High-Reliability Autonomous Management Systems for Spacecraft

By Jianjun Zhang and Jing Li

This book examines the autonomous management of spacecraft, which uses modern control technologies such as artificial intelligence to establish a remote intelligent body on the spacecraft so that the spacecraft can complete its flight tasks by itself. Its goal is to accurately perceive its own state and external environment without relying on external information injection and control, or rely on external control as little as possible, make various appropriate decisions based on this information and user tasks, and be able to autonomously control spacecraft to complete various tasks.

• Divides the autonomous management level of spacecraft into two levels: - Basic autonomy to meet spacecraft health requirements, namely, autonomous health management, and autonomy of the advanced stage.
• Divides the implementation of spacecraft autonomous management into three aspects: - Autonomous health management of spacecraft – the spacecraft can monitor and sense its own state and can autonomously detect, isolate, and recover from faults. - Autonomous mission management – the spacecraft can directly receive the mission, formulate a reasonable plan according to the current state and working environment of the spacecraft, and convert the mission into a specific sequence of instructions. - Spacecraft autonomous data management – the spacecraft processes a large amount of raw data and extracts useful information and autonomously executes or changes flight tasks.
• The autonomous management model of the spacecraft is divided into two points: - Compatibility – the existing traditional control systems belong to the execution layer logic and are compatible with the existing systems. - Scalability – it adopts a layered structure, and each layer has different autonomous capabilities.

• Language: English
• Publisher: Elsevier Science
• Release date: Aug 22, 2023
• ISBN: 9780443132827

Jianjun Zhang

Jianjun Zhang, PhD, is a Professor at the Beijing Institute of Spacecraft System Engineering, China Academy of Space Technology, Member of the Youth Science Club of China Electronics Society, Member of the Edge Computing Expert of China Electronics Society, Chairman of the "Space (Aerospace) Information Technology," Professional Committee of China Electronics Society, and Member of the Satellite Application Expert Group of China Aerospace Society. He mainly engaged in satellite navigation system design and advanced spatial information system technology based on cognitive mechanism. He has presided over several major projects such as the National Natural Science Foundation's major research project, the final assembly fund, the 863 project, and the development project of the Science and Technology Commission of the China Academy of Space Technology. He has published more than 50 SCI/EI research papers in international journals and conferences, authorized more than 20 invention patents at home and abroad, and published 3 monographs. He won third prize of the National Defense Science and Technology Progress Award.

Book preview

Preface

The autonomous management of spacecraft uses modern control technologies, such as artificial intelligence, to establish a remote network that enables the spacecraft to manage itself and complete the flight mission. Its goal is to accurately determine its own state and external environment without relying on external information injection and control or as little as possible on external control, make various appropriate decisions based on this information and user tasks, and be able to control spacecraft to complete various tasks independently.

Traditionally, the spacecraft’s mission planning and flight procedure formulation is accomplished manually on the ground. At the same time, the calibration and verification of spacecraft operation status also need to be completed through the ground system. With this idea, remote control and telemetry on the ground play an extremely important role in spacecraft management. However, the decision-making of ground control depends largely on the operation status information of each subsystem provided by the spacecraft. This has led to many problems and limitations.

1. Because the coverage area of the TT&C network is limited, the ground system often cannot obtain the TT&C information of the spacecraft in real time. Therefore the ground system cannot carry out effective real-time control according to the current situation.

2. The telemetry and telecontrol data of spacecraft are limited, and only some important information is transmitted to the ground system. This information often cannot fully reflect the operation status of satellite subsystems, and the ground system cannot complete complex fault detection and diagnosis tasks based on the information available.

3. The spacecraft depends on the remote control and telemetry data. Once the TT&C subsystem fails or the enemy interferes with the communication link, the spacecraft loses some or all of its working ability.

This book analyzes the current development trends and addresses three main problems of spacecraft autonomous management. The first is independent planning and scheduling. The autonomous operation of spacecraft should be able to directly receive mission-level tasks and formulate reasonable plans according to the current state and working environment, which can improve the flexibility of spacecraft to perform tasks and reduce the burden on the ground. The second problem is condition monitoring and fault diagnosis. Spacecraft autonomy must have long-term reliability. Therefore it is necessary to realize autonomous state monitoring and fault diagnosis, not rely on the ground to monitor the operating parameters of the spacecraft and carry out system reconstruction after failure, which is the prerequisite for long-term autonomous management of the spacecraft. The autonomous processing of payload data is another important aspect of spacecraft autonomous management. Autonomous data processing enables the spacecraft to extract useful information from a large amount of original data, reduce communication requirements, and independently change the flight mission according to the data processing situation to obtain more effective information, which is a higher level of autonomous management.

Autonomous management of spacecraft is the goal of spacecraft design and the inevitable trend of the developments in the aerospace industry.

