420 research outputs found

    Feedback local optimality principle applied to rocket vertical landing VTVL

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    Vertical landing is becoming popular in the last fifteen years, a technology known under the acronym VTVL, Vertical Takeoff and Vertical Landing [1,2]. The interest in such landing technology is dictated by possible cost reductions [3,4], that impose spaceship’s recycling. The rockets are not generally de- signed to perform landing operations, rather their design is aimed at takeoff operations, guaranteeing a very high forward acceleration to gain the velocity needed to escape the gravitational force. In this paper a new control method based on Feedback Local Optimality Principle, named FLOP is applied to the rocket landing problem. The FLOP belongs to a special class of optimal controllers, developed by the mechatronic and vehicle dynamics lab of Sapienza, named Variational Feedback Controllers - VFC, that are part of an ongoing research and are recently applied in different field: nonlinear system [5], marine and terrestrial autonomous vehicles [6,7,8], multi agents interactions and vibration control [9, 10]. The paper is devoted to show the robustness of the nonlinear controlled system, comparing the performances with the LQR, one of the most acknowledged methods in optimal control

    Optimal and Robust Control of Atmospheric Reentry Trajectories

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    Reentering the Earth’s atmosphere is one of the most difficult phases of any spaceship’s mission. During reentry, following an optimal trajectory in terms of minimal heating rate, dynamic pressure, and maximum deceleration is vital to the mission’s success. This dissertation proposes a novel design for a controller based on H8 control methods, with the goal of achieving optimal and robust control for a Reentry Lifting Vehicle. This dissertation begins by summarizing the theory and history behind the Shuttle Space Program, including the planning of its trajectories and descriptions of the Reentry Flight Dynamics Model. The analysis of the obtained reference trajectory will follow and the comparison of it to a real shuttle trajectory will be made. The design and configuration of the H8 controller comes after, beginning with the linearization of the obtained system in the previous step and ending with the recalculation of vehicle state variables after its application. The disturbance is then applied and the results of the actuation of the controller are displayed. The H8 controller for Reentry Lifting Vehicle proves itself to be a useful application presenting satisfying and significant results in this critical phase of flight.A reentrada na atmosfera terrestre é uma das fases mais difíceis da missão de qualquer nave espacial. Durante a reentrada, seguir uma trajectória óptima em termos de taxa mínima de aquecimento, pressão dinâmica e maáxima desaceleração é vital para o sucesso da missão. Esta dissertação propõe o design de um controlador baseado em métodos de H8, com o objectivo de alcançar um controlo óptimo e robusto para um Veículo de Reentrada na atmosfera capaz de produzir sustentação. Esta dissertação começa com um resumo da teoria e história por detrás do Programa Espacial do Vaivém, incluindo o planeamento de trajectórias e descrições do Modelo de Dinâmica de Voo de Reentrada. A análise da trajectória de referência obtida seguir­se­á e será feita a sua comparação com uma trajectória real do vaivém. A concepção e configuração do controlador H8 virá depois, começando com a linearização do sistema obtida no passo anterior e terminando com o recálculo das variáveis de estado do veículo após a sua aplicação. A perturbação é então aplicada e os resultados do accionamento do controlador são exibidos. O controlador H8 para Veículo de Reentrada capaz de produzir Sustentação mostrou ser uma aplicação útil apresentando resultados satisfatórios e significativos nesta fase crítica de voo

    An interactive fuzzy physical programming for solving multiobjective skip entry problem

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    The multi-criteria trajectory planning for Space Manoeuvre Vehicle (SMV) is recognised as a challenging problem. Because of the nonlinearity and uncertainty in the dynamic model and even the objectives, it is hard for decision makers to balance all of the preference indices without violating strict path and box constraints. In this paper, to provide the designer an effective method and solve the trajectory hopping problem, an Interactive Fuzzy Physical Programming (IFPP) algorithm is introduced. A new multi-objective SMV optimal control problem is formulated and parameterized using an adaptive technique. By using the density function, the oscillations of the trajectory can be captured effectively. In addition, an interactive decision-making strategy is applied to modify the current designer’s preferences during optimization process. Two realistic decision-making scenarios are conducted by using the proposed algorithm; Simulation results indicated that without driving objective functions out of the tolerable region, the proposed approach can have better performance in terms of the satisfactory degree compared with other approaches like traditional weighted-sum method, Goal Programming (GP) and fuzzy goal programming (FGP). Also, the results can satisfy the current preferences given by the decision makers. Therefore, The method is potentially feasible for solving multi-criteria SMV trajectory planning problems

    Adaptive fault-tolerant attitude tracking control for hypersonic vehicle with unknown inertial matrix and states constraints

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    This paper proposes an adaptive fault-tolerant control (FTC) method for hypersonic vehicle (HSV) with unexpected centroid shift, actuator fault, time-varying full state constraints, and input saturation. The occurrence of unexpected centroid shift has three main effects on the HSV system, which are system uncertainties, eccentric moments, and variation of input matrix. In order to ensure the time-varying state constraints, a novel attitude state constraint control strategy, to keep the safe flight of HSV, is technically proposed by a time-varying state constraint function (TVSCF). A unified controller is designed to handle the time-varying state constraints according to the proposed TVSCF. Then, the constrained HSV system can be transformed into a novel free-constrained system based on the TVSCF. For the variation of system input matrix, input saturation and actuator fault, a special Nussbaum-type function is designed to compensate for those time-varying nonlinear terms. Additionally, the auxiliary systems is designed to compensate the constraint of system control inputs. Then, it is proved that the proposed control scheme can guarantee the boundedness of all closed-loop signals based on the Lyapunov stability theory. At last, the simulation results are provided to demonstrate the effectiveness of the proposed fault-tolerant control scheme.</p

