Optimal Guidance Problem Research Articles

Olfactory-based powered descent guidance for Mars methane plume exploration in long-time-average wind environment

This paper investigates an olfactory-based powered descent guidance method that enable a lander to autonomously locate and target the vent source of any methane plume in long-time-average wind environment on Mars. The episodic methane plumes emanating from the Martian surface invite the possibility of direct access to the subsurface methane reservoir to acquire pristine organic materials. Constrained by the insufficient knowledge of the accurate plume vent location, Mars landers must infer the target location — the plume source — autonomously during the powered descent. However, existing powered descent guidance methods require the target location as a terminal constraint, rendering them ineffective in plume exploration missions. We propose an olfactory-based powered descent guidance method that could steer a lander to target the methane vent source by tracking the gradient of methane concentration in long-time-average wind environment, imposing sub-optimal fuel consumption. A novel olfactory navigation method based on tracking the negative logarithmic concentration gradient, and the corresponding gradient measurement method, is proposed. By implementing the negative logarithmic gradient field, gradient-dependent dynamic equations for the powered descending lander are proposed. The gradient-dependent equations provide a way to transform the original optimal guidance problem, which is non-convex and terminal-free, into a convex and terminal-fixed problem. A suboptimal guidance law, similar to E-guidance, is then derived by solving this problem. The proposed guidance could target the vent source of any methane plume in long-time-average wind environment, imposing modest fuel consumption by feeding back the concentration gradient. Numerical simulations illustrate that, in comparison to the terminal-fixed E-guidance and the open-loop fuel-optimal guidance, the lander imposes additional fuel consumption of 2.57% and 12.15% respectively, using the proposed guidance law.

Meta-Reinforcement Learning for Spacecraft Proximity Operations Guidance and Control in Cislunar Space

Innovative lightweight and model-free guidance algorithms are essential to achieve full autonomy of spacecraft and address future space exploration challenges. In the near future, this type of technology will be essential for cislunar space proximity operations, such as NASA’s Artemis program and its Lunar Gateway project. In this scenario, a meta-reinforcement learning algorithm is employed to address the real-time optimal guidance problem of a spacecraft in the cislunar environment. Non-Keplerian orbits pose complex dynamics, where classic control theory may be less adaptable and more computationally expensive compared to machine learning approaches. Meta-RL stands out for its ability to learn how to learn through experience, training on various tasks to enhance efficiency, and effectiveness in tackling new ones. By modeling a stochastic optimal control problem within the circular restricted three-body problem framework as a Markov decision process, an LSTM-based network agent is trained using proximal policy optimization, considering operational constraints and stochastic effects for safety and robustness evaluation. Additionally, an MLP-based agent and an optimal control pseudo-spectral solution are assessed for comparison. The resulting tool autonomously guides spacecraft in cislunar proximity operations, approximating the optimal control solution with a versatile algorithmic framework. This ensures both robustness and computational efficiency.

Dynamic Encircling Cooperative Guidance for Intercepting Superior Target with Overload, Impact Angle and Simultaneous Time Constraints

This paper proposes a dynamic encircling cooperative guidance (DECG) law to enable multiple interceptors to cooperatively intercept a superior target, considering low velocity, limited overload, impact angle and simultaneous arrival constraints. First, the feasible escaping area of the target is analyzed and a dynamic encircling strategy for the target is established. This strategy efficiently provides virtual escaping points, allowing interceptors to dynamically encircle the target without excessive energy consumption, ultimately leading to a successful interception. Second, to enhance the physical feasibility of the kinematic equations governing the interaction between interceptors and target at the virtual escaping points, the independent variable is substituted and the kinematic equations are remodeled. Convex optimization is employed to address the multi-constraint optimal guidance problem for each interceptor, thereby facilitating simultaneous interception. Compared with the existing guidance laws, DECG has a more practical and feasible cooperative strategy, is able to handle more constraints including the interceptor’s own constraints and cooperative constraints, and does not rely on the precise calculation of explicit remaining flight time in the guidance law implementation. Lastly, the effectiveness, superiority and robustness of the DECG law are evaluated through a series of numerical simulations, and its performance is compared with that of the cooperative proportional navigation guidance law (CPNG).

