Terminal Area Energy Management Phase Research Articles

Real-time online trajectory planning and guidance for terminal area energy management of unmanned aerial vehicle

<p style='text-indent:20px;'>Aiming at the energy management problem of unmanned aerial vehicles (UAVs) in the terminal area energy management (TAEM) phase, a real-time online trajectory planning and guidance strategy based on judging energy is proposed. The trajectory planning strategy estimates the flight profile online in real time by judging the energy and changing the radius of the heading alignment circle. In addition, guidance instructions are also obtained at once. In the S-turn stage, the lateral guidance adopts a closed loop control mode with a fixed bank angle. In the remaining stage, the lateral guidance adopts a closed loop control mode for tracking the azimuth angle. In all stages, the longitudinal guidance adopts a closed loop control mode for tracking the flight path angle and flight height. The trajectory planning strategy is able to quickly generate a reference trajectory for testing cases with large variations not only in the initial energy but also in the energy of the flight process. The simulation results show that the proposed trajectory planning and guidance strategy can effectively manage a UAV's energy in the TAEM phase, ensuring that the UAV lands safely.</p>

Guidance of Terminal Area Energy Management Trajectories for Re-entry Vehicles

One of the most critical periods of a space-plane re-entry is the Terminal Area Energy Management (TAEM) phase, where performance utilizing on-board generation is required. The ability of an autonomous Reusable Launch Vehicle (RLV) to recover from unforeseen disruptions is considerably enhanced by on-board trajectory-generating capabilities. Contemporary guiding approaches can reduce operational expenses and design time by utilizing modern computer power and faster algorithms. Also, it is increase the RLV mission resilience and efficiency at the same time. In this paper, the complete method of how to control and land an RLV, using the guidance system and control algorithms during the TAEM phase of re-entry has been discussed. The paper has been produced after thorough research on the newer guidance techniques, control laws and the guidance algorithms which relate mainly to the TAEM phase.

Robust Guidance for a Reusable Launch Vehicle in Terminal Phase

This paper focuses on the three-dimensional guidance strategy for a reusable launching vehicle (RLV) during terminal area energy management (TAEM) phase. Based on sliding mode and shrinking horizon techniques, the proposed scheme consists of trajectory generation and correction mechanisms, which can enhance the guidance precision and robustness against disturbances. The RLV guidance model, in the form of a set of highly non-linear differential equations in time-domain, is recast as an altitude-domain model. By this means, the main characteristics of TAEM gliding motion are extracted. The altitude-domain model is thereby used for trajectory generation. A sliding surface and guidance law are proposed. Hybrid TAEM constraints can be fully satisfied when the proposed guidance law drives the altitude-domain vehicle model to the designated altitude. Using the proposed guidance law as the input of altitude-domain model, a constrained TAEM trajectory is generated, leading to TAEM guidance commands simultaneously. The commands are utilized to drive the time-domain model to the terminal target. In an attempt to compensate for model uncertainties and initial deviations, the guidance commands are modified periodically by shrinking-horizon correction mechanism according to current states. Simulations on different scenarios are provided to demonstrate the performance of the proposed guidance strategy.

CACLA-Based Trajectory Tracking Guidance for RLV in Terminal Area Energy Management Phase.

This paper focuses on the trajectory tracking guidance problem for the Terminal Area Energy Management (TAEM) phase of the Reusable Launch Vehicle (RLV). Considering the continuous state and action space of this guidance problem, the Continuous Actor–Critic Learning Automata (CACLA) is applied to construct the guidance strategy of RLV. Two three-layer neuron networks are used to model the critic and actor of CACLA, respectively. The weight vectors of the critic are updated by the model-free Temporal Difference (TD) learning algorithm, which is improved by eligibility trace and momentum factor. The weight vectors of the actor are updated based on the sign of TD error, and a Gauss exploration is carried out in the actor. Finally, a Monte Carlo simulation and a comparison simulation are performed to show the effectiveness of the CACLA-based guidance strategy.

