability with cooperation of a modern frequency controller. Simulation results show the truth behavior of proposed approach in comparison with previous methods

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One of the important problems in seismic rehabilitation studies of existing structures is opportune decision making about ending or continuance of various stages rehabilitation in order to save time and cost. About that we can use decision maker systems to solve this problem and to give more rational assessment about that problem. This paper presents a procedure based on Fuzzy Logic that classifies structures into qualitative seismic hazard categories. The purpose of this study is to get a model that can speed existing structures seismic rehabilitation primary studies and also to prompt decision making about continuance of study process. In order to account real world data, in addition to expert’s knowledge, groups of school seismic rehabilitation data of different cities of Iran have been used for modeling. In order to reduce the input space and increase generalization ability of the system, a feature selection method has been applied to the data. Among available parameters of data, significant parameters have been selected by Decision Tree Learning method. Then, Fuzzy Membership Functions corresponding to these parameters have been defined. Appropriate defining of these functions, we can insinuate factors such as uncertainty on that parameter in computations also. Afterwards, the Fuzzy System has been designed by conditional regulations. It is worth to say that these regulations are optimizedcompletely. In order to ease the process of risk assessment based on this model, software named “Rapid Seismic Risk Evaluation” (RSRE) has been developed. Thus, we have a model that by inputting 7 entrance parameters of a structure (both structural and geotechnical parameters corresponding to existing structure), generates its seismic risk level. The proposed procedure has advantages among the rest we can recount the possibility of modeling uncertainties, inputting structural information qualitative and high speed of risk analysis process. It is clear that using Fuzzy Logic not only lead to more simple formation, but also speed the rate of risk analysis process intensely, that this case is one of the most important advantages of the proposed method. In order to scrutiny of the designed model, various controls have been done. These controls have been tested on different data. Outcome results are representative high accuracy of designed model. Finally, in order to survey the efficiency of proposed procedure, the designed model has been applied to some of Tehran and its suburb school structures and outcome results have been compared with main data real results. Outcome results are representative good efficiency of the method. We should notice that using Fuzzy Concluder Systems lead to speed structure risk analysis and so decision making about various stages of structure rehabilitation is performed with more rate than previous. Thus, use of procedure that proposed in this paper, can has suitable applications in rapid seismic risk evaluation of studied structures in first stage of rehabilitation process.

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In this paper, analysis the performance of PI, PI-like fuzzy, and parallel fuzzy P+ fuzzy I controllers for He-Ne lasers frequency stabilization by combination of frequency locking and power balanced methods is presented. He-Ne lasers can be attributed to an unstable system due to the influence of environmental factors on its' frequency. Therefore, the stabilization of He-Ne laser is so important in sensitive applications such as laser interferometers and nanometrology systems. The simulation results of controllers by powerful software MATLAB/SIMULINK-GUI show that parallel fuzzy P+ fuzzy I controller has better stabilization performance and integrated absolute error (IAE) than others. Also, frequency fluctuations of He-Ne laser is about 2×10^-11 by parallel fuzzy P+ fuzzy I controller.    

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This paper has proposed‎ ‎a gain-scheduled controller‎ with stability proof and guaranteed cost for a turboshaft driving a variable pitch propeller‎‎. ‎In order to overcome the complexity of the nonlinear model‎, a linear parameter varying (LPV) model is proposed for the first time which is in affine form.‎ Proposed model is established based on a family of local linear models and is suitable for LPV gain scheduling methods‎. Thus a gain scheduled design procedure is proposed which considers parameter dependent Lyapunov matrices to ensure stability and a quadratic cost function for guaranteed performance of the closed loop system‎‎. Proposed procedure also has the advantage of considering an upper bound for change rate of the scheduling signal which decreases conservativeness. ‎Controller design problem and calculating its gain matrices is formulated in a set of Linear Matrix Inequalities‎ which easily can be solved using LMILAB toolbox. Simulation results showed the effectiveness and practicality of the proposed procedure.    