Jianjun Zhang and Jing Li

Beijing

Part I

Introduction

Outline

1 Spacecraft self-service management connotation

2 Spacecraft systems

1

Spacecraft self-service management connotation

Abstract

The chapter analyzes the autonomous capability of spacecraft, proposes the concept of autonomous management of spacecraft, refines the connotation of autonomous management of spacecraft at three levels, and summarizes the core functions of autonomous management of spacecraft.

Keywords

Connotation; health management; task management; data management

Since the 21st century, the autonomous survivability of spacecraft has become a new research hotspot. Its level directly determines the life of spacecraft, maintenance costs, and support costs of earth stations. Major aerospace companies in the United States and Europe have researched the application of Failure Detection, Isolation, and Recovery (FDIR) technology in the integrated electronic system to improve the autonomous capability of spacecraft. Deep Space 1 and 2, launched by NASA; Smart-FDIR, led by Alcatel Alenia Space, launched by ESA; and Advanced FDIR, led by EADS, are at the forefront of technology. Artificial intelligence technology is directed toward the engineering application stage. ESA’s Dawn Goddess initiative, launched in 2004 and led by Space Systems Finland, also identified FDIR technology as one of the key research projects that could influence the success of its mission. Although related research studies are being carried out on spacecraft autonomy in various organizations worldwide, they are still in the exploratory stage, and the system’s theoretical guidance and engineering application need to be further studied.

1.1 Autonomous capability of spacecraft

Based on the research of NASA’s deep space program, Cranfield University proposed in a monograph published in 2003 that spacecraft autonomy should consist of the following six aspects:

• Spacecraft autonomous navigation and autonomous orbit control;

• Spacecraft autonomous mission scheduling and resource management;

• Intelligent task execution management;

• Fault management;

• Intelligent information data analysis;

• Architecture autonomy and intelligent software evolution.

These six aspects need a powerful integrated electronic system as the carrier and the FDIR architecture and related technology as the auxiliary to achieve.

Cranfield University also assigns four levels of autonomy to spacecraft:

1. Low Level: Ability to handle clearly defined or most spatial organizations have clearly defined closed-loop control tasks.

2. Middle Level: The ability to perform programmed spacecraft actions through prestored programmed or chronograph commands without ground assistance. Most spacecraft have this capability.

3. Higher Level: Ability to respond through event-based analysis and handle events that are not set in advance. Many of the latest generations of spacecraft have this level of autonomy. They can be sensitive to undefined hardware failures and reassemble the spacecraft to adapt to unknown hardware failures by switching it to safe mode or autonomously switching redundant hardware components [1–3].

4. True Level: This level of spacecraft handling unknown events will no longer be based on analyzing event rules, which are also difficult to define comprehensively. The processing of unknown events is based on permutation and combination of existing capabilities, derivation of AI engine, and scheduling of intelligent agents. This level of autonomy is not yet mature; still in the exploratory stage. But successful examples have emerged. For example, the solar probe on the Deep Space 1 project has achieved this level of system autonomy through the agent mechanism of intelligent AI software.

Through the Deep Space program, NASA is convinced that true spacecraft autonomy should evolve systems to support achieving spacecraft mission objectives. The most important task should be to solve the engineering application of spacecraft autonomous FDIR. Combined with the six autonomous contents of spacecraft mentioned above, spacecraft should be capable of autonomous health management, mission management, and data management. AI and other technologies, such as determinism, cause-and-effect models, and other special technologies, will play an important role in achieving the True Level of spacecraft autonomy [4–6].

1.2 The concept of spacecraft autonomous management

For a long time, the mission operation of spacecraft has been completed by manual operations. Throughout the spacecraft’s life, mission planning, execution, and response to anomalies are accomplished by remote control commands issued by the ground station at a time when it can communicate with it. It is necessary to formulate various detailed operation standards and procedures to support the traditional mission operation mode and build and equip the huge supporting infrastructure and instruments. Moreover, to ensure that the system and the payload serving it coordinate with each other to complete the mission operation, in addition to the payload manager, it also includes a large ground working group of subsystem operators. This traditional way of spacecraft mission operation is a necessary basis for developing space technology, but it is no longer suitable if it is still used. It is imperative to reform traditional mission operations and replace them with new modes of autonomous operation that significantly reduce human intervention and do not require ground intervention until the entire life of the spacecraft [2,7–11].

Spacecraft is an important part of the life cycle management. With the progress of space technology and the rising number of operating spacecraft, many common spacecraft management systems have become crucial for satellite management for a long time. To ensure the safe and stable operation of the satellite, finding faults on a timely basis and addressing them have become the focus of management. In the future, there will be many new requirements for the autonomous management of spacecraft. Autonomous management technology is significant for space activities, such as deep space exploration, unmanned guarding of low-orbit satellites, and constellation networking. Mainly reflected in:

1. For commercial tasks: Cannot interrupt the task. When failure occurs, the system should have independent judgment and switching abilities to maintain normal operation.

2. To the military task: Regardless of the primary mission to use space, support operations as the goal. Or Control space. Any advanced mission aimed at exploring the sky should make every effort to improve the autonomy of spacecraft and reduce their dependence on ground stations so that they can operate autonomously even if the ground stations are destroyed [12–17].

