Adaptive Guidance Research Articles

Three-dimensional adaptive fixed-time cooperative guidance law with impact time and angle constraints

This paper mainly addresses the simultaneous attack of multiple missiles against a maneuvering target in three-dimensional (3-D) space. Here, we show that a novel fixed-time fast nonsingular terminal slide mode surface (FNTSMS), which has the characteristics of nonsingularity, converges in fixed time. With the help of the fixed-time FNTSMS, fixed-time adaptive distributed guidance laws along and perpendicular to the line of sight (LOS) direction are proposed. This realizes the dynamic adjustment of the target parameters in guidance laws, reduces the energy consumption of the guidance process, and realizes the constraints of the impact time and angle simultaneously. Additionally, considering that the communication topology will cause topology switching failure, this paper proves through graph theory that the proposed adaptive guidance laws will not be affected by topology switching. Moreover, through relevant auxiliary transformations, guidance laws with control input delay are demonstrated. To close to the actual action process of the missile, the air resistance item is added to guidance laws and analyzed. In addition, the control input amplitude is restricted to meet the actual working conditions of the missile. Finally, simulations are conducted to demonstrate the performance of the guidance law and its robustness against the mutation of communication topology.

Adaptive entry guidance for the Tianwen-1 mission

To meet the requirements of the Tianwen-1 mission, adaptive entry guidance for entry vehicles, with low lift-to-drag ratios, limited control authority, and large initial state bias, was presented. Typically, the entry guidance law is divided into four distinct phases: trim angle-of-attack phase, range control phase, heading alignment phase, and trim-wing deployment phase. In the range control phase, the predictor—corrector guidance algorithm is improved by planning an on-board trajectory based on the Mars Science Laboratory (MSL) entry guidance algorithm. The nominal trajectory was designed and described using a combination of the downrange value and other states, such as drag acceleration and altitude rate. For a large initial state bias, the nominal downrange value was modified onboard by weighing the landing accuracy, control authority, and parachute deployment altitude. The biggest advantage of this approach is that it allows the successful correction of altitude errors and the avoidance of control saturation. An overview of the optimal trajectory design process, including a discussion of the design of the initial flight path angle, relevant event trigger, and transition conditions between the four phases, was also presented. Finally, telemetry data analysis and post-flight assessment results were used to illustrate the adaptive guidance law, create good conditions for subsequent parachute reduction and power reduction processes, and gauge the success of the mission.

AI-Induced guidance: Preserving the optimal Zone of Proximal Development

Holding the promise of higher learning outcomes, discovery learning utilizes intrinsic motivation to provide an enjoyable self-directed learning experience. Unfortunately, this approach can also lead to a sub-optimal cognitive load, which hinders learning. To avoid this, players must be in the optimal Zone of Proximal Development (ZPD). A way of accomplishing this is to make use of Artificial Intelligence in a narrative-centered discovery game using adaptive guidance. Textual instructions were automatically adapted in real-time to ensure a personalized challenge for one group of learners, where a control group received static instructions. Compared to the control group, the learners with personalized instructions showed higher story and spatial learning, while having decreased cognitive load and a similar learning experience. So, instructions given to self-directed learners can be personalized in real-time, which not only reduces learners’ cognitive load but also leads to enhanced learning outcomes without affecting the learning experience.

Multi-Agent for Adaptive Guidance of Unknown Targets

Multi-Agent for Adaptive Guidance of Unknown Targets

Multivariable Adaptive Super-Twisting Guidance Law Based on Barrier Function

For tactical missiles, sliding mode control and super-twisting algorithms have been widely studied in the area of guidance law design. However, these methods require the information of the target accelerations and the target acceleration derivatives, which is always unknown in practice. In addition, guidance laws utilizing these tools always have chattering phenomena and large acceleration commands. To solve these problems, this article introduces a barrier function based super twisting controller and expands the controller to a multivariable adaptive form. Consequently, a multivariable adaptive super-twisting guidance law based on barrier function is proposed. Moreover, the stability of the guidance law is analyzed, and the effectiveness and the robustness are demonstrated by three simulation examples. Compared with previous guidance laws using sliding mode control or super-twisting algorithm, the one proposed in this paper does not require the information of target accelerations, nor target acceleration derivatives; it has smaller super-twisting gains so that has smaller acceleration commands; it can increase and decrease the gains to follow the target accelerations and maintain the sliding mode, and it does not chatter.

