Subsystem Optimization Research Articles

SUBSTITUTION OF OPTIMIZATION CRITERIA FOR UAV INFORMATION PROCESSING SYSTEMS TAKING INTO ACCOUNT INFORMATION CHARACTERISTICS OF OUTPUT INFORMATION

The use of UAVs with combined navigation systems during the repulsion of large-scale armed aggression of the Russian Federation was analyzed. The models of description of information features for correlation-extreme navigation systems were analyzed. The characteristics of different types of objects and backgrounds of the sighting surface were determined. The general principles that determine the description of the sighting surface of any type were formulated. It was shown that current images formed using informative features should be described using the same indicator. An approach to describing the sighting surface through brightness was developed, separately for each channel of correlation-extreme navigation systems, which are formed by information sensors. Analytical expressions for the current image in each information sensor of correlation-extreme navigation systems are given. The results of numerical modeling of brightness and contrast distributions for a randomly selected section of the sighting surface are given. The results of numerical modeling of correlation analysis fields of brightness, contrast and fractal dimension for selected objects on the viewing surface are presented. The results of numerical modeling were analyzed and conclusions were drawn on its basis regarding the dependence of information features on changes in UAV navigation parameters and the influence of obstacles. The dependence of information features on changes in UAV navigation parameters and interference effects is confirmed. This means that the formation of a set of reference images taking into account the navigation and angular parameters of the UAV orientation and the influence of interference is possible in accordance with the selected information features. But minimizing the number of fragments of reference images in the set requires determining the degree of coincidence of the compared images, which necessitates solving the problem of determining this indicator and its thresholds, the use of which will ensure the formation of a unimodal decision function, or a decision function with several maxima, the use of which in further processing will ensure the determination of the global maximum of the decision function. The results obtained can be used for further development and optimization of subsystems for detecting and processing information and forming UAV control signals in difficult interference conditions. They can be useful for creating new approaches to increasing the accuracy and probability of location of modern and promising air attack means produced by the state.

RELIABILITY ANALYSIS OF SWITCH’S CONTROL SCHEMES

Purpose. The purpose of this article is to conduct an analysis of the reliability of the control schemes of the electric arrow drive with the aim of optimizing and modernizing them to increase the reliability indicators. To show an approach to optimizing the control circuits of an electric turnout that is advantageous from an operational point of view, the implementation of fewer control circuits will minimize the number of failures. To demonstrate a principled circuit solution for optimizing the control circuit of an electric turner with the use of separate redundancy with always-on redundancy and integer multiplicity. Methods. During the research, methods of comparative analysis, synthesis, probability theory, and reliability theory were used. Findings. The paper analyzes the types of re-reservation as a way to increase the reliability of the arrow control scheme. A comparative study of the reliability of various options for reserving the turnout control scheme was carried out in comparison with the classic situation on the railways of Ukraine - the absence of a reserve. It has been proven that the use of separate redundancy with always-on reserve and integer multiplicity provides the maximum increase in reliability, but the significant amount of necessary equipment significantly reduces the economic attractiveness of this method. On the other hand, the use of separate redundancy with substitution and fractional multiplicity (sliding redundancy) gives a positive result only if one redundancy unit serves no more than 15 turnout electric drives, otherwise the overall reliability of the subsystem may decrease. The optimization of the arrow control subsystem at the station is proposed, which requires the use of only six arrow control schemes, one of which is a sliding reserve. The influence of different types of redundancy on the reliability indicators of the arrow control scheme is considered. The most effective option for optimizing the arrow control subsystem has been determined. Scientific novelty. The scientific novelty of the work consists in the well-founded sufficiency of using only six arrow control schemes in combination with the use of sliding redundancy of the arrow control scheme for the control of arrows when disbanding warehouses on the sorting slide. The proposed method makes it possible to increase the reliability of the arrow control subsystem while maintaining the operational parameters of the station. Practical significance. The practical significance of the results lies in the fact that when using the proposed optimization, the resource use of hill automation devices is improved, the maintenance process is simplified, and the total cost of equipment and maintenance costs are reduced.

