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TD3 Algorithm of Dynamic Classification Replay Buffer Based pid parameter optimization

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2024年第10期22卷 3068-3082页

作者： Zhong, Haojun Wang, Zhenlei East China Univ Sci & Technol Key Lab Smart Mfg Energy Chem Proc Minsty Educ Shanghai 200237 Peoples R China East China Univ Sci & Technol Ctr Proc Syst Engn Minsty Educ Shanghai 200237 Peoples R China

In industrial control, pid controllers are widely used, but their control performance depends heavily on the parameters of the controller. However, the adjustment of pid controller parameters is cumbersome and inefficient. Recently, deep reinforcement learning has been gradually introduced into the industrial control field due to its advantage of being able to learn autonomously by interacting with the environment. In this paper, a pid parameter optimization method based on TD3 algorithm of dynamic classification replay buffer (DCRB-TD3) is proposed. By designing the optimization framework, the optimization process of the pid parameters is converted into the learning process of the weights of the actor network. In order to improve the learning efficiency of the reinforcement learning algorithm, avoid the phenomenon of control curve dispersion and ensure that the whole process can be continuously closed-loop optimized. In this paper, the regular TD3 algorithm is improved, a dynamic classification ratio strategy is designed, and a sampling update method for dynamic classification experience replay is proposed. Finally, simulations are performed on various systems, and DCRB-TD3 is compared with the pid parameter optimization method based on the PSO algorithm. The results show that the pid parameters optimized by DCRB-TD3 have better control performance than other methods.

关键词： Deep reinforcement learning intelligent optimization pid parameter optimization twin delayed deep deterministic policy gradient (TD3)

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pid parameter optimization OF THE GRATE COOLING ELECTRO-HYDRAULIC POSITION SERVO SYSTEM BASED ON APSO 13

PID PARAMETER OPTIMIZATION OF THE GRATE COOLING ELECTRO-HYDR...

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13th IEEE International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP)

作者： Jiang, Chang-Hong Xu, Hong Wang, Sheng-Hui Changchun Univ Technol Coll Elect & Elect Engn Changchun 130012 Jilin Peoples R China

ISBN: (纸本)9781509061266

In this paper, a new particle swarm optimization algorithm, adaptive particle swarm optimization (APSO) algorithm, is proposed to optimize the stability and setting time of the fourth generation grate cooler scraper during speed regulation. This algorithm replaces the compression factor with the time varying parameter by using the dynamic variation of the time varying parameters of the traditional PSO algorithm. At the same time, it is proved that the new PSO algorithm in this paper has faster convergence speed and higher efficiency than traditional PSO algorithm. Finally, algorithm is applied to the simulation of electro-hydraulic servo system of grate cooler, and good control effect is achieved.

关键词： Adaptive Particle Swarm optimization Algorithm electro-hydraulic servo control system pid parameter optimization simulation

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Optimal Control Strategy of Turbine Governor parameters Based on Improved Beetle Antennae Search Algorithm

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TEHNICKI VJESNIK-TECHNICAL GAZETTE 2021年第4期28卷 1082-1090页

作者： Kong, Fannie Li, Jinzhao Yang, Daliang Guangxi Univ Sch Elect Engn Univ Guangxi Univ 100 Daxuedong Rd Nanning 530004 Guangxi Peoples R China

Aiming at the occurrence of long-term and ultra-low frequency oscillations in the hydropower network system, this paper derives the generalized turbine transfer function speed control system model including the flow factor T-pq based on the generalized turbine model, and analyzes the influence of T-pq and pid parameters on the ultra-low frequency damping of the hydraulic turbine governing system. In order to better suppress the ultra-low frequency oscillation caused by improper pid parameter settings, a comprehensive optimization objective function reflecting damping and turbine speed deviation index (ITAE) in ultra-low frequency band is established. Based on the fast and efficient optimization strategy of Beetle Antennae Search, an improved beetle antennae particle swarm optimization is constructed. In single-machine and multi-machine systems, the improved algorithm is compared with different optimization algorithms. The simulation results show that the improved algorithm can overcome the slow convergence speed and easily fall into local optimization problem, effectively improve the damping level of hydraulic turbine governing system in ultra-low frequency, and is more effective and superior than other optimization algorithms. It provides a new way of thinking and technical means to suppress the ultra-low frequency oscillation by optimizing the parameters of the speed control system.