Minimum-Effort Waypoint-Following Differential Geometric Guidance Law Design for Endo-Atmospheric Flight Vehicles

To improve the autonomous flight capability of endo-atmospheric flight vehicles, such as cruise missiles, drones, and other small, low-cost unmanned aerial vehicles (UAVs), a novel minimum-effort waypoint-following differential geometric guidance law (MEWFDGGL) is proposed in this paper. Using the classical differential geometry curve theory, the optimal guidance problem of endo-atmospheric flight vehicles is transformed into an optimal space curve design problem, where the guidance command is the curvature. On the one hand, the change in speed of the flight vehicle is decoupled from the guidance problem. In this way, the widely adopted constant speed hypothesis in the process of designing the guidance law is eliminated, and, hence, the performance of the proposed MEWFDGGL is not influenced by the varying speed of the flight vehicle. On the other hand, considering the onboard computational burden, a suboptimal form of the MEWFDGGL is proposed to solve the problem, where both the complexity and the computational burden of the guidance law dramatically increase as the number of waypoints increases. The theoretical analysis demonstrates that both the original MEWFDGGL and its suboptimal form can be applied to general waypoint-following tasks with an arbitrary number of waypoints. Finally, the superiority and effectiveness of the proposed MEWFDGGL are verified by a numerical simulation and flight experiments.

Three-Dimensional Guidance Approach with Obstacle Avoidance against Maneuvering Targets

A guidance approach with obstacle avoidance is proposed for maneuvering target interception. Firstly, by decomposing the constrained optimal guidance problem into two associated subproblems, the overall scheme of guidance is presented. Secondly, to improve the guidance accuracy against the maneuvering target, an MPC controller with disturbance estimation is designed, which transforms the global optimization problem into a finite-horizon optimal control problem. An auxiliary controller is also developed to ensure the system’s stability. Then, to achieve obstacle avoidance without affecting the guidance accuracy, a unified function is built to assess the threats from obstacles of different shapes, based on which the optimal guidance-obstacle avoidance model is established. Finally, to solve the above optimization problems, a hybrid solver is developed based on the adaptive moment estimation (Adam) algorithm, whose output will serve as the real-time guidance command. The numerical simulation results show that the guidance approach presented in this paper can achieve precise guidance and obstacle avoidance in various scenarios, and the Monte Carlo experiment further demonstrates the robustness and computation efficiency of the approach.

Cooperative optimal guidance of hypersonic glide vehicles by real-time optimization and deep learning

This paper investigates the cooperative optimal guidance of hypersonic glide vehicles (HGVs) in the terminal phase with consideration on time-varying velocity, aerodynamic forces, and practical constraints. The cooperative optimal guidance problem is formulated as an optimal control problem with time as the independent variable, which brings great convenience in controlling the impact time. We propose proper convexification techniques to convexify this problem and apply successive convex optimization to get the solution of the original problem. To achieve cooperative guidance of multiple HGVs with time coordination constraint, a deep learning–based approach is proposed to find an optimal common impact time assigned to all the HGVs. The training samples required by deep learning are obtained by convex optimization. An algorithm is then presented to summarize the cooperative optimal guidance strategy. In each guidance loop, the common impact time is updated according to mission conditions, and the guidance commands are generated by the successive solution procedure in real time. Numerical examples will be provided to demonstrate that the proposed cooperative optimal guidance algorithm is effective and efficient, and it can achieve better performance than a popular cooperative proportional navigation guidance law.

Computational Optimal Impact Angle Control Guidance Laws Weighted by Arbitrary Functions

This paper presents a computational impact angle control guidance law based on the energy cost weighted by arbitrary functions in order to shape the acceleration command as desired. The optimal guidance problem is established in the impact angle frame and is solved by the Gauss orthogonal collocation method. The proposed guidance law is formulated from the generalized optimal control framework, thus a new guidance law that allows achieving a specific guidance goal can be easily obtained in the way of devising a proper weighting function (smooth, piecewise, nonsmooth, or even discontinuous). This property provides more degrees of freedom in the guidance law design to accomplish a specified guidance objective. A hardware experiment is conducted to evaluate the real-time computational capacity of the proposed computational guidance law. Illustrative examples with several types of weighting functions, including smooth, piecewise, nonsmooth, and discontinuous functions, are provided to demonstrate the advantages and capacity of the proposed guidance law.