A reliable spacecraft power supply subsystem based on discrete water cycle multi-objective optimization

The successful execution of spacecraft missions relies heavily on the performance and reliability of their power supply subsystems. Achieving optimal component size and configuration is crucial for efficient power generation, distribution, and storage. Designing an efficient power supply subsystem for spacecraft missions is a complex and multi-objective optimization problem. Traditional optimization techniques, such as genetic algorithm and particle swarm optimization, have been employed, but their limitations in handling discrete variables and achieving global optima necessitate the exploration of alternative methods. In this context, this research paper explores the application of discrete water cycle algorithm (DWCA) optimization as a novel approach for optimizing the component size and configuration of spacecraft power supply subsystems. By emulating the dynamic flow and distribution of water, DWCA seeks to efficiently explore the design space and identify optimal solutions.Through comprehensive experimentation and comparative analysis, this research demonstrates that the proposed DWCA outperforms/surpasses other traditional optimization techniques in optimizing component size and configuration for spacecraft power supply subsystems. It consistently determines designs that are more efficient in power generation and storage. Moreover, DWCA enhances the efficiency and reliability of spacecraft power supply systems, especially in mission-critical scenarios. The successful optimization of spacecraft power supply subsystems is paramount to the overall success of space missions. Therefore, this advancement contributes significantly to the ongoing efforts to ensure the success of future space missions.

The Impacts of Water Ecological Carrying Capacity on Green Total Factor Productivity: The Case of Chemical Industry in Jiangsu, China

The chemical industry is not only a crucial sector of national economy, but also a significant consumer of water resources and a major initiator of water pollution. The sustainable development of this sector is intricately linked to the regional water ecological carrying capacity (WECC). Based on SBM-DEA and Global Moran’s I, the green total factor productivity (GTFP) and spatial correlation characteristics of the chemical industry in 13 cities within China’s chemical agglomeration region in Jiangsu Province were estimated from 2015 to 2019. By combining the WECC results, the Tobit model was employed to reveal the driving factors of WECC in optimizing GTFP. The results indicated that the regional WECC in southern Jiangsu was increasing compared with that in northern Jiangsu, which promoted the growth of GTFP. WECC has been a positive radiation-driven effect since 2017, and the optimization of the various subsystems of WECC has had a different impact on GTFP. For the sustainable development of Jiangsu’s chemical industry, effective water resource policies should be formulated by the government, while enterprises need to pursue sustained structural adjustments.

Experimental study of compact room temperature magnetic cooling system based on different flow time ratios

Magnetic refrigeration has become a promising new technology to replace conventional vapor-compression refrigeration technology, for it has excellent application characteristics such as the high efficiency, environmental friendliness and structural simplicity. Many studies have been carried out to analyze the various subsystems, but the interaction laws between the systems are not yet clear, and the optimization of each subsystem is still an area of research worth exploring. This work is based on a compact room temperature magnetic refrigeration system developed before, and carries out experimental research on the different flow time ratio to explore the correlation among refrigeration temperature span, cooling capacity, pressure drop, coefficient of performance (COP) and blow fraction under a fixed magnetic field timing. Especially, the effects of different flow time ratios (100%, 80%, 60%) on the system performance are studied under magnetic field timing of 1∶4∶1∶4 and a frequency of 0.45 Hz. The experimental results reveal that a low utilization factor combined with a high flow time ratio can achieve a greater temperature spread, whereas a high utilization factor combined with a high flow time ratio can accomplish a bigger cooling capacity. When the utilization factor is 0.42 and the flow time ratio is 100%, the maximum unloaded cooling temperature span is 26.2 K. Meanwhile, the effects of the utilization factor and flow time ratio on the pressure drop and COP of the regenerator are studied in detail. It is discovered that raising the flow time ratio and reducing the utilization factor both result in a fall in fluid velocity, which leads the pressure to further decrease and the COP to rise. In a word, this research investigates the relationship among cooling temperature span, cooling capacity, pressure drop, COP, and flow time ratio in a fixed magnetic field timing, thus providing the groundwork for future improving the performances of room temperature magnetic refrigeration systems.

