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در این مقاله، طراحی مسیر بازگشت به جو یک کپسول فضایی از لحظه خروج از مدار اولیه تا رسیدن به شرایط عملکرد سیستم بازیابی مورد بررسی قرار می گیرد. برای این منظور دو روش حل عددی مسائل کنترل بهینه با رویکرد چند بازه ای توسعه داده شده و مورد استفاده و مقایسه قرار گرفته است. روش اول در دسته روشهای پرتاب (شوتینگ متد) قرار دارد که بهینه سازی در آن با استفاده از الگوریتم ژنتیک صورت می پذیرد. در این روش با بهره گیری از مدل جامعی برای توصیف تاریخچه کنترلی، به طور همزمان تعداد و چینش بازه ها و نوع تاریخچه کنترلی در هر بازه بهینه می شود. روش دوم موسوم به روش شبه طیفی می باشد که در آن متغیرهای حالت و کنترل برای ارضای همزمان قیود و شرایط بهینگی در نقاطی موسوم به گره ها تعیین می شوند. این روش هم با رویکرد چند بازه ای حل شده و با روش اول مقایسه گشته است. روشهای توسعه داده شده که در انتها عملکرد آنها مورد مقایسه و تحلیل قرار گرفته، قابل استفاده برای حل کلیه مسائل کنترل بهینه و طراحی مسیر می باشند.

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Aerospace Launch Vehicles (ALVs), used for launching artificial satellites and space stations to Earth orbits, usually encounter with failure in navigation systems . In these cases, survival of an ALV during accurate payloads injection in orbits is one of the most critical issues for Guidance and Control systems.An important challenge for safety of Aerospace Launch Vehicle (ALV) is their reliability against all types of faults. There is a requirement for on-board fault detection without deteriorating the performance of ALV. In this paper, a new software sensor is proposed for fault detection and compensation based on symmetrical behavior of the yaw and pitch channels of an ALV. For this purpose, using identification techniques on the yaw channel, a new software sensor is developed as an online rigid dynamic predictor for the pitch channel. The proposed software sensor is employed to generate the residual of estimation error as an indicator of predefined faults. The main novelty of this software sensor is online tuning of the virtual sensor against unforeseen variations in the parameters of the vehicle. Robustness of the new control system in the presence of asymmetric behavior is investigated. The efficiency of the proposed fault tolerant method is illustrated through simulations.

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This paper is concerned with design, develop and implementation of a quaternion based attitude control system for a rigid suborbital module which using cold gas thrusters over a short-duration mission. The quaternion controller produces a demand torque, and a pulse-width pulse-frequency (PWPF) modulator determines the necessary thruster fire signals. The effect of disturbances on module attitude has been investigated and the most significant found to be due to misalignment of thrusters effects. The system concept has been evaluated through modeling in Simulink and a rapid prototype hardware-in-the-loop platform and has been found to meet the requirements laid out for a typical module mission. The satisfactory performance of the controllers was illustrated through both numerical and hardware-in-the-loop simulations, where a system of twelve thrusters and load sensors were implemented in the hardware and disturbance effects such as thrust misalignment and sensor noise were studied. The results show the effectiveness of the proposed control method for agile attitude maneuvers of suborbital modules. The results of the HIL simulation were also used for tuning the parameters of the module’s numerical simulation that is to be used for error budgeting analyses.

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Optimal trajectory planning is an important task which is required in most of guidance missions. This paper introduces a new method that utilizes the most important characteristics of global optimization methods along with a new gradient-based method in a two layered scheme for the trajectory planning. In the first layer to construct a convenient shooting method based algorithm, some of the most important global methods of optimization are used in an information transform structure. Exchanging the information between selected algorithms helps for increasing the efficiency of problem solving. To do this, a comprehensive model for parameterization of the control history is introduced which allows the method to search for the best profile in a variety of different profiles. Results of this layer are transformed to the second layer that uses one of direct methods of solving the optimal control problems. This gradient based method named Radau pseudospectral method using of the results of global methods, completes the optimization process. Finally, developed algorithm is used to find the optimal trajectory of a reentry capsule and effects of the path constraint values on the total heat absorbed is investigated.

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Processor memory capacity and update frequency are one of the main restricting constraints in star tracker design and development. In order to decrease the volume of the data required onboard, uniforming the star catalog which is eventually used as pattern recognition database is considered. Three different methods of uniforming the star catalog have been applied. Spherical patches, fixed slope curve and charged particles or Thomson’s problem. After generation of a sphere with uniform distribution of points, a star is assigned to each point according to its spherical distance or best magnitude. In order to evaluate the performance of each method, seven evaluation criteria are defined. Point distribution minimum energy, catalog size, minimum star required for pattern recognition, mean and standard deviation of star distribution in each frame, database size and pattern recognition true recognize percentage. These seven criteria are combined in weighted equation of “average” to choose the best star catalog uniforming method with respect to the star tracker mission. After having implemented the average equation it is demonstrated that uniforming the star catalog using charged particle or Thomson’s problem has better results.

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Reaction wheels are angular momentum exchange devices used to stabilize the position of the satellite and maneuvering. This actuator can change the momentum of the satellite to change the attitude of the system. During the process of operation, noise and disturbances arisen from the unbalancing of the wheels lead to inconvenient performance of the reaction wheels. Several works have been presented for active noise cancelation in these devices. But, the practical tools of signal processing such as filter banks and wavelets which used for offline de-noising are samples of very useful noise cancellation methods. If these toolboxes are employed for online de-noising these signal processing approaches are applicable for noisy systems such as reaction wheels. The main challenge of this strategy is delay arisen from the signal processing and this is inevitable. In this paper, a strategy of online wavelet de-noising is designed and proposed for noise cancellation in a reaction wheel. In this regards, for considering the delay compensation the method of Smith predictor is used to lead the delay of the process out of the closed loop control system. The accuracy of this algorithm requires an estimate of the system dynamics and the understanding of the delay system. According to the use of the FIR filter delay can be fully calculated. The recursive least squares used for identification reaction wheel as an estimate of the system.

