Contract Mechanism of Water Environment Regulation for Small and Medium Sized Enterprises Based on Optimal Control Theory

The small and scattered enterprise pattern in the county economy has formed numerous sporadic pollution sources, hindering the centralized treatment of the water environment, increasing the cost and difficulty of treatment. How enterprises can make reasonable decisions on their water environment behavior based on the external environment and their own factors is of great significance for scientifically and effectively designing water environment regulation mechanisms. Based on optimal control theory, this study investigates the design of contractual mechanisms for water environmental regulation for small and medium-sized enterprises. The enterprise is regarded as an independent economic entity that can adopt optimal control strategies to maximize its own interests. Based on the participation of multiple subjects including the government, enterprises, and the public, an optimal control strategy model for enterprises under contractual water environmental regulation is constructed using optimal control theory, and a method for calculating the amount of unit pollutant penalties is derived. The water pollutant treatment cost data of a paper company is selected to conduct empirical numerical analysis on the model. The results show that the increase in the probability of government regulation and public participation, as well as the decrease in local government protection for enterprises, can achieve the same regulatory effect while reducing the number of administrative penalties per unit. Finally, the implementation process of contractual water environmental regulation for small and medium-sized enterprises is designed.

Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems

This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation theory.For the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost function.For the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement data.By combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop system.The proposed decomposition design not only bypasses the numerical stiffness but also alleviates the high-dimensionality.The efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.

Event-triggered robust cooperative output regulation for a class of linear multi-agent systems with an unknown exosystem

This paper investigates the robust cooperative output regulation problem for a class of heterogeneousuncertain linear multi-agent systems with an unknown exosystem via event-triggered control (ETC). By utilizingthe internal model approach and the adaptive control technique, a distributed adaptive internal model isconstructed for each agent. Then, based on this internal model, a fully distributed ETC strategy composed ofa distributed event-triggered adaptive output feedback control law and a distributed dynamic event-triggeringmechanism is proposed, in which each agent updates its control input at its own triggering time instants. It isshown that under the proposed ETC strategy, the robust cooperative output regulation problem can be solvedwithout requiring either the global information associated with the communication topology or the bounds ofthe uncertain or unknown parameters in each agent and the exosystem. A numerical example is provided toillustrate the effectiveness of the proposed control strategy.

Regulations for the Manufacture and Control of Live Poliovirus Vaccine: International Experience and China’s Path

The eradication of poliomyelitis is a landmark achievement in the history of public health, providing strong protection for children’s health. The introduction of the Chinese Regulations for the Manufacture and Control of Live Poliovirus Vaccine is a prerequisite and safeguard for the large-scale production and use of domestically produced live poliovirus vaccines, serving as an indispensable component of vaccine safety. This article, based on archival documents, letters, collections of essays, and oral interviews, examines the historical experience of the development of Chinese Regulations for the Manufacture and Control of Live Poliovirus Vaccine. It contends that the emphasis on localization and the active engagement in international cooperation are critical factors in the swift introduction of Chinese Regulations for the Manufacture and Control of Live Poliovirus Vaccine.

Technical Regulations for Comprehensive Control Weeding in Millet Field

According to experiments in many years in Hebei Province, the research explored weed comprehensive control technology on millet fields in terms of application range, prevention rules, prevention object, agricultural control, physical control, and chemical control and proposed specific methods and technological indices in order to provide technological references for comprehensive control on weeds of millet fields.

Effect of sand-fixing vegetation on the hydrological regulation function of sand dunes and its practical significance