1.2.1 The concept of spacecraft autonomous management

Spacecraft autonomous management uses AI and other modern control technology, establishing a remote agent on the spacecraft so that the spacecraft can self-complete the flight task. Its goal is to achieve independence of external information injection and control or as little as possible dependent on external control and can accurately perceive their own state and external environment, according to this information and user tasks to make appropriate decisions, and can autonomously control the spacecraft to complete a variety of tasks.

1.2.2 The level of spacecraft autonomous management

Spacecraft autonomous management is divided into two levels: the first level of basic stage autonomy, which is to meet the basic autonomy of spacecraft health requirements, namely autonomous health management. Control attitude and execute tasks according to the instructions uploaded from the ground. Distribute power supply reasonably and maintain normal temperature during execution. Seize the opportunity to carry out the mission operation. At the same time, the probe’s health will be monitored and reported to the ground. Once a fault occurs, perform automatic fault recovery according to the fault situation, or enter the safe mode and wait for the ground command to deal with it. The second level is the autonomy of the advanced stage. Based on the basic autonomy function, autonomous task management (independent task planning and scheduling execution), autonomous data management (independent operation of payload), and stronger independent fault management functions are added. Specifically, it can receive target-based ground commands, independently plan command sequences, and execute them according to command requirements. Judge the space condition, seize the task opportunity, and implement the operation autonomously. In extremely severe cases, more failures are recovered from the top, which only go into the safe mode. Wait for the ground command. After rectifying the fault, re-evaluate the system’s capability and continue to perform tasks. In general, the spacecraft’s autonomous operation is the hope that the spacecraft can achieve a level of intelligence, to complete the perception, decision-making, and execution of three tasks.

The autonomous management system is a complex system of software and hardware interaction. At present, the complete autonomous capability is only in theoretical research. Security is the first element of an autonomous management system. A spacecraft can only carry out the work and complete the task implementation based on safety. To ensure security, no single point of failure is allowed to lead to the failure of system functions, whether software or hardware. Implement algorithm with more reliable and efficient hardware circuit. Ensure the normal operation of the power supply, measurement, and control subsystem. All data should be effectively protected and backed up when necessary. Improve the testability of the system with the idea of modular design.

1.2.3 Advantages of spacecraft autonomous management

Spacecraft autonomous management is advanced, whereas ground management carries out the traditional orbit measurement and control method. Spacecraft only have basic execution and perception abilities and lack decision-making abilities. The autonomous management of spacecraft uses intelligence, takes decisions, and can self-manage. For example, ground control engineers formulate a detailed flight instruction sequence for traditional spacecraft control according to the flight mission, spacecraft function, and operating environment, then uplink to the spacecraft. In autonomous control, the spacecraft can directly receive the user’s original flight tasks and then use its intelligent algorithms to relay a detailed flight command sequence. These sequences of instructions have the same effect as the ground engineer’s plan. Traditional spacecraft need to descend a variety of parameters, and then on the ground, according to these parameters, the state of the spacecraft is determined and faults are diagnosed. In autonomous management, the spacecraft itself can directly deal with these parameters, judge the state of the spacecraft, and take various measures to deal with various faults. It can maintain the functioning of spacecraft without the help of engineers on the ground. Conventional spacecraft take payload data and send it down to engineers on the ground for processing. In autonomous management, the spacecraft has various processing algorithms that can directly process the payload data and adjust the flight mission according to the processing results. Thus, the autonomous management of spacecraft has many advantages:

1. It can effectively reduce the cost of space missions. In the traditional spacecraft management mode, telemetry data need to be sent down to the ground receiving station through the satellite-ground transmission channel, and the ground technicians perform the status analysis. In the case of determining the occurrence of the fault, the ground control center quickly formulates the fault disposal instructions and sends them up to the spacecraft for fault treatment. The spacecraft with autonomous management ability can analyze and judge the situation of the spacecraft independently and formulate and take appropriate treatment measures to effectively reduce the participation of manual and the scale of the ground station. Table 1.1 compares the number of operators required for spacecraft missions under traditional and autonomous management modes. It can be seen from the table that autonomous management can significantly reduce the ratio of spacecraft operators [18–21].

Table 1.1

2. It can effectively improve the handling capacity and timeliness of spacecraft emergencies. Manual maintenance is difficult and costly for spacecraft operating in low and medium orbits (such as satellites, space stations, etc.), and the time window available for ground monitoring and maintenance is limited. However, for deep space detectors, the time of information exchange between ground stations and detectors is very long. At the same time, due to the shadowing of other celestial bodies, the existence of satellite-to-earth communication blind areas will also occur. For example, it took nearly an hour and 20 minutes for the DS-1 spacecraft on the Saturn mission to receive telemetry instructions from Earth. Therefore, realizing the timely response and processing of spacecraft sudden faults and events under limited manual intervention or even inability to accept ground instructions is of great importance to ensure the smooth completion of space missions, prolong their service life, and improve their