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Jet engine Fuel Control Unit (FCU) has been manufactured recently in the SSAC laboratory of Iran University of science and technology, and is being tested now using HIL testing. Regarding there is no possibility utilizing a jet engine in this test set; an induction motor was used as an actuator to transit rotation acquired using jet engine real time simulation to the FCU pump. In this paper, the induction motor’s velocity control is presented considering condition for the test set. To do so, system identification method is used to model the components employed in induction motor velocity control system. Then, the model is evaluated using experimental test results. Afterward, it is used to design ANFIS controller, and the controller parameters is adjusted employing IWO optimization algorithm as a strong tool for seeking in vast disorder spaces. Subsequently, the controller designed is implemented on a real system. Results gained using simulation and the designed controller implementation show that ANFIS controller designed using IWO algorithm works appropriately.

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In the face of limited water resources, better utilization and operation of irrigation networks is essential. Use of control systems is considered as one of the most assured ways to achieve the aim. In the course of the present study, two centralized controllers are applied to the west canal of Aghili irrigation district in I. R. Iran. The proposed control algorithms consist of a distant Downstream PI Feedback control (DPIF), and a distant Downstream PI Feedback along with Feedforward control (DPIFF). In the controllers, each water-level regulator is adjusted as based on water levels in all the pools of the canal. The test case canal and flow scenarios are simulated using SOBEK. The controllers are evaluated using the simulation results. The results indicated that both of the proposed controllers possess the considerable needed potential to closely match the discharge (at the cross regulators) with those ordered by water users while properly maintaining the water level throughout the length of the canals of the irrigation system. It is apparent that the DPIFF controller is more effective than DPIF controller in providing a desirable performance. Use of these algorithms makes demand oriented water distribution as well as a better performance of the system possible. The DPIFF controller as the main control system accompanied by a local controller as a backup system can be recommended to present an efficient robust control system for the canal.

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In this paper, trajectory tracking control of a wheeled mobile robot is analyzed. Wheeled mobile robot is a nonlinear system. This system including three generalized coordinates (x,y,ϕ), and a nonholonomic constraint. First, system kinematic and dynamic equations are obtained. A non-model-based control algorithm using PD-action filtered errors has been used in order to control the wheeled mobile robot. Non-model-based controllers are always more appropriate than model-based algorithms due to independency from dynamic models, lower computational costs and also robustness to uncertainties. Asymptotic stability of the closed loop system for trajectory tracking control of wheeled mobile robot has been investigated using appropriate Lyapunov function and also Barbalat’s lemma method. Finally, in order to show the effectiveness of the proposed approach simulation and experimental results have been presented. Obtained results show that without requiring a priori knowledge of plant dynamics, and with reduced computational burden, the tracking performance of the presented algorithm is quite satisfactory. Therefore, the proposed control algorithm is well suited to most industrial applications where simple efficient algorithms are more appropriate than complicated theoretical ones with massive computational burden.

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In this study a safe and smooth path planning containing the slightest risk is considered for an Unmanned Underwater Vehicle (UUV). To do so, three smooth and continues functions resembling the three dimensional path are introduced and then their parameters are optimized using the particle swarm optimization method to find the safest possible path. For each point in space a numeric value is considered as vulnerability and the objective function is the integral of the vulnerability over the path produced. This path forms controlling signals which through a TSK fuzzy controller, the UUV is guided. The new arrangement of the propulsion vehicle subsurface was modeled. Since for the design of the controller, the parameters of the Under Water Vehicle dynamic system not used, so the control system is robust with respect to parameter Uncertainties. In the last section three environments with different complexities are considered to illustrate the creating process’s performance of the path and it is concluded that this method demonstrates desired performance in the development of a safe and smooth path through a harmful environment and the design of an adequate controller.