Soil water content is a key controlling factor for vegetation restoration in sand dunes.The deep seepage and lateral migration of water in dunes affect the recharge process of deep soil water and groundwater in sand dune ecosystems.To determine the influence of vegetation on the hydrological regulation function of sand dunes,we examined the deep seepage and lateral migration of dune water with different vegetation coverages during the growing season in the Horqin Sandy Land,China.The results showed that the deep seepage and lateral migration of water decreased with the increase in vegetation coverage on the dunes.The accumulated deep seepage water of mobile dunes(vegetation coverage<5%)and dunes with vegetation coverage of 18.03%,27.12%,and 50.65%accounted for 56.53%,51.82%,18.98%,and 0.26%,respectively,of the rainfall in the same period.The accumulated lateral migration of water in these dunes accounted for 12.39%,6.33%,2.23%,and 7.61%of the rainfall in the same period.The direction and position of the dune slope affected the soil water deep seepage and lateral migration process.The amounts of deep seepage and lateral migration of water on the windward slope were lower than those on the leeward slope.The amounts of deep seepage and lateral migration of water showed a decreasing trend from the bottom to the middle and to the top of the dune slope.According to the above results,during the construction of sand-control projects in sandy regions,we suggest that a certain area of mobile dunes(>13.75%)should be retained as a water resource reservoir to maintain the water balance of artificial fixed dune ecosystems.These findings provide reliable evidence for the accurate assessment of water resources within the sand dune ecosystem and guide the construction of desertification control projects.

Speed Regulation Method Using Genetic Algorithm for Dual Three-phase Permanent Magnet Synchronous Motors

Dual three-phase Permanent Magnet Synchronous Motor(DTP-PMSM)is a nonlinear,strongly coupled,high-order multivariable system.In today’s application scenarios,it is difficult for traditional PI controllers to meet the requirements of fast response,high accuracy and good robustness.In order to improve the performance of DTP-PMSM speed regulation system,a control strategy of PI controller based on genetic algorithm is proposed.Firstly,the basic mathematical model of DTP-PMSM is established,and the PI parameters of DTP-PMSM speed regulation system are optimized by genetic algorithm,and the modeling and simulation experiments of DTP-PMSM control system are carried out by MATLAB/SIMULINK.The simulation results show that,compared with the traditional PI control,the proposed algorithm significantly improves the performance of the control system,and the speed output overshoot of the GA-PI speed control system is smaller.The anti-interference ability is stronger,and the torque and double three-phase current output fluctuations are smaller.

Control design for the nonlinear benchmark problem via the output regulation method

The problem of designing a feedback controller to achieve asymptotic disturbance rejection / attenuation while maintaining good transient response in the RTAC system is known as a benchmark nonlinear control problem, which has been an intensive research subject since 1995. In this paper, we will further investigate the solvability of the robust disturbance rejection problem of the RTAC system by the measurement output feedback control based on the robust output regulation method. We have obtained a design by overcoming two major obstacles: find a closed-form solution of the regulator equations; and devise a nonlinear internal model to account for non-polynomial nonlinearities.

Asymptotic regulation of cascade systems with unknown control directions and nonlinear parameterization

A robust partial-state feedback asymptotic regulating control scheme is developed for a class of cascade systems with both nonlinear uncertainties and unknown control directions. A parameter separation technique is introduced to separate the time-varying uncertainty and the unmeasurable state from nonlinear functions. Then, the Nussbaum-type gain method together with the idea of changing supply functions is adopted in the design of a smooth partial-state regulator that can ensure all the signals of the closed-loop system are globally uniformly bounded. Especially, the system state asymptotically converges to zero. The design procedure is illustrated through an example and the simulation results show that the controller is feasible and effective.

Notch signaling controls chondrocyte hypertrophy via indirect regulation of Sox9

RBPjk-dependent Notch signaling regulates both the onset of chondrocyte hypertrophy and the progression to terminal chondrocyte maturation during endochondral ossification. It has been suggested that Notch signaling can regulate Sox9 transcription, although how this occurs at the molecular level in chondrocytes and whether this transcriptional regulation mediates Notch control of chondrocyte hypertrophy and cartilage development is unknown or controversial. Here we have provided conclusive genetic evidence linking RBPjk-dependent Notch signaling to the regulation of Sox9 expression and chondrocyte hypertrophy by examining tissuespecific Rbpjk mutant（Prx1Cre;Rbpjkf/f）, Rbpjk mutant/Sox9 haploinsufficient（Prx1Cre;Rbpjkf/f;Sox9f/1）,and control embryos for alterations in SOX9 expression and chondrocyte hypertrophy during cartilage development. These studies demonstrate that Notch signaling regulates the onset of chondrocyte maturation in a SOX9-dependent manner, while Notch-mediated regulation of terminal chondrocyte maturation likely functions independently of SOX9. Furthermore, our in vitro molecular analyses of the Sox9 promoter and Notch-mediated regulation of Sox9 gene expression in chondrogenic cells identified the ability of Notch to induce Sox9 expression directly in the acute setting, but suppresses Sox9 transcription with prolonged Notch signaling that requires protein synthesis of secondary effectors.

