An experimental study on dynamic random variation of population size

Comparing with the serial ones, parallel manipulators have potential advantages in terms of high stiffness, accuracy and speed (Merlet, 2001). Especially the high accuracy and speed performances make the parallel manipulators widely applied to the following fields, like the pick-and-place operation in food, medicine, electronic industry and so on. At present, the key issues are the ways to meet the demand of high accuracy in moving process under the condition of high speed. In order to realize the high speed and accuracy motion, it’s very important to design efficient control strategies for parallel manipulators. In literatures, there are two basic control strategies for parallel manipulators (Zhang et.al., 2007): kinematic control strategies and dynamic control strategies. In the kinematic control strategies, parallel manipulators are decoupled into a group of single axis control systems, so they can be controlled by a group of individual controllers. Proportional-derivative (PD) control(Ghorbel et.al., 2000; Wu et.al., 2002), nonlinear PD (NPD) control (Ouyang et.al., 2002; Su et.al., 2004), and fuzzy control (Su et.al., 2005) all belong to this type of control strategies. These controllers do not always produce high control performance, and there is no guarantee of stability at the high speed. Unlike the kinematic control strategies, full dynamic model of parallel manipulators is taken into account in the dynamic control strategies. So the nonlinear dynamics of parallel manipulators can be compensated and better performance can be achieved with the dynamic strategies. The traditional dynamic control strategies of parallel manipulators are the augmented PD (APD) control and the computed-torque (CT) control (Li & Wu, 2004; Cheng et.al., 2003; Paccot et.al., 2009). In the APD controller (Cheng et.al., 2003), the control law contains the tracking control term and the feed-forward compensation term. The tracking control term is realized by the PD control algorithm. The feed-forward compensation term contains the dynamic compensation calculated by the desired velocity and desired acceleration on the basis of the dynamic model. Compared with the simple PD controller, the APD controller is a tracking control method. However, the feed-forward compensation can not restrain the trajectory disturbance effectively, thus the tracking accuracy of the APD controller will be decreased. In order to solve this problem, the CT controller including the velocity feed-back is proposed based on the PD controller (Paccot et.al., 2009). The CT control method yields a controller that suppresses disturbance and tracks desired trajectories uniformly in all configurations of the manipulators. Both the APD controller and the CT controller contain two parts including the PD control term and the dynamic compensation term. For the

In this study, dynamic traffic control strategies, namely dynamic ramp metering and dynamic speed limit control, have been examined through microscopic traffic simulation based on site measurements. In this context, the traffic flow data at a particular highway intersection have been analyzed to determine the pattern of the traffic. Then, the traffic model has been built in a traffic micro-simulation software and calibrated with the field data. The foci of the study are to measure the efficiency of the dynamic traffic control strategies and to compare it with the uncontrolled case considering various performance indicators such as total travel time, average delay time per vehicle, and average number of stops per vehicle. For the dynamic ramp metering strategies, the ALINEA (Asservissement Lineaire d’Entree Autoroutiere - French for Linear Utilization for Highway Entrances) control algorithm is implemented with different fixed-time cycle lengths. It has been observed that various ramp metering implementations decreased the average delay time per vehicle up to 30%. The dynamic speed limit control strategies are set according to the occupancy rates that are measured at the bottleneck downstream. The examined speed limit control strategies decreased the average delay time per vehicle to around 7%. The results also revealed that the implemented dynamic traffic control strategies help alleviate congestion by increasing the capacity of the bottleneck section.