关键词： generalized hydro-turbine transfer function model hydraulic turbine governing system improved beetle antennae particle swarm optimization algorithm pid parameter optimization ultra-low frequency oscillation

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Consumer-oriented intelligent ripening control system for post-ripening fruit

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JOURNAL OF FOOD PROCESS ENGINEERING 2023年第12期46卷 e14442-e14442页

作者： Li, Yuliang Huang, Wentao Li, Hanyu Wang, Xiang Zhang, Xiaoshuan China Agr Univ Coll Engn Beijing Lab Food Qual & Safety Beijing Peoples R China China Agr Univ Coll Engn Beijing Lab Food Qual & Safety Beijing 100083 Peoples R China

To address the issues commonly encountered in traditional fruit ripening processes, which include reliance on manual experience, low efficiency, single control parameter, and significant fluctuations, a new intelligent fruit ripening control system has been designed. This system is based on a mathematical modeling algorithm, which allows for more effective and precise control over the ripening process. To ensure that the ripe fruits are transported to the fruit processing center in a low ripeness state, the proposed system adopts a strategy of precise control of temperature and ethylene, as well as range control of other environmental parameters. The RSSA-pid model is used for ethylene and temperature control, which has high smoothness, fast response time, and high stability. Compared with the traditional pid model, the RSSA-pid model has better dynamic performance and stability. Finally, the proposed system is applied to the ripening process of post-ripening fruits, and the results show that the system achieves intelligent ripening, precise control, and low power consumption. The temperature and ethylene concentration are controlled within a variation of no more than 0.5%, and the humidity, oxygen, and carbon dioxide are maintained within reasonable thresholds. Overall, this paper provides a promising solution for the ripening process of post-ripening fruits, which can benefit the fruit industry by improving the efficiency and quality of the supply *** ApplicationThe ripening chamber environment is a dynamic equilibrium environment with non-linear characteristics because the fruits in the ripening chamber are constantly exchanging substances and energy with the environment through respiration and transpiration. An intelligent ripening control system (IRCS) for post-ripening fruits is proposed in this paper (Figure 1). The whole ripening process runs automatically, which significantly reduces the ripening time and saves a lot of post-processing time. The

关键词： pid parameter optimization post-ripening fruit ripening control RSSA supply chain

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parameter optimization of unmanned surface vessel propulsion motor based on BAS-PSO

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INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 2022年第2期19卷

作者： Bian, Li Che, Xiangqian Liu Chengyang Dai Jiageng Hui, He Guangdong Ocean Univ Coll Maritime Zhanjiang Guangdong Peoples R China Guangdong Ocean Univ Coll Math & Comp Zhanjiang 524088 Guangdong Peoples R China Heilongjiang Univ Sci & Technol Coll Elect & Control Engn Harbin Heilongjiang Peoples R China

Despite advances in modern control theory and artificial intelligence technology, current methods for tuning proportional-integral-derivative (pid) controller parameters based on the traditional particle swarm optimization (PSO) algorithm do not meet the requirements for controlling an unmanned surface vessel (USV) propulsion motor. To overcome the disadvantages of the PSO algorithm, such as low precision and easily falling into a local optimum, the beetle antennae search (BAS) algorithm can be introduced into the PSO algorithm by replacing particles with beetles, and effectively prevents the PSO algorithm from easily falling into the local optimum. At the same time, the BAS algorithm will no longer be limited to single objective parameterization. Herein, we propose a pid parameter optimization method based on the hybrid BAS-PSO algorithm for a USV propulsion motor. The pid parameter optimization of propulsion motor effectively becomes a beetle foraging problem with group optimization. Numerical results show that the method can effectively solve the problems of PSO and greatly improve convergence speed. Compared with the genetic algorithm and standard PSO algorithm, the BAS-PSO algorithm is superior for pid parameter tuning and can improve performance of USV propulsion system.