Robust Non-fragile PID Controller Design for the Stroke Regulation of Metering Pumps

This job focuses on the stroke regulation of a class of high-precision metering pumps.A parametertuning method of robust non-fragile PID（proportional-integral-derivative）controllers is proposed with the assumption that a PID controller has additive gain perturbations.An H-infinite robust PID controller can be obtained by solving a linear matrix inequality.This approach can guarantee that the closed-loop control systems is asymptotically stable and the H-infinite norm of the transfer function from the disturbance to the output of a controlled system is less than a given constant to attenuate disturbances.The simulation case shows that the control performance of the proposed strategy is significantly better than the traditional PID approach in the situation with perturbations of controller parameters.

Pressure Regulation for Earth Pressure Balance Control on Shield Tunneling Machine by Using Adaptive Robust Control

Most current studies about shield tunneling machine focus on the construction safety and tunnel structure stability during the excavation. Behaviors of the machine itself are also studied, like some tracking control of the machine. Yet, few works concern about the hydraulic components, especially the pressure and flow rate regulation components. This research focuses on pressure control strategies by using proportional pressure relief valve, which is widely applied on typical shield tunneling machines. Modeling of a commercial pressure relief valve is done. The modeling centers on the main valve, because the dynamic performance is determined by the main valve. To validate such modeling, a frequency-experiment result of the pressure relief valve, whose bandwidth is about 3 Hz, is presented as comparison. The modeling and the frequency experimental result show that it is reasonable to regard the pressure relief valve as a second-order system with two low corner frequencies. PID control, dead band compensation control and adaptive robust control（ARC） are proposed and simulation results are presented. For the ARC, implements by using first order approximation and second order approximation are presented. The simulation results show that the second order approximation implement with ARC can track 4 Hz sine signal very well, and the two ARC simulation errors are within 0.2 MPa. Finally, experiment results of dead band compensation control and adaptive robust control are given. The results show that dead band compensation had about 30° phase lag and about 20% off of the amplitude attenuation. ARC is tracking with little phase lag and almost no amplitude attenuation. In this research, ARC has been tested on a pressure relief valve. It is able to improve the valve＇s dynamic performances greatly, and it is capable of the pressure control of shield machine excavation.

Containment-Based Multiple PCC Voltage Regulation Strategy for Communication Link and Sensor Faults

The distributed AC microgrid(MG) voltage restoration problem has been extensively studied. Still, many existing secondary voltage control strategies neglect the co-regulation of the voltage at the point of common coupling(PCC) in the AC multi-MG system(MMS). When an MMS consists of sub-MGs connected in series, power flow between the sub-MGs is not possible if the PCC voltage regulation relies on traditional consensus control objectives. In addition, communication faults and sensor faults are inevitable in the MMS. Therefore, a resilient voltage regulation strategy based on containment control is proposed.First, the feedback linearization technique allows us to deal with the nonlinear distributed generation(DG) dynamics, where the PCC regulation problem of an AC MG is transformed into an output feedback tracking problem for a linear multi-agent system(MAS) containing nonlinear dynamics. This process is an indispensable pre-processing in control algorithm design. Moreover, considering the unavailability of full-state measurements and the potential faults present in the sensors, a novel follower observer is designed to handle communication faults. Based on this, a controller based on containment control is designed to achieve voltage regulation. In regulating multiple PCC voltages to a reasonable upper and lower limit, a voltage difference exists between sub-MGs to achieve power flow. In addition, the secondary control algorithm avoids using global information of directed communication network and fault boundaries for communication link and sensor faults. Finally, the simulation results verify the performance of the proposed strategy.