3D Profile Reconstruction and Guidance for the Terminal Area Energy Management Phase of an Unpowered RLV with Aerosurface Failure

AbstractThis paper focuses on the guidance of an unpowered reusable launch vehicle (RLV) with aerosurface failure in the terminal area energy management (TAEM) phase. The aerosurface failure will l...

Onboard Path Planning for Reusable Launch Vehicles Application to the Shuttle Orbiter Reentry Mission

This paper proposes a method for designing a model-based onboard path planning unit for reusable launch vehicles. Flatness approach is used to map the system dynamics into a lower dimension space. As a consequence, the number of optimization variables involved in the optimal control problem is reduced. In addition, nonconvex nonlinear trajectory constraints in the flat output space are inner approximated by means of superquadric shapes. Genetic algorithms are used to find a global solution both for the superquadric shapes and the associated geometric transformations tuning parameters. Finally, simulations results are presented to illustrate the proposed approach. Simulations are based on the terminal area energy management phase of the Shuttle orbiter STS-1 reentry mission.

Onboard guidance system design for reusable launch vehicles in the terminal area energy management phase

A terminal area energy management (TAEM) guidance system for an unpowered reusable launch vehicle (RLV) is proposed in this paper. The mathematical model representing the RLV gliding motion is provided, followed by a transformation of extracting the required dynamics for reference profile generation. Reference longitudinal profiles are conceived based on the capability of maximum dive and maximum glide that a RLV can perform. The trajectory is obtained by iterating the motion equations at each node of altitude, where the angle of attack and the flight-path angle are regarded as regulating variables. An onboard ground-track predictor is constructed to generate the current range-to-go and lateral commands online. Although the longitudinal profile generation requires pre-processing using the RLV aerodynamics, the ground-track prediction can be executed online. This makes the guidance scheme adaptable to abnormal conditions. Finally, the guidance law is designed to track the reference commands. Numerical simulations demonstrate that the proposed guidance scheme is capable of guiding the RLV to the desired touchdown conditions.

Trajectory Planning for Terminal Area Energy Management Phase of Reusable Launch Vehicles

A three-dimensional trajectory planning algorithm is proposed for the terminal area energy management (TAEM) phase of an unpowered reusable launch vehicle (RLV). Firstly, a reference dynamic pressure profile which characterizes the longitudinal motion is conceived on the basis of the maximum dive and maximum glide capabilities. Secondly, a reference ground-track path is developed, which is composed of four flight segments determined by the location, the size, and the turning mode of a heading alignment cone. Then, the RLV motion equations modeled by kernel extraction protocol (KEP) are numerically solved via secant iteration method, according to the knowledge of the pre-designed dynamical pressure profile and the ground-track path. Finally, a down-track correction scheme is designed to correct the down-track position along the runway centerline. Numerical simulations are conducted to illustrate the effectiveness of the proposed trajectory planning algorithm.

Onboard planning of constrained longitudinal trajectory for reusable launch vehicles in terminal area

A rapid planning algorithm is developed to generate a constrained longitudinal trajectory onboard for reusable launch vehicles (RLVs) in the terminal area energy management (TAEM) phase. The longitudinal trajectory is planned in the flight-path angle vs. altitude space. This flight-path angle profile is designed with required altitude, flight-path angle and range-to-go, and then optimized as a one-parameter search problem to meet the velocity constraint. Considering the dynamic pressure constraint, a dynamic pressure protection (DPP) method is designed. With the DPP, the highly constrained longitudinal trajectory is generated by tracking the planned flight-path angle profile. Finally, the TAEM trajectory planning algorithm is tested on the X-33 vehicle model in different cases. The algorithm is shown to be effective and robust to generate longitudinal flight trajectories with all constraints satisfied in high precision. In each case, the constrained trajectory is planned within 1s on a PC, which indicates that the algorithm is feasible to be employed onboard.