Multi-phase and dual aero/propulsive rocket landing guidance using successive convex programming

This paper aims to suggest a new landing guidance algorithm for reusable launch vehicles (RLVs) to enable generation of fuel-efficient trajectories based on successive convex programming. To this end, a dual aero/propulsive landing guidance problem is first formulated to fully exploit the additional moment generated by the aerodynamic control to reduce the propulsion demand required for attitude control. As the result of the aerodynamic landing phase could greatly affect the fuel-optimal trajectory during the vertical landing phase, the formulation is further extended to the multi-phase optimal guidance problem using state-triggered constraints. The proposed guidance strategy is then obtained by solving the formulated optimal control problem based on the successive convex optimization framework using an interior point method The main contribution of this study lies in forming new RLV landing guidance problems to get an optimal trajectory and transforming the corresponding nonconvex problem into a convex optimization problem by introducing appropriate combinations for convexification techniques. Additionally, this paper introduces several practical constraints, such as the maximum slew rate of aerodynamic control fins and nozzle angles, which are not considered in previous works. In this paper, the performance of the proposed method with the potential for online computation is investigated through numerical simulations.

Optimal guidance method based on conjugate gradient method and pseudospectral method

This paper aims to propose a method to solve the nonlinear optimal guidance problems with various performance indexes. First, the conjugate gradient method is derived based on the performance indexes of general form and specified form, and the execution steps of the optimal guidance method are obtained. Secondly, the pseudospectral collocation scheme is used to solve some intermediate variables in the algorithm, and the differential equations are transformed into algebraic equations, so as to improve the computational efficiency. Finally, the proposed method is applied to the air-to-ground missile guidance problem. By comparing with the simulation results of GPOPS-II, the optimality of the proposed method is verified. Additionally, the high computational efficiency of the algorithm is also verified.

Fuel-Optimal Guidance for End-to-End Human-Mars Entry, Powered-Descent, and Landing Mission

This article investigates the fuel-optimal guidance problem of the end-to-end human-Mars entry, powered-descent, and landing (EDL) mission. It applies a unified modeling scheme and develops a computationally efficient new optimization algorithm to solve the multiphase optimal guidance problem. The end-to-end EDL guidance problem is first modeled as a multiphase optimal control problem with different dynamics and constraints at each phase. Via polynomial approximation and discretization techniques, this multiphase optimal control problem is then reformulated as a polynomial programming problem. By introducing intermediate variables and quadratic equality constraints, a polynomial program is equivalently converted into a nonconvex quadratically constrained quadratic program (QCQP). Then, a novel customized alternating direction method of multipliers (ADMM) is proposed to efficiently solve the large-scale QCQP with convergence proof to a local optimum under certain conditions on the algorithmic parameters. The fuel savings under the end-to-end human-Mars EDL guidance are verified by comparing to the fuel consumption using the separate phase guidance approach. Furthermore, the computational efficiency of the customized ADMM algorithm is validated by comparing to the state-of-the-art nonlinear programming method. The robustness of the customized ADMM algorithm is verified via extensive simulation cases with random initial conditions.

Guidance algorithm for impact time, angle, and acceleration control under varying velocity condition

A highly constrained guidance algorithm is investigated, which is capable of addressing the constraints on impact time, impact angle, and terminal load factor simultaneously, in particular under a challenging condition where the missile's velocity varies passively with time and cannot be adjusted for impact time control. To develop the guidance, a new flight dynamics is established by treating downrange as the independent variable and flight time as a state variable, and then augmented by putting forward an Additional Maneuvering Acceleration Term (AMAT) for impact time control. Based on the dynamics, an impact-angle-constrained optimal guidance problem is proposed and solved to develop a new guidance formula. Further, the generalized semi-analytical solutions for the guidance command and impact time are derived by putting forward and linearizing a novel engagement model, which takes the heading angle, line-of-sight angle, and flight time as the state variables. Especially, in Appendix A, for a special kind of varying velocity profile, the complete closed-form solutions are developed. Subsequently, for addressing the impact time constraint, the impact-time solution is used to determine the parameters of the AMAT. Finally, to control the terminal load factor, two inequalities are created by applying the kinetic energy theorem, and then used to deduce the limits of some complex integral terms appearing in the generalized semi-analytical solutions. By analyzing these limits, the guidance coefficients making the load factor converge to a pre-specified value can be determined. The superiority of the guidance is demonstrated by conducting a large number of trajectory simulations.