Flexural Property of String Beam of Pre-Stressed Glulam Based on Influence of Regulation and Control

Applying pre-stress in glulam beam can reduce its deformation and make full use of the compressive strength of wood.However,when the glulam with low strength and the pre-stressed steel with high strength form combined members,materials of high strength can’t be fully utilized.Therefore,this study puts forward the idea of regulating and controlling string beam of pre-stressed glulam.By regulating and controlling the pre-stress,a part of the load borne by the wood is allocated to the pre-stressed tendon,which is equivalent to completing a redistribution of internal force,thus realizing the repeated utilization of the wood strength and the full utilization of the strength of the high-strength pre-stressed tendon.The bending experiments of 10 beams under 5 working conditions are carried out.The failure mode,bearing capacity and deformation of the beams are analyzed.The results show that 90%of beams are deformed under compression.The ultimate load of the regulated and controlled beam is obviously larger than that of the unregulated beam,and the ultimate load of the beam increases with the increase of the degree of regulation and control.Compared with that of the unregulated beams,the ultimate load of beams regulated by 7.5%-30%increases by 25.42%-65.08%,and the regulated and controlled effect is obvious.With the increase of the regulation and control amplitude of pre-stress,the stiffness of string beam of pre-stressed glulam increases.In addition,with the increase of the regulation and control amplitude,the compression height of the beam increases before the failure,and it reaches the state of full-section compression at the time of failure,giving full play to the compressive property of the glulam.At the end of the experiment,the constitutive relation which can reflect the anisotropy of the wood is established combined with the experimental data.The finite element analysis of the beam under 7 working conditions is carried out by using ABAQUS finite element program,and the influence of the regulation and control amplitude on the stress distribution and ultimate bearing capacity of the beam is discussed.

Distributed Robust Containment Control of Linear Heterogeneous Multi-Agent Systems:An Output Regulation Approach

In this paper,we consider the robust output containment problem of linear heterogeneous multi-agent systems under fixed directed networks.A distributed dynamic observer based on the leaders’measurable output was designed to estimate a convex combination of the leaders’states.First,for the case of followers with identical state dimensions,distributed dynamic state and output feedback control laws were designed based on the state-coupled item and the internal model compensator to drive the uncertain followers into the leaders’convex hull within the output regulation framework.Subsequently,we extended theoretical results to the case where followers have nonidentical state dimensions.By establishing virtual errors between the dynamic observer and followers,a new distributed dynamic output feedback control law was constructed using only the states of the compensator to solve the robust output containment problem.Finally,two numerical simulations verified the effectiveness of the designed schemes.

Impact of environmental regulations on the efficient control of industrial pollution in China

The continuous progress of industrialization is a fundamental cause of China’s increasingly severe environmental pollution problem.Improving the efficiency of industrial pollution control is an inevitable choice to effectively decrease pollution emissions,thus winning the battle of pollution prevention and control.In this paper,we used the stochastic frontier analysis(SFA)model to measure the provincial efficiency of industrial pollution control based on the input and output data of industrial pollution control of 29 administrative provinces in China from 2000 to 2017.On this basis,a spatial econometric model was used to explore the influence of environmental regulation intensity on the efficiency of industrial pollution control.In addition,the spatial spillover effect of pollution reduction was thoroughly examined.The results show that:(1)The efficiency of industrial pollution control in China has improved year by year,but the overall efficiency is still low,with the average value increasing from 0.165 in 2000 to 0.309 in 2017.Furthermore,there is significant regional heterogeneity with the highest efficiency level in the east and lowest efficiency level in the west.(2)By increasing the financial and material input,the efficiency of industrial pollution control has increased.However,the increase of human input has not been so helpful.(3)The global Moran’s I index is significantly greater than zero,indicating a strong spatial correlation and agglomeration in the efficiency of industrial pollution control,which is reflected in high-high agglomeration in the eastern region and low-low agglomeration in the western region.(4)Stringent environmental regulation has a positive effect on improving the efficiency of industrial pollution control.It also imposes a positive spatial spillover effect,indicating a strategic interaction and coordination of regional pollution control.In line with this,related proposals have been made to optimize the investment structure for environmental pollution control,establish a flow mechanism for the factor market,and strengthen the environmental responsibility awareness of state-owned enterprises.On this basis,we expect to provide a policy for improving the efficiency of industrial pollution control and promoting regional joint pollution control in China.