Research on Building DSM Fusion Method Based on Adaptive Spline and Target Characteristic Guidance

In order to adapt to the actual scene of a stereo satellite observing the same area sequentially and improve the accuracy of the target-oriented 3D reconstruction, this paper proposed a building DSM fusion update method based on adaptive splines and target characteristic guidance. This method analyzed the target characteristics of surface building targets to explore their intrinsic geometric structure information, established a nonlinear fusion method guided by the target characteristics to achieve the effective fusion of multiple DSMs on the basis of maintaining the target structural characteristics, and supported the online updating of DSM to ensure the needs of practical engineering applications. This paper presented a DSM fusion method for surface building targets and finally conducted DSM fusion experiments using typical urban area images of different scenes. The experimental results showed that the proposed method can effectively constrain and improve the DSM of buildings, and the integrity of the overall construction of the target 3D model structure was significantly improved, indicating that this paper provides an effective and efficient DSM constraint method for buildings.

Computer-based guidance to support students’ revision of their science explanations

As they encounter new ideas, students need to make integrated revisions to their science explanations, a key aspect of science learning. This involves filling gaps, resolving inconsistencies with evidence, and strengthening connections among ideas. Rather than making integrated revisions, even after automated, adaptive guidance, students typically add disconnected ideas or fix mechanical errors. The knowledge integration framework, supported by new technologies including natural language processing, guided the design of the Annotator, a tool that models the revision process for students’ written explanations. This research investigates the added value of the Annotator compared to automated, adaptive guidance to support students to make integrated revisions to their science explanations and to strengthen knowledge integration. 798 6th and 7th-grade students from 4 schools participated in a study featuring pretests, posttests, embedded student explanations, student interviews and observations. Students using the Annotator who initially displayed unintegrated ideas were more likely to make integrated revisions to their explanations, than students receiving automated, adaptive guidance. These students also made greater knowledge integration revisions on the posttest one week later. Thus, modeling revision with the Annotator strengthened the ability of students who started with unintegrated ideas to explain scientific phenomena.

Effect of Adaptive Guidance and Visualization Literacy on Gaze Attentive Behaviors and Sequential Patterns on Magazine-Style Narrative Visualizations

We study the effectiveness of adaptive interventions at helping users process textual documents with embedded visualizations, a form of multimodal documents known as Magazine-Style Narrative Visualizations (MSNVs). The interventions are meant to dynamically highlight in the visualization the datapoints that are described in the textual sentence currently being read by the user, as captured by eye-tracking. These interventions were previously evaluated in two user studies that involved 98 participants reading excerpts of real-world MSNVs during a 1-hour session. Participants’ outcomes included their subjective feedback about the guidance, and well as their reading time and score on a set of comprehension questions. Results showed that the interventions can increase comprehension of the MSNV excerpts for users with lower levels of a cognitive skill known as visualization literacy. In this article, we aim to further investigate this result by leveraging eye-tracking to analyze in depth how the participants processed the interventions depending on their levels of visualization literacy. We first analyzed summative gaze metrics that capture how users process and integrate the key components of the narrative visualizations. Second, we mined the salient patterns in the users’ scanpaths to contextualize how users sequentially process these components. Results indicate that the interventions succeed in guiding attention to salient components of the narrative visualizations, especially by generating more transitions between key components of the visualization (i.e., datapoints, labels, and legend), as well as between the two modalities (text and visualization). We also show that the interventions help users with lower levels of visualization literacy to better map datapoints to the legend, which likely contributed to their improved comprehension of the documents. These findings shed light on how adaptive interventions help users with different levels of visualization literacy, informing the design of personalized narrative visualizations.