Endoatmospheric Ascent Optimal Guidance with Analytical Nonlinear Trajectory Prediction

In this paper, an endoatmospheric ascent optimal guidance law with terminal constraint is proposed, which is under the framework of predictor-corrector algorithm. Firstly, a precise analytical nonlinear trajectory prediction with arbitrary Angle of Attack (AOA) profile is derived. This derivation process is divided into two steps. The first step is to derive the analytical trajectory with zero AOA using a regular perturbation method. The other step is to employ pseudospectral collocation scheme and regular perturbation method to solve the increment equation so as to derive the analytical solution with arbitrary AOA profile. The increment equation is formulated by Taylor expansion around the trajectory with zero AOA which remains the second order increment terms. Therefore, the resulting analytical solutions are the nonlinear functions of high order terms of arbitrary AOA values discretized in Chebyshev-Gauss-Legendre points, which has high accuracy. Secondly, an iterative correction scheme using analytical gradient is proposed to solve the endoatmospheric ascent optimal guidance problem, in which the dynamical constraint is enforced by the resulting analytical solutions. It only takes a fraction of a second to get the guidance command. Nominal simulations, Monte Carlo simulations, and optimality verification are carried out to test the performance of the proposed guidance law. The results show that it not only performs well in providing the optimal guidance command, but also has great applicability, high guidance accuracy and computational efficiency. Moreover, it has great robustness even in large dispersions and uncertainties.

Impact-Angle and Terminal-Maneuvering-Acceleration Constrained Guidance against Maneuvering Target

A new, highly constrained guidance law is proposed against a maneuvering target while satisfying both impact angle and terminal acceleration constraints. Here, the impact angle constraint is addressed by solving an optimal guidance problem in which the target’s maneuvering acceleration is time-varying. To deal with the terminal acceleration constraint, the closed-form solutions of the new guidance are needed. Thus, a novel engagement system based on the guidance considering the target maneuvers is put forward by choosing two angles associated with the relative velocity vector and line of sight (LOS) as the state variables, and then the system is linearized using small angle assumptions, which yields a special linear time-varying (LTV) system that can be solved analytically by the spectral-decomposition-based method. For the general case where the closing speed, which is the speed of approach of the missile and target, is allowed to change with time arbitrarily, the solutions obtained are semi-analytical. In particular, when the closing speed changes linearly with time, the completely closed-form solutions are derived successfully. By analyzing the generalized solutions, the stability domain of the guidance coefficients is obtained, in which the maneuvering acceleration of the missile can converge to zero finally. Here, the key to investigating the stability domain is to find the limits of some complicated integral terms of the generalized solutions by skillfully using the squeeze theorem. The advantages of the proposed guidance are demonstrated by conducting trajectory simulations.

Comparison of Two Optimal Guidance Methods for the Long-Distance Orbital Pursuit-Evasion Game

The orbital pursuit-evasion game (OPE) is a topic of research that has been attracting increasing attention from scholars. However, most works based on the relative dynamics under a short-distance assumption is not applicable when the distance between two spacecrafts is too large. Accordingly, there should be two phases in the OPE, a long-distance OPE (LDOPE) as well as a short-distance one. This article concerns on the optimal guidance problem for the LDOPE. Two different models are introduced in this article to formulate the LDOPE, namely, the Cartesian model, and the spherical model. Then, to overcome the unacceptable solution computation time of traditional algorithms, such as the differential evolution (DE), a well-designed algorithm called “mixed global-local optimization strategy” (MGLOS), which consists of the global optimization phase, and the local optimization phase, is introduced in this article. The MGLOS is nearly two orders of magnitude more efficient than the DE. Moreover, simulations under different initial conditions demonstrate the robustness of the algorithm, and the accuracy, and efficiency of the Cartesian, and spherical models, respectively. Finally, the robustness of two models is analyzed by Monte Carlo simulation, which provides a quantified way to make a choice between two models depending on the measurement accuracy, and permitted maximum error.

Linear Quadratic Minimum-Effort, Specify-Performance Approach to Missile Guidance

A generic guidance design framework is proposed that is based on the idea of minimizing the guidance effort expressed as the quadratic integral of the guidance command and imposing performance constraints on various trajectory parameters at arbitrary points in time during the flight. This framework extends previous work on guidance algorithms for active aerial defense and for obstacle avoidance. Using some concrete examples it is shown that the proposed framework is flexible enough to tackle interesting guidance problems related to multiple targets scenarios. It is also shown that the same framework offers a practical solution for the optimal intercept guidance problem with constraints on the lateral missile acceleration.

Fuel-Efficient Powered Descent Guidance on Large Planetary Bodies via Theory of Functional Connections.