关键词： Beetle antennae search particle swarm optimization propulsion motor unmanned surface vehicle pid parameter optimization

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Optimal Control of Chilled Water System Based on Improved Sparrow Search Algorithm

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BUILDINGS 2022年第3期12卷 269页

作者： Zhu, Qixin Zhuang, Mengxiang Liu, Hongli Zhu, Yonghong Suzhou Univ Sci & Technol Sch Mech Engn Suzhou 215009 Peoples R China Suzhou Univ Sci & Technol Jiangsu Prov Key Lab Intelligent Bldg Energy Effi Suzhou 215009 Peoples R China Suzhou Univ Sci & Technol Sch Environm Sci & Engn Suzhou 215009 Peoples R China Jingdezhen Ceram Inst Sch Mech & Elect Engn Jingdezhen 333001 Peoples R China

Chilled water systems have large time delays and large inertia, and the traditional pid controller has a poor control effect. In this paper, an improved sparrow search algorithm is proposed to optimize the control of chilled water systems. Firstly, the random walk strategy was used to randomly perturb the sparrows to improve the searching ability of the sparrows. Then, a Gauss mutation was added in the iteration process of sparrows to enhance the local search ability. Finally, the values of the pid parameters as obtained by the above methods were substituted into the controller for simulation. The simulation results show that the method proposed in this paper improves the search accuracy of the sparrow search algorithm and effectively solves the problems of large time delays and large inertia in the chilled water system. The method in this paper took the least amount of time for the system to reach the steady state at only 12.75 s. The control effect of the proposed method was also better than that of the improved ant colony optimization algorithm. The rise time was 2.713 s, and the adjustment time was 4.95 s.

关键词： sparrow search algorithm random walk strategy Gauss mutation pid parameter optimization chilled water system

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parameters optimization for suspension system of maglev train via improved PSO

Parameters Optimization for suspension system of maglev trai...

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Chinese Automation Congress (CAC)

作者： Zhou, Xu Wang, Ping Long, Zhiqiang Natl Univ Def Technol Coll Intelligence Sci & Technol Changsha 410073 Peoples R China Hunan Prov Key Lab Electromagnet Levitat & Prop T Changsha 410073 Peoples R China

ISBN: (纸本)9781728176871

The control strategy for suspension system is of great importance to stability and safety of the medium-speed maglev train. The medium-speed maglev train usually adopts the inner current loop control, causing low control accuracy and difficulty to achieve the desired effect. On basis of the in-depth comprehension of pid control and particle swarm optimization algorithm (PSO) , the control strategy of pid control based on improved PSO is proposed. Through the introduction of PM control on the basis of the traditional double-loop control of the medium-speed maglev train, the optimal pid parameters are searched in the solution space by the PSO algorithm based on decreasing inertia weight. The proposed control strategy improves the efficiency and accuracy. Meanwhile, the simulation results confirm the effectiveness of the control strategy.

关键词： Improved PSO suspension system inner current loop pid parameter optimization

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optimization Strategy of Hydrogovernors for Eliminating Ultralow-Frequency Oscillations in Hydrodominant Power Systems

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IEEE JOURNAL OF EMERGING AND SELECTED TOPICS IN POWER ELECTRONICS 2018年第3期6卷 1086-1094页

作者： Chen, Gang Tang, Fan Shi, Huabo Yu, Rui Wang, Guanhong Ding, Lijie Liu, Baisi Lu, Xiaonan State Grid Sichuan Elect Power Res Inst Dept Power Syst Technol Chengdu 610072 Sichuan Peoples R China State Grid Corp China Southwest Branch Chengdu 610041 Sichuan Peoples R China China Elect Power Res Inst Dept Power Syst Beijing 100096 Peoples R China Argonne Natl Lab Energy Syst Div Lemont IL 60439 USA