    Optimal fuel consumption finite-thrust orbital hopping of aeroassisted spacecraft

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    In the paper, the problem of minimum-fuel aeroassisted spacecraft regional reconnaissance (orbital hopping) is considered. A new nonlinear constrained optimal control formulation is designed and constructed so as to describe this mission scenario. This formulation contains multiple exo-atmospheric and atmospheric flight phases and correspondingly, two sets of flight dynamics. The constructed continuous-time optimal control system is then discretized via a multi-phase global collocation technique. The resulting discrete-time system is optimized using a newly proposed gradient-based optimization algorithm. Several comparative simulations are carried out and the obtained optimal results indicate that it is effective and feasible to use the proposed multi-phase optimal control design for achieving the aeroassisted vehicle orbital hopping mission

    Incremental twisting fault tolerant control for hypersonic vehicles with partial model knowledge

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    A passive fault tolerant control scheme is proposed for the full reentry trajectory tracking of a hypersonic vehicle in the presence of modelling uncertainties, external disturbances, and actuator faults. To achieve this goal, the attitude error dynamics with relative degree two is formulated first by ignoring the nonlinearities induced by the translational motions. Then, a multivariable twisting controller is developed as a benchmark to ensure the precise tracking task. Theoretical analysis with the Lyapunov method proves that the attitude tracking error and its first-order derivative can simultaneously converge to the origin exponentially. To depend less on the model knowledge and reduce the system uncertainties, an incremental twisting fault tolerant controller is derived based on the incremental nonlinear dynamic inversion control and the predesigned twisting controller. Notably, the proposed controller is user friendly in that only fixed gains and partial model knowledge are required

    Multi-objective trajectory optimization of Space Maneuver Vehicle using adaptive differential evolution and modified game theory

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    Highly constrained trajectory optimization for Space Manoeuvre Vehicles (SMV) is a challenging problem. In practice, this problem becomes more difficult when multiple mission requirements are taken into account. Because of the nonlinearity in the dynamic model and even the objectives, it is usually hard for designers to generate a compromised trajectory without violating strict path and box constraints. In this paper, a new multi-objective SMV optimal control model is formulated and parameterized using combined shooting-collocation technique. A modified game theory approach, coupled with an adaptive differential evolution algorithm, is designed in order to generate the pareto front of the multi-objective trajectory optimization problem. In addition, to improve the quality of obtained solutions, a control logic is embedded in the framework of the proposed approach. Several existing multi-objective evolutionary algorithms are studied and compared with the proposed method. Simulation results indicate that without driving the solution out of the feasible region, the proposed method can perform better in terms of convergence ability and convergence speed than its counterparts. Moreover, the quality of the pareto set generated using the proposed method is higher than other multi-objective evolutionary algorithms, which means the newly proposed algorithm is more attractive for solving multi-criteria SMV trajectory planning problem

    Solving multiobjective constrained trajectory optimization problem by an extended evolutionary algorithm

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    Highly constrained trajectory optimization problems are usually difficult to solve. Due to some real-world requirements, a typical trajectory optimization model may need to be formulated containing several objectives. Because of the discontinuity or nonlinearity in the vehicle dynamics and mission objectives, it is challenging to generate a compromised trajectory that can satisfy constraints and optimize objectives. To address the multiobjective trajectory planning problem, this paper applies a specific multiple-shooting discretization technique with the newest NSGA-III optimization algorithm and constructs a new evolutionary optimal control solver. In addition, three constraint handling algorithms are incorporated in this evolutionary optimal control framework. The performance of using different constraint handling strategies is detailed and analyzed. The proposed approach is compared with other well-developed multiobjective techniques. Experimental studies demonstrate that the present method can outperform other evolutionary-based solvers investigated in this paper with respect to convergence ability and distribution of the Pareto-optimal solutions. Therefore, the present evolutionary optimal control solver is more attractive and can offer an alternative for optimizing multiobjective continuous-time trajectory optimization problems

    Unified multiobjective optimization scheme for aeroassisted vehicle trajectory planning

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    In this work, a multiobjective aeroassisted trajectory optimization problem with mission priority constraints is constructed and studied. To effectively embed the priority requirements into the optimization model, a specific transformation technique is applied and the original problem is then transcribed to a single-objective formulation. The resulting single-objective programming model is solved via an evolutionary optimization algorithm. Such a design is unlike most traditional approaches where the nondominated sorting procedure is required to be performed to rank all the objectives. Moreover, in order to enhance the local search ability of the optimization process, a hybrid gradient-based operator is introduced. Simulation results indicate that the proposed design can produce feasible and high-quality flight trajectories. Comparative simulations with other typical methods are also performed, and the results show that the proposed approach can achieve a better performance in terms of satisfying the prespecified priority requirements

    Aeronautical engineering: A continuing bibliography with indexes (supplement 286)

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    This bibliography lists 845 reports, articles, and other documents introduced into the NASA scientific and technical information system in Dec. 1992. Subject coverage includes: design, construction and testing of aircraft and aircraft engines; aircraft components, equipment, and systems; ground support systems; and theoretical and applied aspects of aerodynamics and general fluid dynamics
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