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Considering uncertainties in the design process is one of the most important factors to achieve reasonable and reliable results. In this article, a collaborative structure, which is a multidisciplinary design optimization, is combined with a robust design approach to design an optimum and robust launch vehicle, while considering the effects of uncertainties. First, a liquid-fuel vehicle is designed under two disciplines to send a 1200 kg mass to the 750 km orbit from the earth surface with 50.7◦ orbital inclination, using the collaborative structure. It should be said that the first discipline includes three subsystems that are engine design, geometry design and estimating the mass. Also, the second discipline includes three subsystems that are pitch program, aerodynamic calculations and trajectory simulation. Then, the optimum collaborative output is combined with the robust design in a multi-objective model to achieve the final vehicle configuration. The results show that the calculated mass of the first stage of the project using the collaborative robust design process is 3 tons heavier than the calculated mass using optimum collaborative design approach and the engines working time is increased. The overall size of the launch vehicle is increased too. The outputs of each subsystem have been evaluated and also, the overall results have been compared with another design process, i.e. MDF. This comparison shows the acceptable accuracy of the proposed approach.

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In this study, optimum design of composite sandwich structures will be surveyed and presented using hybrid algorithm. Since, most modern payload fairings are constructed of a composite sandwich laminate, in this research the architecture of the fairing structure has been analyzed on the basis of the composite sandwich shell with a flexible core. However, from the geometrical point of view, fairing composed of two conical and cylindrical parts. Therefore, in the first phase, buckling analysis of conical composite sandwich shell has been done by using high-order theories and the obtained equations reduce to the governing equations of cylindrical sandwich shell when the semi-cone angle is set equal to zero. In the second phase, the obtained structure was optimized using hybrid algorithm. Due to the variety and complexity of design variables in composite sandwich structures, designing process leads to difficulties and obstacles in design optimization problems. Since, the most important selected discipline for optimizing the mass specifications of launch vehicle is structure, therefore with relying on optimization of the structure, after completion of optimization process, finally considerable mass reduction i.e. 40 percent comparing to the utilized fairing in this study (Fairing of Safir), will be concluded due to simultaneous changing of material and optimization.

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In this paper, conceptual design of a General Aviation Aircraft (GAA) is explained as a multi-objective Multidisciplinary Design Optimization (MDO). In the early sizing phase, preliminary aircraft configuration is defined based on a predetermined requirements and statistical Study. Afterwards, conceptual design disciplines are developed and integrated based on Multidisciplinary Design Feasibility (MDF) structure to improve the aircraft performance. The MDF loop is established by implementing a multidisciplinary analysis which includes disciplines as engine selection, weight and sizing, aerodynamics, performance and stability. In this design process, Constraints and algorithms are considered based on the Gudmundsson design approach. Design variables are selected carefully using sensitivity analysis on design objectives (i.e. reducing the weight and increasing the range). In order to obtain a feasible design, static stability constraints are considered. The NSGA-II multi-objective evolutionary optimization algorithm is utilized to demonstrate a set of possible answers in the form of the Pareto front. By selecting different engines and illustrating the Pareto fronts resulted from optimization process, the feasibility and effectiveness of rapid GAA conceptual design is demonstrated.

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In this paper the problem of optimal multiple-burn injection of a satellite into geostationary orbit using an upper stage with a limited thrust and restart capability, and comparison with sub-optimal case is considered. The goal is finding thrust vector angle, times of the engine firings and optimal duration of active phases of the upper stage so as to minimize fuel consumption and to meet desired boundary conditions. The contribution of this research is developing an accurate and rapid convergence algorithm for solving multiple-burn trajectory for satellite injection into geostationary orbit. To solve the multipoint boundary value problem, an improved indirect shooting method with high performance and modified Newton’s method is presented and used for optimal solution. Moreover, the novel method presented for multi burn problem, not only has very good accuracy, but also, it converges very fast to the desired end conditions. Various flight sequences with multiple burns are considered and the optimal trajectory with minimum fuel consumption criteria, for each flight sequence is derived. The verification and validation of the proposed algorithm is made via comparison with references. Finally, the results of optimal solutions are compared with the results of sub-optimal solution which its thrust direction is aligned to the velocity vector direction.

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In this research, High Order Expansions method implementation in order to obtain an optimal solution for an unmanned aerial vehicle continuous maneuver problem is studied. The main goal of this research, is to describe a specific approach to solve nonlinear optimal control problems using series expansions and algebraic matrix Riccati equation in order to obtain solutions with better performance. Based on this, the state feedback control with different powers is used for optimal commands calculations. Clearly, the control command would be high order and closed-loop; it has been shown it results in a superior performance in smooth nonlinear problems. In this research, in addition to the implementation of High Order Expansions method and its usage, a different approach of dealing with optimal control problem based on this method has been given. Continuous maneuver of an unmanned aerial vehicle problem is solved for investigating the performance of the proposed method. In this example, the High Order Expansions up to and including the third order are used and two different flight scenarios are simulated. By investigating the result of the solution to this problem, the superior performance of the third order optimal command with respect to the first order is illustrated.

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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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