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Because of high accuracy and low weight-to-force ratio, servo hydraulic systems are widely used in various branches of industry. Simultaneous improvement of accuracy and time response are among ever increasing needs for these systems. Rapid movement commands to hydraulic actuator excite attached mechanical components and consequently produce undesired vibrations. Recommended solution to overcome the above mentioned problem is to design and implement advanced controller which takes into consideration the high frequency uncertainties. In this research a two-degree-of–freedom (2DOF) position controller has been design and implemented for undesirable vibration regulation and robust performance achievement on a servo hydraulic table. In this regard various elements of the system are modeled and then the servo hydraulic table nominal system and uncertainty are identified using grey-box method. The 2DOF robust controller is designed using general H∞ framework and analyzed by structured singular value, Mu. The feedback block of controller is used to reduce the effect of uncertainty, measurement noises and reject disturbances, whereas the forward controller shapes the command signals to improve the performance. The designed controller has been implemented on the servo hydraulic test rig in order to track sine and trapezoid position command signals. It has been observed the controller has a more accurate performance and faster time response than the common robust controller with just one feedback block. Extensive experimental results of the developed controller indicate robust performance and acceptable response to disturbance and measurement noise rejection in the defined uncertainty range.

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This paper talked about spacecraft formation flying control. Leader-flower structure is used in formation flying. A non-linear PID controller is designed based on predictive control. The formation relative equation is obtained from nonlinear Hill equation. First, the frequency control is achieved with the using of predictive control algorithm. In control frequency, disturbances have been replaced from disturbance observer. Equations are rewritten in the form of PID gains. Stability of the closed-loop system is proven by closed-loop error dynamics. Nonlinear PID controller performance in the pursuit of desired arrangement has been tested in simulations. Also effects of various factors on the quality of controller results are studied. It is shown that choosing predictive horizon time and disturbance observer gains have the most effect on system response. It is shown that if predictive time increase the settling time increase and the control effort decrease. if disturbance observer gain increase from a limit, it has no effect on settling time but control effort increase. As shown in simulation, the tracking response show the controller method ability. the simulation show the ability of this nonlinear control method in tracking.

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The purpose of this study, control and monitoring of a rehabilitation robot with two degrees of freedom (2-DOF) for rehabilitation of the lower limbs of patients with loss of ability for movement due to injury, disease, stroke or surgical operations. After determining the movements, that is included flexion-extension movements of the knee and hip joints, the performance of the mechanism was investigated using dynamic analysis and simulation. Then, a programmable logic controller (PLC) was employed to control the robot performance. Finally, the accuracy of PLC program was guaranteed by monitoring the robot. Passive, assistive and resistive exercises were considered in programming the controller. In assistive exercises, the forces needed by the patient to perform the movements were actually set automatically by using the feedback data provided by the patient's forces. In addition, to perform the resistive exercises rather than using actual weights, negative loads were employed. The results obtained represent considerable accuracy to perform the movements and create safe conditions for the patient. Also, high flexibility in programming has provided the possibility to perform a wide range of rehabilitation exercises.

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In this paper, a novel methodology is proposed to improve performance of the Networked Control System (NCS) in the face of random time-delays, using Model Predictive Controller (MPC) approach. For this purpose, a new state-feedback MPC structure is developed to cope with random network time-delays when the system is subjected to uncertainties with state and control constraints. The main idea is to reduce the disturbing effect of random network time-delays on regulatory performance of the NCS using a new robust formulation in MPC design. A terminal penalty constraint has been added to the finite horizon objective function to guarantee the stability of the system stability. Finally, applicability of the presented method is evaluated in a real pilot plant within a NCS configuration, being realized by an industrial Ethernet and Foundation Fieldbus technology. It is demonstrated that the proposed online methodology is effective to provide a better performance, having faster response, smaller overshoot and stronger robustness compared to the conventional MPC method with less aggressive control actions.  