In this study, dynamic traffic control strategies, namely dynamic ramp metering and dynamic speed limit control, have been examined through microscopic traffic simulation based on site measurements. In this context, the traffic flow data at a particular highway intersection have been analyzed to determine the pattern of the traffic. Then, the traffic model has been built in a traffic micro-simulation software and calibrated with the field data. The foci of the study are to measure the efficiency of the dynamic traffic control strategies and to compare it with the uncontrolled case considering various performance indicators such as total travel time, average delay time per vehicle, and average number of stops per vehicle. For the dynamic ramp metering strategies, the ALINEA (Asservissement Lineaire d’Entree Autoroutiere - French for Linear Utilization for Highway Entrances) control algorithm is implemented with different fixed-time cycle lengths. It has been observed that various ramp metering implementations decreased the average delay time per vehicle up to 30%. The dynamic speed limit control strategies are set according to the occupancy rates that are measured at the bottleneck downstream. The examined speed limit control strategies decreased the average delay time per vehicle to around 7%. The results also revealed that the implemented dynamic traffic control strategies help alleviate congestion by increasing the capacity of the bottleneck section.

Knowledge base of dynamic risk control strategy based on immunity is a significant effect on effective analysis and defense against illegal network intrusion. How to realize the automatic understanding and processing of computers with control strategy knowledge is of great significance for quickly responding to network security risks. As a kind of knowledge representation tool, ontology can provide support for knowledge sharing, reuse and automatic computer understanding in specific fields, and has been widely used in various fields. This paper first introduces the immune-based network dynamic risk control model and network dynamic risk quantitative evaluation. And then, according to the ontology modeling method of network dynamic risk control strategy knowledge, this paper extracts domain knowledge concepts, attributes, relationships, instances, etc., and constructs domain ontology model, application ontology model, and atom ontology model for the network dynamic risk control strategy knowledge. These ontology models are represented using semantic Web ontology expression languages PDF and OWL, and are constructed using the protege ontology editing tool. Finally, the important concepts in the knowledge of network dynamic risk control strategy and the relationship between concepts are expressed in the form of graph, so as to help the network security analysts and decision makers to effectively control and make decisions.

The objective of this work is to devise an effective control system for addressing the trajectory tracking challenge in nonholonomic mobile robots. Two primary control approaches, namely kinematic and dynamic strategies, are explored to achieve this goal. In the kinematic control domain, a backstepping controller (BSC) is introduced as the core element of the control system. The BSC is utilized to guide the mobile robot along the desired trajectory, leveraging the robot’s kinematic model. To address the limitations of the kinematic control approach, a dynamic control strategy is proposed, incorporating the dynamic parameters of the robot. This dynamic control ensures real-time control of the mobile robot. To ensure the stability of the control system, the Lyapunov stability theory is employed, providing a rigorous framework for analyzing and proving stability. Additionally, to optimize the performance of the control system, a genetic algorithm is employed to design an optimal control law. The effectiveness of the developed control approach is demonstrated through simulation results. These results showcase the enhanced performance and efficiency achieved by the proposed control strategies. Overall, this study presents a comprehensive and robust approach for trajectory tracking in nonholonomic mobile robots, combining kinematic and dynamic control strategies while ensuring stability and performance optimization.

This paper presents a dynamic cancellation control strategy for the inversion stage of the recently proposed high-power-density common-neutral single-dc-bus (CN-SDB) single-phase online uninterruptible power supply (UPS). The inversion stage operates in buck or buck-boost mode depending on the polarity of the output voltage reference and produces a sinusoidal output voltage. Owing to the dual-mode nature of the inversion stage, output voltage regulation with standard feedback control results in a large dc-offset and poor total harmonic distortion (THD), which is unacceptable for practical applications. To substantially improve the output voltage dc-offset and THD, a dynamic cancellation control strategy is proposed for the buck-boost mode of the dual-mode inversion stage. An analytical model capturing the dynamics of the inversion stage with dynamic cancellation control strategy is also presented to facilitate the controller design. A 1-kVA GaN-based prototype of online UPS is designed, built, and tested, and the output voltage THD is experimentally measured across a wide output voltage range. Standard feedback control strategy results in a 10% output voltage THD whereas the dynamic cancellation control strategy offers a significant improvement of 68% and results in a 3.2% output voltage THD.