Fixed-Time Disturbance Observer-Based Adaptive Finite-Time Guidance Law Design considering Impact Angle Constraint and Autopilot Dynamics

This paper aims to establish an effective guidance law to accomplish the interception guidance mission for a missile intercepting a target with impact angle constraint and autopilot dynamics. To achieve this purpose, a fixed-time disturbance observer-based adaptive finite-time guidance law is presented. First, a fixed-time disturbance observer (FTDO) is designed to guarantee the fast estimation of the lumped disturbance caused by the target maneuver. Then, the FTDO-based adaptive integral sliding mode backstepping (AISMB) guidance law is constructed for the interception guidance problem. Besides, several adaptive laws are established to estimate the derivative of virtual control inputs, making the “differential explosion problem” of conventional backstepping get avoided. The finite-time convergence characteristic of the closed-loop system is analyzed by utilizing the Lyapunov stability theory. Finally, the simulation examples are conducted to demonstrate the effectiveness of the proposed composite guidance law.

Adaptive torque equilibrium attitude guidance for rapid deorbit of space debris by aerodynamic drag considering model uncertainty

Currently, considerable research is directed toward active debris removal (ADR) in space, especially by small, cost-effective satellites. However, a drawback to effective ADR missions has been that they use thrusters to move from a high altitude for reentry, which consumes a great deal of fuel. Thus, the propulsion system for these satellites is quite large, so designing the propulsion system for a small satellite is quite difficult. This paper proposes a new guidance design based on the altitude-dependent mean torque equilibrium attitude (TEA) and centered on determining the equilibrium point in a satellite’s attitude dynamics with respect to aerodynamic and gravity gradient torques. To correct guidance errors, the adaptive TEA guidance technique learns the actuator inputs during one orbital revolution. The controller is designed to guarantee robustness against disturbances and modeling uncertainties. Finally, the proposed adaptive guidance system and the robust controller’s effectiveness are demonstrated through numerical simulations to enhance the feasibility of an ADR mission.

Measurement Compensation for Time-Delay Seeker and Three-Dimensional Adaptive Guidance Law Design.

The time delay of seekers has grown to be a serious issue for tactical missile guidance with the development of flight vehicle technologies. To address the problem, a measurement compensation system for the seeker, with lags and delays based on predictive active disturbance rejection control, is proposed. In addition, to eliminate the effects of target maneuvers to the tactical missile guidance, an adaptive finite-time convergent sliding mode guidance law, based on super-twisting algorithm, is proposed in three-dimensional missile-target engagement kinematics. Specifically, the compensation system consists of a predictive tracking structure and an active disturbance rejection control system, which could follow a virtual measurement without lags and delays. The compensation system has advantages in disturbance rejection and model inaccuracy addressing, compared with existing compensation methods for seeker measurement. As for the sliding mode guidance law design, the proposed approach is based on an improved super-twisting algorithm with fast convergent adaptive gains, which has advantages in addressing unknown but bounded target maneuvers and avoiding chattering of the classical sliding mode control. As a result, the measurement compensation system and the adaptive sliding mode guidance law is verified robust and effective under the proposed constraints by the simulation examples.

Co-evolutionary Multi-Colony Ant Colony Optimization Based on Adaptive Guidance Mechanism and Its Application

Co-evolutionary Multi-Colony Ant Colony Optimization Based on Adaptive Guidance Mechanism and Its Application

CellEVAC: An adaptive guidance system for crowd evacuation through behavioral optimization

A critical aspect of crowds’ evacuation processes is the dynamism of individual decision making. Identifying optimal strategies at an individual level may improve both evacuation time and safety, which is essential for developing efficient evacuation systems. Here, we investigate how to favor a coordinated group dynamic through optimal exit-choice instructions using behavioral strategy optimization. We propose and evaluate an adaptive guidance system (Cell-based Crowd Evacuation, CellEVAC) that dynamically allocates colors to cells in a cell-based pedestrian positioning infrastructure, to provide efficient exit-choice indications. The operational module of CellEVAC implements an optimized discrete-choice model that integrates the influential factors that would make evacuees adapt their exit choice. To optimize the model, we used a simulation–optimization modeling framework that integrates microscopic pedestrian simulation based on the classical Social Force Model. In the majority of studies, the objective has been to optimize evacuation time. In contrast, we paid particular attention to safety by using Pedestrian Fundamental Diagrams that model the dynamics of the exit gates. CellEVAC has been tested in a simulated real scenario (Madrid Arena) under different external pedestrian flow patterns that simulate complex pedestrian interactions. Results showed that CellEVAC outperforms evacuation processes in which the system is not used, with an exponential improvement as interactions become complex. We compared our system with an existing approach based on Cartesian Genetic Programming. Our system exhibited a better overall performance in terms of safety, evacuation time, and the number of revisions of exit-choice decisions. Further analyses also revealed that Cartesian Genetic Programming generates less natural pedestrian reactions and movements than CellEVAC. The fact that the decision logic module is built upon a behavioral model seems to favor a more natural and effective response. We also found that our proposal has a positive influence on evacuations even for a low compliance rate (40%).