Southwest China power grid (SCPG) and central China power grid are planned to be unsynchronized by using back-to-back voltage source converter based high voltage direct current transmission between Chongqing and Hubei power grids. After asynchronous interconnection, the proportion of hydro in installed capacity is about 70%. In other words, the SCPG is a typical hydrodominant power system. Due to the negative damping effect of governors of hydrogenerators, there is a serious risk of ultralow-frequency oscillation (ULFO) in the range of 0.05 Hz. In this paper, optimization strategies of governor for hydropower unit are presented to eliminate ULFOs. First, the control mode is selected based on comparing damping characteristic of different control modes of governor. Then, a relevant coefficient index is proposed to select sensitive generators of ULFO. Afterward, pid parameters of governor are optimized based on a new performance criteria considering the damping characteristic of governor. Finally, optimization strategies are presented and applied to SCPG. Simulation results show effectiveness and practicability of the proposed measures, which have been adopted and will be implemented before the asynchronous interconnection.

关键词： Correlation coefficient index damping characteristic governor pid parameter optimization ultralow-frequency oscillation (ULFO)

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Practical Strategy for Adjusting parameters of Hydro-Governors in Hydro-Dominant Power Systems Accommodating Asynchronous Interconnection

Practical Strategy for Adjusting Parameters of Hydro-Governo...

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International Conference on Power System Technology (POWERCON)

作者： Chen, Gang Han, Xiaoyan Wang, Guanhong Zhang, Yudong Zhang, Hua Ai, Dongping Tang, Fan Wang, Liang Shi, Huabo State Grid Sichuan Elect Power Res Inst Chengdu 610072 Sichuan Peoples R China State Grid Sichuan Elect Power Co Chengdu 610072 Sichuan Peoples R China China Elect Power Res Inst 15 Qinghe Xiaoying East Rd Beijing 100096 Peoples R China State Grid Corp Southwest Branch Chengdu 610041 Sichuan Peoples R China

ISBN: (纸本)9781538664612

In this paper, a practical strategy for adjusting PM parameters of hydro-governors in hydro-dominant power systems is presented, in order to suppress the ultra-low frequency oscillation (ULFO) in the range of 0.05 Hz. Firstly, practical indexes are proposed to select sensitive generators of ULFO. Then, Practical pid parameters optimization methods are introduced, considering damping characteristic of governor. Afterwards, general process of adjusting parameters for hydro-governors is presented, which could be referenced by engineering and technical personnel. Finally, the proposed strategies are applied to Southwest China Power Grid (SCPG) which is going to be asynchronous interconnection with Central China Power Grid. Simulation and field test results show effectiveness and practicability of the proposed measures.

关键词： Ultra-low frequency oscillation damping characteristic pid parameter optimization governor

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An Improved BBO Algorithm and Its Application in pid optimization of CFB Bed Temperature System 5th

An Improved BBO Algorithm and Its Application in PID Optimiz...

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5th International Conference on Electrical Engineering and Automatic Control (ICEEAC)

作者： Xue, Hong Pu, Han North China Elect Power Univ Dept Automat Baoding Peoples R China

ISBN: (纸本)9783662487686;9783662487662

In order to improve the performance of biogeography optimization (BBO) algorithm in pid controller parameter optimization of thermal systems and have superior convergence characteristics, the article gives an improved BBO algorithm. The improved BBO algorithm introduces the introducing convergence mechanism of particle swarm optimization on the basis of original migration strategy, so that the whole migration process has a certain direction. Also, the article uses phase-out strategy to remove poor parameters which are obtained after the migration and mutation processes. Thus, on the one hand, directional migration and elimination mechanism can ensure its fast convergence properties. On the other hand, mutational mechanisms can ensure the global characteristics of wide-area searching and avoid falling into local extrema. Using it in the pid optimization of CFB bed temperature system, the simulation results show that the improved BBO algorithm has a better performance than the standard BBO algorithm on convergence speed and precision. It is feasible and effective for pid controller parameter optimization in thermal system.

关键词： Improved BBO algorithm pid parameter optimization CFB bed temperature Simulation research

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