Controlling the dynamic behavior of decentralized cluster through centralized approaches

How to control the dynamic behavior of large-scale artificial active matter is a critical concern in experimental research on soft matter, particularly regarding the emergence of collective behaviors and the formation of group patterns. Centralized systems excel in precise control over individual behavior within a group, ensuring high accuracy and controllability in task execution. Nevertheless, their sensitivity to group size may limit their adaptability to diverse tasks. In contrast, decentralized systems empower individuals with autonomous decision-making, enhancing adaptability and system robustness. Yet, this flexibility comes at the cost of reduced accuracy and efficiency in task execution. In this work, we present a unique method for regulating the centralized dynamic behavior of self-organizing clusters based on environmental interactions. Within this environment-coupled robot system, each robot possesses similar dynamic characteristics, and their internal programs are entirely identical. However, their behaviors can be guided by the centralized control of the environment, facilitating the accomplishment of diverse cluster tasks. This approach aims to balance the accuracy and flexibility of centralized control with the robustness and task adaptability of decentralized control. The proactive regulation of dynamic behavioral characteristics in active matter groups, demonstrated in this work through environmental interactions, holds the potential to introduce a novel technological approach and provide experimental references for studying the dynamic behavior control of large-scale artificial active matter systems.

Self-Triggered Set Stabilization of Boolean Control Networks and Its Applications

Set stabilization is one of the essential problems in engineering systems, and self-triggered control(STC) can save the storage space for interactive information, and can be successfully applied in networked control systems with limited communication resources. In this study, the set stabilization problem and STC design of Boolean control networks are investigated via the semi-tensor product technique. On the one hand, the largest control invariant subset is calculated in terms of the strongly connected components of the state transition graph, by which a graph-theoretical condition for set stabilization is derived. On the other hand, a characteristic function is exploited to determine the triggering mechanism and feasible controls. Based on this, the minimum-time and minimum-triggering open-loop, state-feedback and output-feedback STCs for set stabilization are designed,respectively. As classic applications of self-triggered set stabilization, self-triggered synchronization, self-triggered output tracking and self-triggered output regulation are discussed as well. Additionally, several practical examples are given to illustrate the effectiveness of theoretical results.

Optimal Cooperative Secondary Control for Islanded DC Microgrids via a Fully Actuated Approach

DC-DC converter-based multi-bus DC microgrids(MGs) in series have received much attention, where the conflict between voltage recovery and current balancing has been a hot topic. The lack of models that accurately portray the electrical characteristics of actual MGs while is controller design-friendly has kept the issue active. To this end, this paper establishes a large-signal model containing the comprehensive dynamical behavior of the DC MGs based on the theory of high-order fully actuated systems, and proposes distributed optimal control based on this. The proposed secondary control method can achieve the two goals of voltage recovery and current sharing for multi-bus DC MGs. Additionally, the simple structure of the proposed approach is similar to one based on droop control, which allows this control technique to be easily implemented in a variety of modern microgrids with different configurations. In contrast to existing studies, the process of controller design in this paper is closely tied to the actual dynamics of the MGs. It is a prominent feature that enables engineers to customize the performance metrics of the system. In addition, the analysis of the stability of the closed-loop DC microgrid system, as well as the optimality and consensus of current sharing are given. Finally, a scaled-down solar and battery-based microgrid prototype with maximum power point tracking controller is developed in the laboratory to experimentally test the efficacy of the proposed control method.

Predictive active control of building structures using LQR and artificial intelligence

This study presents a neural network-based model for predicting linear quadratic regulator(LQR)weighting matrices for achieving a target response reduction.Based on the expected weighting matrices,the LQR algorithm is used to determine the various responses of the structure.The responses are determined by numerically analyzing the governing equation of motion using the state-space approach.For training a neural network,four input parameters are considered:the time history of the ground motion,the percentage reduction in lateral displacement,lateral velocity,and lateral acceleration,Output parameters are LQR weighting matrices.To study the effectiveness of an LQR-based neural network(LQRNN),the actual percentage reduction in the responses obtained from using LQRNN is compared with the target percentage reductions.Furthermore,to investigate the efficacy of an active control system using LQRNN,the controlled responses of a system are compared to the corresponding uncontrolled responses.The trained neural network effectively predicts weighting parameters that can provide a percentage reduction in displacement,velocity,and acceleration close to the target percentage reduction.Based on the simulation study,it can be concluded that significant response reductions are observed in the active-controlled system using LQRNN.Moreover,the LQRNN algorithm can replace conventional LQR control with the use of an active control system.