A Multicriteria Evaluation and Cascaded Optimization Framework for Integrated Energy System of Steel Industry

Integrated Energy System (IES) involving coal, by-product gas, power, etc., plays a pivotal role in steel industry, which greatly requires reasonable utilization scheme for avoiding extensive energy consumption and intensive environment pollution. While due to the complex coupling relationship among the multiple energy and the contradiction existed between the optimization of global IES and local sub-system, an effective solution for this important practical problem is still highly required in real-world application. As such, a multi-criteria evaluation and cascaded optimization framework is proposed in this study. In order to make a comprehensive evaluation, criteria including global energy consumption and local gas emission are respectively evaluated from the perspective of both the entire IES and the by-product gas subsystem. Then, a cascaded optimization model is accordingly established, where a Reinforcement Learning based cascaded algorithm is also designed for efficiently and effectively acquiring an optimal trade-off as the final solution. The following experiments carried out on practical industrial data clearly demonstrated that the proposed framework gives scientifically reasonable as well as practically available energy utilization scheme, which is beneficial for energy-saving and emission reduction in practical application.

Cost and size optimization of hybrid solar and hydrogen subsystem using HomerPro software

Hybrid Renewable Energy Systems have been considered as a suitable way to supply electricity. The hybrid energy (Solar-Wind-Storage-hydrogen-diesel) is increasingly used in various applications, especially at isolated sites. This study proposes the optimization and analysis of a stand-alone photovoltaic/battery/fuel cell/electrolyzer/hydrogen hybrid system (HS) to find out the optimal sizes and costs. In the first step, SAM software was used to estimate the global solar irradiance (GHI) for the studied area and to select the best PV, battery and fuel cell components. MATLAB software was handled to predict the power output of the renewable source (PV system) using an Artificial Neural Network (ANN) model. Then, simulation, optimization and techno-economic analysis were carried out in the second step with HomerPro software. Four proposed configurations are optimized in this work and different comparisons have been made regarding the found results. The results of the cost optimization were found to be 50861.21 $ and 0.95657 $ for NCP and COE, respectively. Moreover, the same HS configurations are simulated and optimized under Moroccan climate.

Coordinated restoration optimization of power-gas integrated energy system with mobile emergency sources

In an integrated energy system (IES) composed of multiple subsystems, energy coupling causes an energy supply blockage or shutdown in one subsystem, thereby affecting the energy flow distribution optimization of other subsystems. The energy supply should be globally optimized during the IES energy supply restoration process to produce the highest restoration net income. Mobile emergency sources can be quickly and flexibly connected to supply energy after an energy outage to ensure a reliable supply to the system, which adds complexity to the decision. This study focuses on a power- gas IES with mobile emergency sources and analyzes the coupling relationship between the gas distribution system and the power distribution system in terms of sources, networks, and loads, and the influence of mobile emergency source transportation. The influence of the transient process caused by the restoration operation of the gas distribution system on the power distribution system is also discussed. An optimization model for power-gas IES restoration was established with the objective of maximizing the net income. The coordinated restoration optimization decision-making process was also built to realize the decoupling iteration of the power-gas IES, including system status recognition, mobile emergency source dispatching optimization, gas-to-power gas flow optimization, and parallel intra-partition restoration scheme optimization for both the power and gas distribution systems. A simulation test power-gas IES consisting of an 81-node medium-voltage power distribution network, an 89-node medium-pressure gas distribution network, and four mobile emergency sources was constructed. The simulation analysis verified the efficiency of the proposed coordinated restoration optimization method.

Evaluation of Water-Energy-Food-Ecology System Development in Beijing-Tianjin-Hebei Region from a Symbiotic Perspective and Analysis of Influencing Factors

Rapid economic and social development has created significant ecological and resource problems in the Beijing-Tianjin-Hebei (BTH) region, making it necessary to identify ways of implementing sustainable regional development. The interactions between water, energy, food, and ecology are characterized by a high degree of relevance and complexity. In studying the relationships between the four systems in depth and choosing representative indicators for each system, a comprehensive development model of the water-energy-food-ecology (WEFE) system in the BTH region has been established. The coupling coordination degree model was used to analyze the coupling synergy relationship between the WEFE systems in the BTH region from 2001 to 2020. The primary contributing elements determining the development of linked synergy in the WEFE system were investigated using a gray correlation model. According to the findings, Beijing’s total coupling coordination development level shows a gradual upward trend and is in excellent coordination; Hebei has progressed the most, experiencing a significant change from little coordination to good coordination; and Tianjin has had the least improvement, only improving from basic to good coordination. The exploitation of water resources and ecological protection of the environment are the aspects that have the greatest impact on the WEFE system. Additionally, the linked and synergistic growth of the WEFE system in the BTH region is significantly influenced by economic, social, and technological advancements in the industrial and agricultural sectors. The coupling coordination development of regional WEFE systems, which takes into consideration the synergistic optimization of many subsystems, is provided by this study as a scientific foundation.