Multi-agent cooperative multi-model adaptive guidance law

ABSTRACTA multi-agent engagement scenario is considered in which a high-value aircraft launches two defenders to intercept two homing missiles aimed at the aircraft. Under the assumption that all aircrafts have first-order linear dynamic characteristics, a combined multiple-mode adaptive estimation (MMAE) and a two-way cooperative optimal guidance law are proposed for the target–defenders team. Considering the full cooperation of the target and both the two defenders, the two-way cooperative strategies provide the analytical expressions for their optimal control input, enabling the target–defenders team to intercept the missiles with minimal control effort. To successfully intercept the missiles, MMAE is used to identify the guidance laws adopted by the missiles and estimate their states. The simulation results show that the target cooperating with the defenders to perform lure manoeuvres for the missiles can improve the guidance performance of the defenders as well as reduce the control effort of the defenders for intercepting the missiles.

Collaborative learning in mathematics classrooms: Can teachers understand progress of concurrent collaborating groups?

Dashboards have been hypothesized to facilitate adaptive guidance in classrooms. Thus far, however, empirical studies in this domain are badly missing. We present a dashboard, which enables teachers to observe concurrent groups as they engage in mathematical tasks using Dynamic Geometry tools and to guide groups when their intervention is needed. We rely on a case study with this dashboard in which a single teacher could successfully orchestrate the progression of several groups working on difficult problems in geometry, when being sent realtime alerts about critical moments, moments whose occurrence may impinge on further co-construction of knowledge. In the present study, we chose six 20-min long demo videos of small groups in a variety of sessions of unguided group work, where each video describes the work of one of six small groups (dyads or triads) dealing simultaneously with identical set tasks. Two versions of this demo were prepared, one with alerts of critical moments generated according to predefined rules, and the other without alerts. The teachers observing concurrent groups and being updated about critical moments (N1 = 21) better understand progression in groups than teachers that are not informed about these critical moments (N2 = 18). In a second study we found that the dispatching of alerts impinges on the ways the teachers navigate across rooms. In particular, they pay attention to certain alerts and at the same time, focus on learning processes in mathematics. We conclude that such tools may help bringing collaborative settings more often in classrooms.

Hybrid Guardian Map-based adaptive control of spacecraft formation flying on highly elliptical orbits in the restricted three-body problem

In this paper, a single parameter Guardian Map-based simple adaptive guidance and control architecture for spacecraft formation flying is developed. When compared with traditional vehicles, the dynamics of spacecraft features larger non-linearities, tighter coupling and higher uncertainty as the eccentricity of an orbit increases. In addition, most formation flying applications involve following bounded relative trajectories that are only applicable to circular orbits and hence becomes an unnatural trajectory when used on eccentric orbits, resulting in unnecessary fuel consumption. Making use of a combination of nonlinear Simple Adaptive Control and Guardian Map theories, a novel autonomous adaptive guidance and control system is developed such that the desired closed-loop stability of the system and asymptotic convergence is guaranteed throughout the orbit while tracking fuel-efficient natural trajectories that are applicable to eccentric orbits. Simulation results show various new types and sizes of bounded natural relative orbits to illustrate the increased performance and robustness of the proposed adaptive controller compared to a conventional non-adaptive linear quadratic regulator found in literature.

Cooperative Intercepting Guidance Law for Large Maneuvering Target with Impact Angle Constraint

A distributed multi-missile cooperative guidance law based on the finite time theory is proposed to solve the terminal guidance problem of three-dimensional multi-missiles cooperative interception of large maneuvering target. According to the finite time consistency theory, an adaptive guidance law based on the integral sliding mode is designed to ensure that all missiles can reach the target at the same time in the terminal guidance process. The longitudinal and lateral acceleration of the line of sight are based on the guidance law of the fast terminal sliding mode surface. The terminal attack angle is constrained, so that the terminal attack Angle can reach the expected value in finite time. The simulation results show that the designed guidance law can achieve the cooperative attack on the maneuvering targets.

