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A gradient-descent iterative learning control algorithm for a non-linear system

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND control 2025年第2期47卷 342-351页

作者： He, Zhiying Pu, Hongji Chongqing Univ Technol Engn Res Ctr Mech Testing Technol & Equipment Minist Educ 69 Hongguang Ave Chongqing Municipality 400054 Peoples R China Chongqing Univ Technol Chongqing Key Lab Time Grating Sensing & Adv Testi Chongqing Peoples R China

Original iterative learning control (OILC) has been proved a powerful tool in dealing with the model-free control problems by repetitively corrections based on the control error. However, the steady-state error under widely-used proportional-type original iterative learning control (P-type OILC) is highly corresponded to the proportional learning gain, making the algorithm parameter-determined. Therefore, a new gradient-descent iterative learning control (GDILC) algorithm is proposed to achieve a parameter-free approach by simulating the gradient-descent process. First, GDILC problem is formulated mathematically. Next, the idea of the algorithm is proposed, the analyses of the convergence and the steady-state error are conducted and the algorithm is implemented. GDILC will generate a random correction with a gradient-descent upper bound, rather than a correction proportional to the error in P-type OILC. Finally, illustrative and application simulations are conducted to validate the algorithm. Results show that the algorithm will be convergent after adequate iterations under proper corrections. The steady-state error will be less affected by the algorithm parameters under GDILC than that under OILC.

关键词： Gradient-descent iterative learning control control algorithm non-linear system steady-state error

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BPNN-assisted control algorithm application to a super large cable-net structure of active FAST reflector system

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STRUCTURES 2025年 73卷

作者： Liu, Juncai Ma, Zhen Tian, Li Li, Qingwei Bi, Wenzhe Shandong Univ Sch Civil Engn Jinan 250061 Shandong Peoples R China Chinese Acad Sci Natl Astron Observ Beijing 100101 Peoples R China

The Five-hundred-meter Aperture Spherical Telescope (FAST), recognized as the world's largest single-dish radio telescope, has made significant contributions to astronomical observations. As an essential component of the FAST system, the super-large cable-net structure with a 500 m diameter necessitates the rapid and simultaneous control of its 2225 actuator strokes to adjust to the desired parabolic shape for observation. Existing control algorithms require improvement to meet these complex requirements. Consequently, this study develops a control algorithm utilizing a backpropagation neural network (BPNN) and integrates it into the high-precision control of the 2225 actuator strokes of the super-large cable-net structure. The superiority of the BPNN model is thoroughly evaluated in terms of prediction accuracy, modeling efficiency, and computing speed, compared against the grid interpolation algorithm currently employed in the FAST system. The comparative analysis underscores the feasibility and effectiveness of the established BPNN model in predicting the profile shape of the super-large cable-net structure. Notably, the BPNN model saves approximately 57 days of modeling time and increases computational efficiency by 65.7 %, while also improving prediction accuracies across various operating conditions. This outcome aims to provide a practical strategy for the active and rapid control of the surface shape of the FAST system.

关键词： Cable-net structure Back propagation neural network FAST control algorithm Surface shape

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RESEARCH ON AUTONOMOUS NAVIGATION AND control algorithm OF INTELLIGENT ROBOT BASED ON REINFORCEMENT LEARNING

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SCALABLE COMPUTING-PRACTICE AND EXPERIENCE 2025年第1期26卷 423-431页

作者： Yi, Yunlong Guan, Ying Shenyang Inst Engn Sch Informat Shenyang 110136 Liaoning Peoples R China

The last few decades have seen impressive developments in the field of robotics, especially in the areas of autonomous navigation and control. Robust algorithms that can facilitate effective decision-making in real-time settings are needed as the need for intelligent robots that can function in complex and dynamic contexts grows. Through trial-and-error interactions with their surroundings, reinforcement learning (RL) has become a promising method for teaching intelligent agents to navigate and control robots independently. The purpose of this study is to look at the creation and use of reinforcement learning algorithms for intelligent robot control and autonomous navigation. With an emphasis on methods like deep Q-learning, policy gradients, and actor-critic approaches, the research delves into the theoretical underpinnings of reinforcement learning and how it has been applied to the field of robotics. This study assesses how well RL algorithms work to help robots acquire the best navigational strategies in challenging surroundings through an extensive literature review and empirical investigation. In addition, the study suggests new improvements and optimizations for current reinforcement learning algorithms to tackle problems unique to robot navigation, such as avoiding obstacles, routing, and interactions with dynamic environments. These improvements increase the effectiveness, flexibility, and security of independent robot navigation systems by utilizing knowledge from cognitive science and neuroscience. The suggested methods are experimentally evaluated through both real-world applications on physical robotic platforms and simulation-based research. Performance measures including navigation speed, success rate, and collision avoidance ability are used to evaluate how well the suggested algorithms operate in different scenarios and circumstances.