Online trajectory planning and guidance for reusable launch vehicles in the terminal area

A guidance scheme has been proposed based on a new online trajectory planning algorithm for an unpowered reusable launch vehicle (RLV) in the terminal area energy management (TAEM) phase. The trajectory planning algorithm is able to rapidly generate a feasible path from the current state to a desired state at approach and landing interface (ALI) based on the dynamic pressure profile and new ground track geometry. Simple guidance laws are used to keep the RLV flying along the reference path which can be adjusted online by five related parameters. Then, the effectiveness and adaptability of the proposed TAEM guidance scheme is demonstrated by numerical trials with variations in the initial energy, position and aerodynamic performance.

Approach and Landing Range Guidance for an Unpowered Reusable Launch Vehicle

A new method has been developed for predicting and controlling the ground range of an unpowered reusable launch vehicle. The key feature is the use of the quasi-equilibrium glide condition to create a database of range-to-go versus energy for different values of the glide-efficiency factor. Downtrack range to runway touchdown is predicted by performing a two-dimensional table lookup of the range-to-go database. Unlike most predictor–corrector guidance methods, the proposed ground-range guidance scheme does not require onboard numerical integration of the governing equations of motion. Another key element is the coupling between the latter stages of the traditional terminal area energy management phase and the entire approach and landing phase, where the flare-to-touchdown maneuver is concisely parameterized by an exponential altitude profile. Numerical simulations demonstrate that this new method can accurately and reliably guide the vehicle to the desired touchdown conditions despite large errors in the initial states, large errors in the initial downtrack distance to the runway, and aerodynamic drag dispersions.

A new approach to trajectory optimization based on direct transcription and differential flatness

The objective of the present paper is to introduce a reliable method to produce an optimal trajectory in the presence of all limitations and constraints. Direct transcription, has been employed to convert the trajectory optimization problem into nonlinear programming problem via discretizing the profile of state and control parameters and solving for a constrained problem. Differential flatness as a complementary theory leads to model the optimization problem in a lowered dimensional space through defining flat variables. Several curvilinear functions have been used to approximate flat variables and have their own benefits and disadvantages. Accuracy, complexity and number of needed points are examples of related issues. A new approach is developed based on an indirect approximation of flat variables, which leads to decrease the optimization variables and computational costs while preserving the needed accuracy. The proposed method deals with a 3rd order approximation of flat variables via integrating linear function of the acceleration profile. The new method is implemented on the terminal area energy management phase of a reusable launch vehicle. Test results show that the suggested method, as compared with other conventional methods, requires lower computational efforts in cases of the number of iterations and function evaluations, while providing a more accurate optimal solution.

Guidance Law Design for Terminal Area Energy Management of Reusable Launch Vehicle by Energy-to-Range Ratio

A new guidance scheme that utilizes a trajectory planning algorithm by energy-to-range ratio has been developed under the circumstance of surplus energy for the terminal area energy management phase of a reusable launch vehicle. The trajectory planning scheme estimates the reference flight profile by piecing together several flight phases that are defined by a set of geometric parameters. Guidance commands are readily available once the best reference trajectory is determined. The trajectory planning algorithm based on energy-to-range ratio is able to quickly generate new reference profiles for testing cases with large variations in initial vehicle condition and energy. The designed flight track has only one turn heading, which simplifies the trajectory planning algorithm. The effectiveness of the trajectory planning algorithm is demonstrated by simulations, which shows that the guided vehicle is able to successfully dissipate energy and reach the desired approach and landing glideslope target with small tracking errors.