Design and optimization of complex mechanism flip shaping subsystem based on genetic algorithm and rigid-flexible coupled dynamic model.

In this paper, the cam connecting rod system of the high-speed group vertical machine flipping shaping mechanism is the research object. In order to solve the key problem that the flipping shaping mechanism cannot accurately complete the action when the vibration of the mechanism is large. In this paper, the finite element method is used to construct the dynamic model of the connecting rod subsystem of the flipped shaping mechanism. And The dynamic model of cam roller subsystem is established by centralized parameter method. Based on the MATLAB Genetic Algorithm toolbox and using Newmark's method, the dynamic equations of the flipped plastic mechanism system are solved. The optimal parameters of the connecting rod of the mechanism, the cam profile curve and the swing power and swing torque of the mechanism at different speeds are analyzed. The results show that the speed and convex contour line are important factors affecting the performance of the mechanism. And the pendulum force (swing torque) is the main cause of the vibration of the mechanism on the frame. Therefore, the mechanism pendulum dynamic and the swing moment are selected as the objective functions of the optimization model. By selecting the node parameters of the sixth order spline motion law and the cross-section parameters of the connecting rod as the design variables. The cam linkage system is optimally designed to obtain the optimal value. Finally, the optimal design of the flipped shaping mechanism was analyzed and compared with the original mechanism.

Optimized Chassis Stability Relative to Dynamic Terrain Profiles in a Self-Propelled Sprayer Multibody Dynamics Model

Highlights This study presented a new optimization methodology using a prismatic joint with high stiffness and damping. The virtual suspension model contained the main bodies, an optimization subsystem, and a free-floating cylinder. Under aggressive terrain, an optimized chassis platform resulted in a 19.5% increase in boom height stability. Abstract. Multibody dynamics (MBD) models are continuing to be valuable for engineering design and product development, especially regarding subsystem optimization. Most MBD optimization processes begin with a sensitivity analysis of treatment factors and levels to understand how uncertainty in model inputs can be attributed to different sources of uncertainty within model outputs; however, this study developed a new MBD methodology to automatically determine the optimized dynamic chassis suspension responses on each corner of the vehicle from a single simulation for a self-propelled sprayer model as the chosen application use-case. This technique leveraged a prismatic joint (with a high spring stiffness and damping coefficient) connected between the chassis mainframe and the simplified optimization tire to create a distance constraint that held the chassis body at a near-consistent height above the ground. Then the solver optimized the response of the chassis suspension system to maintain a stable chassis platform relative to the terrain beneath it as the vehicle traversed across dynamic terrain conditions. This optimization response was also accomplished by replacing the baseline chassis suspension components with a free-floating cylinder, which permitted the unrestricted, optimized motion needed to keep the chassis body at a near-level position with respect to the roll and pitch profiles of the terrain. For a simulation with an aggressive terrain configuration, the analysis showed that an optimized suspension system resulted in a 46% decrease in operator comfort and a 19.5% increase in overall boom height stability as the boom height control system better maintained a dynamic position closer to the specified target height. Keywords: Boom height, Chassis suspension, Multibody dynamics (MBD), Optimization, Prismatic joint, Simulation, Terrain.

A systems approach to a resilience assessment for agility

This work proposes a theoretical approach to assessing agility in terms of a modified version of resilience during large-scale crisis to sustain operational reliability. The proposed method could be used on subsystem optimization or eventually scaled up to global interconnectedness enabling decision makers to optimize resource allocation and so obtain resilience and agility in troubling times along with long-term sustained prosperity. Introducing weights to various parameters can also allow customizing outcomes such as insuring equitable outcomes, environmental stewardship and proper response to emergencies or any national crisis. The provided mathematical formalism can then become a decision maker tool to predict corrective action outcomes from various responses to a crisis or alternatively to determine sensitivity and potential risk for a crisis from apparently ambient or slowly changing conditions. Ad-hoc examples are considered to demonstrate the generality of the approach.

