جستجوی مقالات مرتبط با کلیدواژه « هدایت بهینه » در نشریات گروه « مکانیک »

In this paper, optimal guidance law design considering fixed final state and time for the final phase booster landing problem of a spacecraft or launch vehicle is investigated and studied. This guidance law, not only satisfied a specific optimality criterion, but it also has the least sensitivity to the initial state’s deviations; which is due to the inclusion of the nonlinear terms in the mathematical modeling using the high order expansions method. The main goal of this research, is to investigate the development and to augment the capability of the high order expansions method for guidance law design. Different implementations of this approach including the differential algebra high order, the generating function based high order and vectorized high order expansions methods have been investigated. After reviewing the implementation concepts of the high order expansions method, the effectiveness of this method has been studied. Then a 3-dimensional booster landing problem has been chosen as the case study and after extracting the mathematical model and nominal optimal solution, the sensitivity variables have been extracted up to the 3rd order. Afterwards, to investigate the performance of the designed guidance law, the Monte Carlo simulations have been performed and it has been shown that the designed guidance law on the basis of the Taylor series and high order expansions method has a good accuracy and is a valuable alterative to the nominal trajectory tracking guidance approach.

The miss distance analysis of the first-order explicit guidance law (EGL) is carried out using linearized equation of motion in the normalized form in order to obtain normalized miss distance curves. The initial heading error, constant target, acceleration limit, radome refraction error, and fifth-order binomial control system are considered. Moreover, body rate feedback is added to the explicit guidance law as a well-known classical compensation method of the radome effect as in proportional navigation. The analysis is performed for different values of the power of the alpha function, defined as the time decrease rate of the zero-effort miss to unit control input. As a special case, the EGL with unit power gives the first-order optimal guidance strategy for minimizing the integral of the square of the commanded acceleration during the total flight time. For the performance/stability analysis, the rms miss distance versus turning rate time constant and radome slope can be plotted for different values of the power of alpha function.

In this research the main goal is to compare the performance of Vectorized High Order Expansions and SDRE method for vertical landing of booster. To this end, at first a comprehensive study of references related to both Vectorized High Order and SDRE method has been performed. Then, the Vectorized High Order Expansions method and the implementation in optimal control problems has been introduced. After that, the SDRE method has been reviewed briefly, and the landing problem has been solved using both methods. To evaluate the performance, a set of various simulations have been performed for both methods and with respect to different initial deviations. By means of simulation results, the performance of both method is studied with regard to landing point errors. To achieve this, statistical results of terminal state errors have been calculated for both method with respect to different initial deviation to evaluate and compare both method, quality-wise.

The atmospheric reentry phase is one of the most important mission steps in space missions, therefore, the guidance and control of reentry vehicles in this phase of mission is important. In this article, a reentry vehicle guidance algorithm is proposed which has suitable robustness in the presence of initial reentry parameters uncertainty. To use any conductive method, first the motion equations must be obtained. In this paper, quadratic nonlinear control method is used to guide the vehicle. In this regard, the equations of motion of reentry vehicles are developed in form of state space and the system and control matrices depending on the state and control variables are extracted. In this article, it is tried to minimize the landing errors at terminal point using Nonlinear Quadratic Tracking (NQT) and chasing a reference trajectory. In order to define a trajectory with different initial states using evolutionary genetic algorithm with changes in weighting matrices Q and R, it is tried to reduce the errors of landing at terminal point. Monte Carlo analysis is used to evaluate the performance of the proposed algorithm. According to the results, the proposed algorithm can reduce the errors more than 90% in the presence of reentry initial parameter uncertainties.

The atmospheric re-entry phase is one of the most significantmission steps in the space missions;hence, theguidance and control of reentry vehicles in this phase of mission is important. In this article, a reentry vehicle guidance algorithm has been proposed which has suitable robustness in the presence of initial reentry parameters uncertainties. Here,it has been tried to minimize the landing errors at terminal point using Nonlinear Quadratic Tracking (NQT) and chasing a reference trajectory. In order to define several trajectories with different initial states using evolutionary genetic algorithm with changes in weighting matrices Q and R, it hasbeen tried to reduce the errors of landing at terminal point. The reentry position of the reentry vehicles may be different from the desired ones with respect to several events. In this situation, reentry vehicles start to move in a new trajectory which is not suitable. Therefore, the reentry vehicles should be guided to come back into the desired trajectory or a new optimum trajectory needs to be redesignedto have the same target position on the ground. To do this, we need optimum weighting matrices R and Q for every new trajectory. In this article, this problem has been resolved using partial least squares regression; meanwhile, obtaining the optimal matrices by genetic algorithms needed many times. Also,it is shown that using this method, in the presence of reentry uncertainties, weighting matrices for each new initial condition hasbeen quickly derived. Additionaly,through the matrices obtained and the nonlinear quadratic tracking controller, reentry vehicle was directedto the target with a good accuracy. The Monte Carlo analysis has been used to evaluate the performance of the proposed algoritm. According to the results, the proposed algoritm has a suitable accuracy level and it can generate the online optimum trajectory.

In this paper, an explicit optimal line-of-sight guidance law for second-order binomial control systems is derived in closed-loop without acceleration limit. The problem geometry is assumed in one dimension and the final time and final position are fixed. The formulation is normalized in three forms to give more insight into the design and performance analysis of the guidance law. The computational burdun of the guidance law is reasonable for now-a-day microprocessors; however curve fitting or look-up table may be used for the implementation of the second-order optimal guidance law. The performance of the second-order optimal guidance law is compared in normalized forms with zero-lag and first-order optimal guidance laws using third-, fourth-, and sixth-order binomial control systems with/without acceleration limit. Moreover, the effect of the final time, the equivalent time constant of the vehicle control system, the vehicle-to-target line-of-sight weighting factor in cost function, and acceleration limit are investigated. Normalized miss distance analysis shows that the miss distance of the second-order guidance law is smaller than the two mentioned schemes for small total flight times, especially with large maneuvering capability.