On-line guidance with trajectory constraints for terminal area energy management of re-entry vehicles

In this article, an on-line guidance strategy for terminal area energy management phase of a re-entry flight is proposed. In order to fulfil the objectives of this flight phase, the algorithm continuously performs long- and short-term on-line trajectory generation, also accounting for the most relevant vehicle and trajectory constraints. Long-term guidance computes a reference trajectory which minimizes the distance from the final target. Short-term guidance generates the control commands by computing a trajectory that minimizes the displacement from the reference one, thus compensating for the errors due to the environmental disturbances and to the uncertainties of the vehicle model. In the proposed guidance strategy, the main vehicle performance constraints are appropriately accounted for, thus guaranteeing adaptivity in the failure situations where the manoeuvring capabilities are reduced. The proposed guidance strategy has been developed in the framework of the unmanned space vehicle program of the Italian Aerospace Research Centre for the execution of Dropped Transonic Flight Test second mission. In this article, the algorithm performances and robustness to the vehicle initial state have been assessed through a preliminary Monte Carlo analysis. Furthermore, several simulations with bank angle and angle of attack limitations have shown the effectiveness of the algorithm in the presence of reduced manoeuvring capabilities.

Robust terminal area energy management guidance using flatness approach

This study deals with the design of a guidance scheme based on flatness theory and dedicated to the terminal area energy management phase of a reusable launch vehicle. The proposed guidance strategy is based on a non-linear dynamic inversion technique to handle the large flight envelope that characterises the reentry mission. This inversion takes advantage of a particular choice of linearising terms called flat outputs, that are used to perform an input-to-state linearisation. First, it is shown that the coupled in-plane and out-of-plane vehicle dynamics admits a set of flat outputs. The flatness property of this model is then used to compute the nominal control input profiles corresponding to a single reference trajectory computed off-line. Based on the linearised model obtained by dynamic inversion, a linear tracking controller is then designed so as to circumvent off-nominal flight conditions. Finally, robustness and performances of the proposed guidance scheme are assessed by performing Monte Carlo runs within an industrial simulation environment.

Trajectory optimization and the control of a re-entry vehicle in TAEM phase

This paper investigates the optimal trajectory and the feedback linearization control of a re-entry vehicle during TAEM (terminal area energy management) phase. First, an optimization algorithm with dynamic pressure as the cost function is used to obtain the optimal trajectory in TAEM. This optimal trajectory is considered the reference for ensuring a stable flight path of the re-entry vehicle. The control inputs are the angle of attack and bank angle, which determine the total energy and safety of the re-entry vehicle. Second, feedback linearization is used to design a tracking law in the TAEM phase. This paper validates the optimal solution as the reference trajectory with HAC (heading alignment cylinder) and the tracking performance of the re-entry vehicle onto the reference trajectory by feedback linearization.

Unpowered Approach and Landing Guidance with Normal Acceleration Limitations

F UTURE reusable launch vehicles (RLV) may greatly benefit from advanced guidance and control (AG&C) technologies. Hanson [1–3] has argued that AG&Cwill greatly improve safety and reliability by successfully returning an RLV that is plagued by aerosurface failures, poor vehicle performance, and larger-thanexpected flight dispersions. Advanced guidance methods have been developed for the ascent, entry, and landing phases of an RLV [3– 10]. Approach and landing (A&L) is a critical flight phase that brings the unpowered vehicle from the terminal area energy management (TAEM) phase to runway touchdown. The Space Shuttle A&L guidance scheme uses a two-phase (steep and shallow) reference flight path, which has proven to be effective for low lift-to-drag (L=D) vehicles [11]. Shuttle guidance also relies on a small set of fixed A&L reference profiles, and therefore it may not be well-suited for scenarios with large trajectory dispersions, poor vehicle performance, or actuator failures. Schierman et al. [9] and Kluever [10] have developed onboard trajectory-reshaping algorithms for the A&L phase of an RLV. Both algorithms recompute a new reference A&L path in the presence of winds, aerodynamic uncertainties, and extreme trajectory dispersions. This Note presents an A&L guidance scheme for an unpowered vehicle with diminished maneuverability in the vertical plane, namely, limited normal acceleration capabilities. An RLV with limited normal acceleration will have difficulty transitioning from the initial steep glide slope to a shallow flight path required for touchdown. The proposed guidance method computes a new reference trajectory such that load factor is minimized during the A&L phase. Trajectory planning is accomplished by performing a series of 1-D searches by iterating on a single guidance parameter and numerically propagating multiple paths to touchdown conditions. Numerical results are presented to demonstrate the effectiveness of the guidance method. System Models