Machine learning utilized for the development of proton exchange membrane electrolyzers

Proton exchange membrane water electrolyzers (PEMWEs) have great potential as energy conversion devices for storing renewable electricity into hydrogen energy. However, their cost and efficiency are still unable to support large-scale commercialization. In PEMWEs, multiple processes at different scales are simultaneously involved: electrochemical reactions at the microscale, reactant transportation at the mesoscale, and thermoelectric-electrical coupling fields at the macroscale. Therefore, the system is so complex that previous studies could only focus on the optimization of different subsystems of PEMWEs and merely investigate limited variables separately: electrocatalysts, membrane electrode assemblies (MEAs), single cells, stacks, etc. Therefore, the contributions of traditional research have been limited, and the trial-and-error method adopted to drive the experimental or theoretical studies is inefficient. Reports of applying machine learning (ML) to accelerate the research and development of key materials in PEMWEs have gradually emerged in recent years. The application of ML can greatly accelerate the optimization of different key materials and components in PEMWEs, significantly reducing unacceptably high costs. Therefore, this paper reviews recent applications of ML for material and component optimization in PEMWEs. Moreover, we provide a phased summary and prospects for the future of this emerging field.

Mean Value-Based Parallel Collaborative Optimization Method for Modular Aircraft Structural Layout

The conventional structural layout optimization method is usually used to solve the layout optimization problem of a single structure, but it is difficult to apply to the layout optimization problem of the modular aircraft structure containing multiple substructures. Therefore, this paper proposes the mean value-based parallel collaborative optimization method (MVPM) for modular aircraft structural layout. This method is a two-stage optimization method based on decomposition. The basic idea of the MVPM is decomposing the layout optimization problem of the modular aircraft structure into a system coordination problem and several independent subsystem optimization problems by introducing coordination variables. The subsystem optimizes each aircraft structure. Under the constraints of the structure itself, the performance of each structure is better, and the shared variables are as close to the coordination variables as possible. The system coordination adjusts the coordination variables according to the optimization results of each subsystem. With constant iteration between the system and subsystems, the shared variables of each subsystem eventually agree with the coordination variables. The numerical test results show that the MVPM has high optimization efficiency and stability.

Transit Signal Priority for an Integrated Traffic Signal System

Passive transit-signal priority (TSP) is an effective approach to improve the operational efficiency of transit systems on arterial roads. This paper presents an integrated TSP model that benefits both transit vehicles and other road users. The proposed model uses the random arrival characteristics of transit vehicles related to their stochastic dwell times at near-side stops. Thus, it enables not only two-way bandwidth maximization within subsystems but also the combined optimization of adjacent subsystems. To minimize any negative impact on side-street traffic, this study, unlike previous research, considers the influential area by the introduction of TSP. Case studies on 15 intersections in Sejong, Korea, verify the superior performance of the proposed model for both transit and general vehicles.

From motor control to team play in simulated humanoid football.

Learning to combine control at the level of joint torques with longer-term goal-directed behavior is a long-standing challenge for physically embodied artificial agents. Intelligent behavior in the physical world unfolds across multiple spatial and temporal scales: Although movements are ultimately executed at the level of instantaneous muscle tensions or joint torques, they must be selected to serve goals that are defined on much longer time scales and that often involve complex interactions with the environment and other agents. Recent research has demonstrated the potential of learning-based approaches applied to the respective problems of complex movement, long-term planning, and multiagent coordination. However, their integration traditionally required the design and optimization of independent subsystems and remains challenging. In this work, we tackled the integration of motor control and long-horizon decision-making in the context of simulated humanoid football, which requires agile motor control and multiagent coordination. We optimized teams of agents to play simulated football via reinforcement learning, constraining the solution space to that of plausible movements learned using human motion capture data. They were trained to maximize several environment rewards and to imitate pretrained football-specific skills if doing so led to improved performance. The result is a team of coordinated humanoid football players that exhibit complex behavior at different scales, quantified by a range of analysis and statistics, including those used in real-world sport analytics. Our work constitutes a complete demonstration of learned integrated decision-making at multiple scales in a multiagent setting.

A Novel Capsule-Delivered Enteric Drug-Injection Device for Delivery of Systemic Biologics: A Pilot Study in a Porcine Model.

Innovative swallowable capsule technologies such as drug-loaded, dissolvable microneedles, mucoadhesive patches, and various microdevices present unique drug-carrying capabilities to overcome challenges regarding oral delivery of biologics. Here, we report a swallowable capsule for intestinal drug delivery (SCIDD) with the potential of directly injecting biological therapeutics into the insensate small intestine wall. The design, optimization, and validation of the SCIDD's primary subsystems were performed both ex-vivo and in-vivo. The assembled capsule was further tested in vivo to validate the actuation sequence and showed a 70% (n = 17) success rate in an animal model. Additionally, a drug delivery study indicated systemic uptake of adalimumab via SCIDD compared with luminal delivery in the small intestine. The pilot study presented here establishes that the novel platform could be used to orally deliver systemic biologics.