Adaptive Entry Guidance for Hypersonic Gliding Vehicles Using Analytic Feedback Control

This paper presents an adaptive, simple, and effective guidance approach for hypersonic entry vehicles with high lift-to-drag (L/D) ratios (e.g., hypersonic gliding vehicles). The core of the constrained guidance approach is a closed-form, easily obtained, and computationally efficient feedback control law that yields the analytic bank command based on the well-known quasi-equilibrium glide condition (QEGC). The magnitude of the bank angle command consists of two parts, i.e., the baseline part and the augmented part, which are calculated analytically and successively. The baseline command is derived from the analytic relation between the range-to-go and the velocity to guarantee the range requirement. Then, the bank angle is augmented with the predictive altitude-rate feedback compensations that are represented by an analytic set of flight path angle needed for the terminal constraints. The inequality path constraints in the velocity-altitude space are translated into the velocity-dependent bounds for the magnitude of the bank angle based on the QEGC. The sign of the bank command is also analytically determined using an automated bank-reversal logic based on the dynamic adjustment criteria. Finally, a feasible three-degree-of-freedom (3DOF) entry flight trajectory is simultaneously generated by integrating with the real-time updated command. Because no iterations and no or few off-line parameter adjustments are required using almost all analytic processing, the algorithm provides remarkable simplicity, rapidity, and adaptability. A considerable range of entry flights using the vehicle data of the CAV-H is tested. Simulation results demonstrate the effectiveness and performance of the presented approach.

Fast fixed-time convergent smooth adaptive guidance law with terminal angle constraint for interception of maneuvering targets

This paper introduces a fast fixed-time guidance law with terminal angle constraint for interception of maneuvering targets, which is based on the structure of singularity-free fast terminal sliding mode and the fixed-time stability theory. Different from the finite-time stability, the fixed-time stability can predefine the maximum stabilization time of system states which is independent on the initial value of system states. Under the proposed guidance law, the guidance system can achieve stabilization within settling time which decides by the parameters of controller. In addition, an adaptive law is proposed which alleviate the chattering of sliding mode and smooths the guidance law. Meanwhile, the proof of the sliding mode manifold and system states fixed-time convergence is given by Lyapunov stability theory. Finally, numerical simulations demonstrate the performance of the proposed guidance law is satisfying.

Developing a Model of Increasing the Learners’ Bilingual Professional Capacity in the Virtual Laboratory Environment

The article considers industrial applications of digital twins and their contribution to decision-making and prevention of failures in manufacturing. Virtual laboratories are described as an example of using digital twins not only in industry but also for educational purposes. The article is also focused on the value of physical and virtual investigations through the prism of content and language integrated learning approach (CLIL) and it offers recommendations for combining the two to strengthen science inquiry learning and job-relevant learning. Students conduct online investigations resulting in interdisciplinary team interaction and knowledge integration. Adopting the CLIL approach changes engineering students’ attitudes to learning a foreign language, drums up their academic interest, and strengthens their motivation. In addition, the article describes how neural networks are applied for the simulation of physical processes in a virtual laboratory. The advantages of using virtual laboratories for professional-oriented training include linking observable and unobservable phenomena, pointing out essential information, and providing online, adaptive guidance. To evaluate the efficiency of the virtual laboratory environment, we conducted an experiment to assess the effectiveness of an integrated learning course with the elements of a virtual laboratory. The sample was 48 students (23 of them were enrolled on the course based on integrated learning with elements of virtual environment; 25 students studied professional discipline and professional English separately). To collect the data two online testing on English were conducted. The professional discipline was evaluated once at the end of the semester. In addition, we conducted an online survey on motivation for students of both groups to reveal the influence of educational process organization on this indicator. The results of the experiment allowed us to ascertain that the CLIL approach in the virtual laboratory environment resulted in better outcomes and helped the students adopt a more positive attitude to learning English.