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In this paper, an Extended Kalman Filter (EKF) and a model-dependent nonlinear controller over network using the separation principle for Low Earth Orbit (LEO) satellite Attitude Determination and Control Subsystem (ADCS) have been designed. In this context, according to the satellites development trend, ADCS architecture for a broad class of LEO satellites is proposed to stabilize and achieve mission objectives such as precision attitude determination and pointing. This architecture is a Networked Control System (NCS) used to establish connection and communication among control components including sensors, actuators and onboard processors, as well as to share data with other subsystems. Then, by modeling all components of the system, and considering the network effects as a bounded disturbance, the control system is designed to compensate of these effects. For this purpose, estimation and control algorithms including EKF and a model-dependent nonlinear controller is designed such that in addition to achieve desired system performance, the stability of each of them is guaranteed. Afterwards, the nonlinear dynamics model of the satellite in terms of quaternion parameters and angular velocities is presented, and by expression of the separation principle for nonlinear observer and controller design, their convergence and exponential stability conditions based on linearized model of satellite are derived. Proof of theorem shows that the closed-loop system continuously maintained satellite attitude in the specified accuracy range. Finally, simulation results obtained from applying the designed observer and controller on the active satellite in orbit demonstrates the efficiency of the proposed design.

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The purpose of this paper is design, construction and the control of a two-wheel self-balancing robot. For this purpose firstly, a literature study is carried out on the history of manufactured self-balancing robots and the researches which have been done so far in this area are reported. In addition, the robot chassis with consideration of the size and material is analyzed; and the dynamic equations of the robot are computed according to the designed chassis. Then, the robot inertial parameters are measured through different experimental tests and these parameters are used in the equations. Also, the derived equations are simplified and the transfer functions are evaluated for considering the stability of the robot. In this self-balancing robot, the simplified Kalman and complementary filters are used for identifying of the bias angle from the vertical position by combination of data obtained from accelerometer and gyroscope sensors. The PID controller and the robot transfer functions are simulated in MATLAB software. Then, the controller gains are obtained for the stability of the constructed robot. These gains are computed by PID tuning toolbox of MATLAB software as well as theoretically, and the results in each method have been compared with each other. Finally, the robot control electronic circuit is designed for analyzing the results through AVR microcontroller, while angle identification sensor is used.

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The problem of two wheeled self-balancing robot is an interesting and challenging problem in control and dynamic systems. This complexity is due to the inherent instability, nonholonomic constraints, and under-actuated mechanism. Dynamical model of two wheeled self-balancing robot can be presented by a set of highly coupled nonlinear differential equations. Authors, previously, developed the modified dynamical equations of the robot. The governed equations have some differences with the commonly used equations. The main difference is due to the existence of a nonlinear coupling term which is neglected before. In this paper we used an adaptive sliding-mode controller based on the zero dynamics theory. The controller objective is to drive the two wheeled self balancing robot to the desired path as well as to make the robot stable. By some simulations the behavior of the robot with the proposed controller is discussed. It is shown that if the nonlinear coupling term is ignored in designing the controller, the controller cannot compensate its effect. Using Lyapunov theorem and the invariant set theorem, it is proved that the errors are globally asymptotically stable.

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In this paper, modeling and tow type of nonlinear controller for trajectory tracking of a novel five-rotor UAV (Unmanned Aerial Vehicle) is developed. Because of the very simple structure and high maneuverability, quadrotors are one of the most preferred types of UAVs but the main problem of them is their small payload. In the proposed novel model, one propeller is added to the center of vehicle to improve the ability of lifting heavier payloads, and to excel anti-crosswind capability of quadrotor. The dynamic model is obtained via Newton Euler approach. The model is under actuated, nonlinear, and has strongly coupled terms. Also, two types of nonlinear controllers are presented. First one is a conventional input-output feedback linearization controller which involves high-order derivative terms and turns out to be quite sensitive to sensor noise as well as modeling uncertainty. Second controller is a BackStepping controller based on the hierarchical control strategy that yields easier controller. The obtained simulation results confirm that the performance of BackStepping controller is convenient in terms of stability, position tracking and it is robust in presence of disturbance.