In this paper we present a new approach to solve the fuel-efficient powered descent guidance problem on large planetary bodies with no atmosphere (e.g., Moon or Mars) using the recently developed Theory of Functional Connections. The problem is formulated using the indirect method which casts the optimal guidance problem as a system of nonlinear two-point boundary value problems. Using the Theory of Functional Connections, the problem's linear constraints are analytically embedded into a functional, which maintains a free-function that is expanded using orthogonal polynomials with unknown coefficients. The constraints are always analytically satisfied regardless of the values of the unknown coefficients (e.g., the coefficients of the free-function) which converts the two-point boundary value problem into an unconstrained optimization problem. This process reduces the whole solution space into the admissible solution subspace satisfying the constraints and, therefore, simpler, more accurate, and faster numerical techniques can be used to solve it. In this paper a nonlinear least-squares method is used. In addition to the derivation of this technique, the method is validated in two scenarios and the results are compared to those obtained by the general purpose optimal control software, GPOPS-II. In general, the proposed technique produces solutions of accuracy. Additionally, for the proposed test cases, it is reported that each individual TFC-based inner-loop iteration converges within 6 iterations, each iteration exhibiting a computational time between 72 and 81 milliseconds, with a total execution time of 2.1 to 2.6 seconds using MATLAB. Consequently, the proposed methodology is potentially suitable for real-time computation of optimal trajectories.

Optimal guidance against active defense ballistic missiles via differential game strategies

The optimal guidance problem for an interceptor against a ballistic missile with active defense is investigated in this paper. A class of optimal guidance schemes are proposed based on linear quadratic differential game method and numerical solution of Riccati differential equation. By choosing proper parameters, the proposed guidance schemes are able to drive the interceptor to the target and away from the defender simultaneously. Additionally, fuel cost, control saturation, chattering phenomenon and parameters selection were taken into account. Satisfaction of the proposed guidance schemes of the saddle point condition is proven theoretically. Finally, nonlinear numerical examples are included to demonstrate the effectiveness and performance of the developed guidance approaches. Comparison of control performance between different guidance schemes are presented and analysis.

Least-squares solution of a class of optimal space guidance problems via Theory of Connections

In this paper, we apply a newly developed method to solve boundary value problems for differential equations to solve optimal space guidance problems in a fast and accurate fashion. The method relies on the least-squares solution of differential equations via orthogonal polynomials expansion and constrained expression as derived via Theory of Connection (ToC). The application of the optimal control theory to derive the first order necessary conditions for optimality, yields a Two-Point Boundary Value Problem (TPBVP) that must be solved to find state and costate. Combining orthogonal polynomials expansion and ToC, we solve the TPBVP for a class of optimal guidance problems including energy-optimal landing on planetary bodies and fixed-time optimal intercept for a target-interceptor scenario. The performance analysis in terms of accuracy shows the potential of the proposed methodology as applied to optimal guidance problems.

Optimal perturbation guidance with constraints on terminal flight-path angle and angle of attack

This paper presents the design of a singular-perturbation-based optimal guidance with constraints on terminal flight-path angle and angle of attack. By modeling the flight-control system dynamics as a first-order system, the angle of attack is introduced into the performance index as a state variable. To solve the resulting high-order optimal guidance problem analytically, the posed optimal guidance problem is divided into two sub-problems by utilizing the singular perturbation method according to two time scales: range, altitude, and flight-path angle are the slow time-scale variables while the angle of attack is the fast time-scale variable. The outer solutions are the optimal control of the slow-scale subsystem. Thereafter, by applying the stretching transformation, the fast-scale subsystem establishes the relationships between the outer solutions and acceleration command. Then, the optimal command can be obtained by solving the fast-scale subsystem also using the optimal control theory. The proposed guidance can achieve a near-zero terminal acceleration as well as a small miss distance. The superior performance of the guidance is demonstrated by adequate trajectory simulations.

Practical generalized optimal guidance law with impact angle constraint

In this paper, we provide a practical solution to the generalized optimal guidance problem with an impact angle constraint. The optimal guidance problem with arbitrary weighting functions is extended to explicitly consider a missile dynamic lag effect as well as a missile velocity variation. Therefore, compared to existing results, the proposed result can prevent performance degradation due to the dynamic lag effect and the velocity variation, which is an essential issue in practice. Besides, since the proposed guidance law is formulated from the generalized optimal control framework, it can directly inherit a vital feature of the framework: providing an additional degree of freedom in shaping a guidance command for achieving a specific guidance operational goal. An illustrative example is provided in order to validate this property. In this study, the proposed solution is also compared with the existing solutions. The comparison results indicate that the proposed result is a more general and practical solution. Finally, numerical simulations are also conducted to demonstrate the practical significance of the proposed method.