关键词： autonomous navigation control algorithm intelligent robot system reinforcement learning

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Kinematic analysis of wire stripping for distribution robots based on wire stripping and cutting force control algorithm under cylindrical gear transmission

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FRONTIERS IN MECHANICAL ENGINEERING-SWITZERLAND 2025年 11卷

作者： Liu, Juan Qiao, Ziqiang Huanghe Jiaotong Univ Sch Mech & Elect Engn Jiaozuo Peoples R China

Introduction The accurate analysis of Wire Stripping Operation of Power Distribution Robot is crucial for the automation and intelligence of power system maintenance operations. Therefore, a new design and control method for Wire Stripping Operation of Power Distribution Robot has been proposed. Methods Firstly, a wire stripping device suitable for Cylindrical Gear Transmission was designed. Then, kinematic analysis was conducted based on the Wire Stripping and Cutting Force to ensure the accuracy of the stripping process. Finally, to cope with changes in stiffness environments, an impedance control strategy based on Recursive Least Square method was introduced to improve the stability and adaptability of the control system. Results These results confirmed that the proposed method performs significantly better than traditional methods in force response tracking. When the wire stripping time was 1.9 s, the sinusoidal force responses of the research method, reference force, and general impedance force were -15.3 N, -15.4 N, and -8.2 N, respectively. The sinusoidal force tracking responses were -19.6 N, 6.5 N, 2.6 N to -18.2 N, respectively. The impedance force error curve of the proposed method shows no significant difference compared to the general impedance force error curve (P < 0.05). Meanwhile, the impedance force error curve of the research method was more stable, while the general impedance force error curve fluctuated greatly. Simulation analysis confirmed that the wire stripping surface of the research method was smooth and undamaged, demonstrating the rationality of the wire stripping device design and the superiority of the wire stripping control algorithm. The accuracy, efficiency, and stability scores of the proposed method are superior to the other three classical control methods. Discussion This study is crucial for improving the automation level and operational accuracy of wire stripping operations in power distribution robots.

关键词： cylindrical gear transmission wire stripping and cutting force control algorithm power distribution robot wire stripping motion RLS

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A novel high-speed railway large-span cable-stayed bridge with deformation active control function: structural system and control algorithm

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STRUCTURE AND INFRASTRUCTURE ENGINEERING 2025年

作者： Zhu, Zhihui Liu, Yang Zheng, Weiqi Ren, Zengzhen Cent South Univ Natl Engn Res Ctr High Speed Railway Construct Tec Changsha Peoples R China Cent South Univ Sch Civil Engn Changsha Peoples R China

Large-span cable-stayed bridges produce adverse girder-deformation under complex service conditions, affecting the track geometric irregularity and train running performance. In this work, the Deformation-Adaptive Cable-Stayed Bridge (DACSB) is invented to control the girder-deformation of cable-stayed bridge by introducing the deformation active control technology. The environment-induced girder-deformation can be adjusted by utilising a set of actuators installed at the DACSB. A deformation active control method is proposed to realise the active control simulation of the DACSB. Based on this, taking a high-speed railway large-span cable-stayed bridge as a case, the girder-deformation active control process is realised under the temperature and train loads. The adverse girder-deformations can be adjusted by the proposed active control method, including dynamic control for temperature-induced deformations and pre-deformation control for train-induced deformations. Furthermore, an evaluation of track geometric irregularity and train running performance is conducted, indicating that the indicators of track geometric irregularity and train riding comfort for large-span cable-stayed bridges are improved significantly by the deformation active control technology. The proposed novel structural system and control algorithm can be used for girder-deformation active control on large-span cable-stayed bridges, providing technical support for the maintenance of track high smoothness on high-speed railways.

关键词： control algorithm deformation active control high-speed railway large-span cable-stayed bridge structural system track geometric irregularity train riding performance

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control algorithm of Electric Vehicle in Coasting Mode Based on Driving Feeling

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Chinese Journal of Mechanical Engineering 2015年第3期28卷 479-486页

作者： SUN Daxu LAN Fengchong ZHOU Yunjiao CHEN Jiqing School of Mechanical & Automotive Engineering South China University of Technology Key Laboratory of Guangdong Province of Automotive Engineering South China University of Technology

Coasting in gear is a common driving mode for the conventional vehicle equipped with the internal combustion engine（ICE）, and the assistant braking function of ICE is utilized to decelerate the vehicle in this mode. However, the electric vehicle（EV） does not have this feature in the coasting mode due to the relatively small inertia of the driving motor, so it will cause the driver cannot obtain the similar driving feeling to that of the conventional vehicle, and even a traffic accident may occur if the driver cannot immediately adapt to the changes. In this paper, the coasting control for EV is researched based on the driving feeling. A conventional vehicle equipped with continuously variable transmission（CVT） is taken as the reference vehicle, and the combined simulation model of EV is established based on AVL CRUISE and MATLAB/Simulink. The torque characteristic of the CVT output shaft is measured in coasting mode, and the data are smoothed and fitted to a polynomial curve. For the EV in coasting mode, if the state of charge（SOC） of the battery is below 95%, the polynomial curve is used as the control target for the torque characteristic of the driving motor, otherwise, the required torque is replaced by hydraulic braking torque to keep the same deceleration. The co-simulation of Matlab/Simulink/Stateflow and AVL CRUISE, as well as the hardware-in-loop experiment combined with d SPACE are carried out to verify the effectiveness and the real-time performance of the control algorithm. The results show that the EV with coasting braking control system has similar driving feeling to that of the reference vehicle, meanwhile, the battery SOC can be increased by 0.036% and 0.021% in the initial speed of 100 km/h and 50 km/h, respectively. The proposed control algorithm for EV is beneficial to improve the driving feeling in coasting mode, and it also makes the EV has the assistant braking function.