Fuzzy Logic Trajectory Design and Guidance for Terminal Area Energy Management

The second generation reusable launch vehicle will leverage many new technologies to make flight to low earth orbit safer and more cost effective. One important capability will be completely autonomous flight during reentry and landing, thus making it unnecessary to man the vehicle for cargo missions with stringent weight constraints. Implementation of sophisticated new guidance and control methods will enable the vehicle to return to earth under less than favorable conditions. The return to earth consists of three phases--Entry, Terminal Area Energy Management (TAEM), and Approach and Landing. The Space Shuttle is programmed to fly all three phases of flight automatically, and under normal circumstances the astronaut-pilot takes manual control only during the Approach and Landing phase. The automatic control algorithms used in the Shuttle for TAEM and Approach and Landing have been developed over the past 30 years. They are computationally efficient, and based on careful study of the spacecraft's flight dynamics, and heuristic reasoning. The gliding return trajectory is planned prior to the mission, and only minor adjustments are made during flight for perturbations in the vehicle energy state. With the advent of the X-33 and X-34 technology demonstration vehicles, several authors investigated implementing advanced control methods to provide autonomous real-time design of gliding return trajectories thus enhancing the ability of the vehicle to adjust to unusual energy states. The bulk of work published to date deals primarily with the approach and landing phase of flight where changes in heading angle are small, and range to the runway is monotonically decreasing. These benign flight conditions allow for model simplification and fairly straightforward optimization. This project focuses on the TAEM phase of flight where mathematically precise methods have produced limited results. Fuzzy Logic methods are used to make onboard autonomous gliding return trajectory design robust to a wider energy envelope, and the possibility of control surface failures, thus increasing the flexibility of unmanned gliding recovery and landing.

ゲインスケジューリングを用いた無人宇宙往還機の飛行制御系設計（ν‐ｇａｐを用いた動作点選択と局所多目的ゲインスケジューリングの提案）

This paper presents flight control designs of an unmanned space vehicle, HOPE-X vehicle using an interpolation gain scheduling technique. The ν-gap metric is used to evaluate the errors between linear models at operating points. The linear parameter varying models for the HOPE-X vehicle were then constructed by minimizing two types of indices defined with the ν-gap metric. On the other hand, the magnitude of the input is locally constrained to avoid the saturation of the control surfaces. In the numerical simulations of the HOPE-X, the gain scheduling control laws whose number of operating points was greater than two could be applicable to the whole region of the terminal area energy management phase of the HOPE-X. Furthermore, the input constraint was effective to suppress the magnitude of the input and to extend the stability region of the design parameter.

線形補間ゲインスケジューリングを用いた無人宇宙往還機の飛行制御系設計

This paper presents flight control designs of an unmanned space vehicle, HOPE-X, vehicle using interpolation gain scheduling techniques. There are three flight phases from deorbit to landing in HOPE-X; reentry, terminal area energy management (TAEM), and approach and landing. This paper is addressed to the TAEM phase in which an amount of lateral maneuvers are required. Two interpolation gain scheduled state feedback laws were designed with respect to the Lyapunov functions used for guaranteeing the global stability of the closed-loop system, and were applied to the numerical simulations of the HOPE-X. As a result, the gain scheduled control law showed better control performance in the entire of TAEM phase than fixed state feedback laws. The gain scheduling using a parameter-dependent Lyapunov function was superior to the one using a conventional Lyapunov function.