Actor-critic continuous state reinforcement learning for wind-turbine control robust optimization

The control of Variable-Speed Wind-Turbines (VSWT) extracting electrical power from the wind kinetic energy are composed of subsystems that need to be controlled jointly, namely the blade pitch and the generator torque controllers. Previous state of the art approaches decompose the joint control problem into independent control subproblems, each with its own control subgoal, carrying out separately the design and tuning of a parameterized controller for each subproblem. Such approaches neglect interactions among subsystems which can introduce significant effects. This paper applies Actor-Critic Reinforcement Learning (ACRL) for the joint control problem as a whole, carrying out the simultaneous control parameter optimization of both subsystems without neglecting their interactions, aiming for a globally optimal control of the whole system. The innovative control architecture uses an augmented input space so that the parameters can be fine-tuned for each working condition. Validation results conducted on simulation experiments using the state-of-the-art OpenFAST simulator show a significant efficiency improvement relative to the best state of the art controllers used as benchmarks, up to a 22% improvement in the average power error performance after ACRL training.

Optimization of subsystems for providing strategic development of the sports and health sphere

Introduction. Implementing the strategy for developing sports and recreational activities in the conditions of new economic and socio-political realities requires the development of effective systems of complex provision of the industry with the necessary resources and mechanisms for their distribution and coordination. The primary direction of the formation of a model aimed at the implementation of strategic goals and objectives of the development of the sports and health sector is the revision of the current management system in the industry and its reformation given the change in tasks, priorities and strategic opportunities, taking into account the economic situation and the primary post-war needs of the restoration of the socio-economic system the country and its regions. The article's purpose is to discuss optimizing the subsystems to ensure the strategic development of the sports and health sector. Method (methodology). General scientific methods were used in the study: systematization and generalization - to identify the conditions for the development of the sports and recreation sphere in Ukraine; determination of development trends - to characterize national and regional trends in the development of sports and health activities. The results. Implementing the strategy for developing sports and recreational activities in the conditions of new economic and socio-political realities requires the development of effective systems of complex provision of the industry with the necessary resources and mechanisms for their distribution and coordination. In this context, the main subsystems (organizational, personnel, material and technical, financial, informational, and socio-psychological support) are highlighted, which will collectively contribute to ensuring the industry's viability in the long term. Their current state and main tasks for adaptation to current and strategic conditions are analyzed. Special attention in the context of the strategic development of sports and health activities is focused on creating an effective system of financial and economic support for the industry as a basic factor in the functioning of other subsystems. The financial and economic subsystem of the development of sports and health activities in the work is understood as a set of structural and dynamic characteristics of economic relationships within the industry (between all participants in the processes of sports and health activities) and outside of it (with state bodies, scientific organizations, foreign partners), which includes a set of defined property relations, systems of movement of financial resources and management methods regulated by relevant legal norms, embodied in organizational and economic mechanisms that allow effective functioning in conditions of a changing environment.

Adaptive fault-tolerant tracking control of flying-wing unmanned aerial vehicle with system input saturation and state constraints

In this paper, an adaptive fault-tolerant attitude tracking controller based on reinforcement learning is developed for flying-wing unmanned aerial vehicle subjected to actuator faults and saturation. At first, the attitude dynamic model is separated into two dynamic subsystems as slow and fast dynamic subsystems based on the principle of time scale separation. Secondly, backstepping technique is adopted to design the controller. For the purpose of attitude angle constraints, the control technique based on Barrier Lyapunov is used to design controller of slow dynamic subsystem. Considering the optimization of the fast dynamic subsystem, this paper introduces an adaptive reinforcement learning control method in which neural network is used to approximate the long-term performance index and lumped fault dynamic. It is shown that this control algorithm can satisfy the requirements of attitude tracking subjected to the control constraints and the stability of the system is proved from Lyapunov stability theory. The simulation results demonstrate that the developed fault-tolerant scheme is useful and has more smooth control effect compared with fault-tolerant controller based on sliding mode theory.