关键词： electric vehicle coasting braking control algorithm engine braking motor braking

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control algorithm update for multi-input multi-output random environment test

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MECHANICAL SYSTEMS AND SIGNAL PROCESSING 2018年 111卷 643-662页

作者： Cui, Song Chen, Huaihai He, Xudong Zheng, Wei Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing 210016 Jiangsu Peoples R China

When conducting multi-input multi-output (MIMO) random vibration environment test, response spectral lines of under test article may exceed their tolerances and some of them can hardly be controlled by control algorithms. The cause of this phenomenon is the high level noises in the input forces, which are induced by the inverse of the ill-conditioned frequency response function matrices. These spectral lines may even trigger the instability of control algorithms and eventually result in an accidental test shutoff. The classical control algorithm for MIMO random vibration environment test contributed by Smallwood is analyzed theoretically and experimentally in the paper to reveal its weakness on dealing with this kind of error. An updated algorithm is proposed on the basis of inverse theory to overcome the difficulty of controlling these stubborn spectral lines. The main idea of the work is to reduce the level of noise components in input forces by regularizing singular values of ill-conditioned frequency response function matrices. An adjusting rule is set up according to the auto-power spectra tolerances. A simulation and an experiment are supplied in the paper to verify the effectiveness of the updated algorithm, the results are satisfactory. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Multi-input multi-output Vibration environment test Random Ill-condition control algorithm

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control algorithm FOR MICROWAVE SINTERING IN A RESONANT SYSTEM

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JOURNAL OF MICROWAVE POWER AND ELECTROMAGNETIC ENERGY 1990年第1期25卷 25-31页

作者： ALLIOUAT, M LECLUSE, Y MASSIEU, J MAZO, L INST SCI MAT RAYONNEMENT GRP ETUD & RECH SCI PHYS INGN CAENAUTOMAT LABF-14032 CAENFRANCE

This paper describes a computer control method for sintering dielectric materials by microwave heating. The algorithm used allows control of either the surface temperature of the sample or the absorbed power. The expe... 详细信息

关键词： Resonant cavity Microwave sintering control algorithm Self turning Microwave heating Ceramic processing Dynamic feedback

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control algorithm influence on the compromise movement time/vibration - Application to a high speed machine

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MECANIQUE & INDUSTRIES 2007年第5期8卷 429-436页

作者： Colas, Frederic Dieulot, Jean-Yves Barre, Pierre-Jean ENSAM L2EP Equipe Rech CEMODYNE F-59046 Lille France

While improving the dynamical performance of a flexible motion control system, additional stresses are generated which induce undesirable vibrations. The design of adequate control algorithms makes it possible to enhance the overall behaviour of the machine while limiting its deformation modes vibrations. This paper presents a comparative study of the influence of different control algorithms on the trade-off between the cycle time and the amplitude of the residual vibrations, which have been applied to a Cartesian robot. While this selection of control algorithms is not exhaustive, these can all easily be implemented in current industrial systems. Each selected control algorithm is analysed along with experimental validations.

关键词： control algorithm movement time residual vibration flexible system

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control algorithm OF HVAC SYSTEM POWER MANAGEMENT IN OLEV (R) APPLICATION

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JOURNAL OF INTEGRATED DESIGN & PROCESS SCIENCE 2011年第3期15卷 29-42页

作者： Suh, In-Soo Shin, Eun Korea Adv Inst Sci & Technol CCS Grad Sch Green Transportat Daejeon South Korea Korea Adv Inst Sci & Technol Dept Aerosp Engn Daejeon South Korea

Battery issues like weight, cost, charging time and infrastructure have been major obstacles to Electric Vehicle (EV) introduction to the market. As a solution, KAIST introduced the new concept of on-road wireless charging technology, called OLEV (R) (On-Line Electric Vehicle). In applying the technology, efficient power management, especially with Heating, Ventilation and AirConditioning (HVAC) system in electric vehicles remains as yet to be solved, in view of continuous and efficient energy management especially when operating on the electrified road. In this paper, unique feature of power control algorithm of HVAC system for OLEV (R) is introduced. The main purpose is to control the amount of power and energy consumed by HVAC system so that it does not affect any key performances of an electric vehicle in view of driving distance and speed. Specifically, the algorithm makes sure that HVAC consumes no more than 20% and 25% of instantaneously available power for air-conditioning and heating respectively by controlling the output of heating or cooling power from HVAC system, while maximizing the HVAC performance in customers' perspective. A proper set of dynamic models and control algorithms for a HVAC system is developed linked together with OLEV (R) system operation. With these models, simulations have been carried out to verify that the algorithm leads to optimized and improved performance of an OLEV (R).

关键词： OLEV HVAC dynamic model control algorithm power management

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