The primary focus of this study is to investigate the control strategies of a hybrid system used in hydraulic excavators. First, the structure and evaluation target of hybrid hydraulic excavators are analyzed. Then the dynamic system model including batteries, motor and engine is built as the simulation environment to obtain control results. A so-called multi-work-point dynamic control strategy, which has both closed-loop speed PI (proportion integral) control and direct torque control, is proposed and studied in the simulation model. Simulation results indicate that the hybrid system with this strategy can meet the power demand and achieve better system stability and higher fuel efficiency.

Dielectric elastomer (DE) possesses attributes such as large deformation and fast response. As a typical DE actuating structure, the multilayered DE bending actuator (MDEBA) is lightweight and can actuate in relatively low voltage without a rigid frame and pre-stretch. These attributes arouse wide research interest in the MDEBA on the application of soft robots. However, due to its large deformation and nonlinear electromechanical dynamics, the control of MDEBA remains highly challenged. Considering the large bending deformation and gravity effect, we develop an electromechanical dynamic model-based control strategy, which can adaptively compensate for the parameter uncertainties during the actuation of MDEBA. Experimental results validate that this control strategy provides highly enhanced control performance compared to the proportional integral derivative (PID) controller. The electromechanical modeling method and dynamic control strategy may guide the further study of MDEBA, soft robots, and flexible devices.

Model-based Dynamic Optimal Control of an Ejector Expansion CO2 Heat Pump Coupled with Thermal Storages

Using zeotropic mixtures as working fluids can improve the thermal efficiency of Organic Rankine cycle (ORC) power plants for utilising geothermal energy. However, currently, such ORC systems cannot regulate the composition of zeotropic mixtures when their operating conditions change. A composition-adjustable ORC system could potentially improve the thermal efficiency by closely matching the cycle to the changing ambient conditions provided that the composition of the working fluid mixture can be adjusted in an economic way. In this paper, a dynamic composition control strategy has been proposed and analysed for such a composition-adjustable ORC system. This method employs a distillation column to separate the two components of the mixture, which can then be pumped back to the main ORC system to adjust the composition of the zeotropic mixture to the required level according to the ambient temperature. The dynamic composition control strategy is simulated using an optimisation algorithm. The design method of the distillation column is presented and its dynamic response characteristics have been analysed using Aspen Plus Dynamics. The results indicate that the average power output can be significantly improved using a composition-adjustable ORC system when the ambient temperature decreases. The size of the distillation system is relatively small and its energy (mainly thermal) consumption is only around 1% of the system's input heat. The research results also show that the dynamic response characteristics of the distillation system can satisfy the requirements of the ORC system.

Efficient utilization of both glucose and xylose, the two most abundant sugars in biomass hydrolysates, is one of the main objectives of biofermentation with lignocellulosic materials. The utilization of xylose is commonly inhibited by glucose, which is known as glucose catabolite repression (GCR). Here, we report a GCR-based dynamic control (GCR-DC) strategy aiming at better co-utilization of glucose and xylose, by decoupling the cell growth and biosynthesis of riboflavin as a product. Using the thermophilic strain Geobacillus thermoglucosidasius DSM 2542 as a host, we constructed additional riboflavin biosynthetic pathways that were activated by xylose but not glucose. The engineered strains showed a two-stage fermentation process. In the first stage, glucose was preferentially used for cell growth and no production of riboflavin was observed, while in the second stage where glucose was nearly depleted, xylose was effectively utilized for riboflavin biosynthesis. Using corn cob hydrolysate as a carbon source, the optimized riboflavin yields of strains DSM2542-DCall-MSS (full pathway dynamic control strategy) and DSM2542-DCrib (single-module dynamic control strategy) were 5.3- and 2.3-fold higher than that of the control strain DSM 2542 Rib-Gtg constitutively producing riboflavin, respectively. This GCR-DC strategy should also be applicable to the construction of cell factories that can efficiently use natural carbon sources with multiple sugar components for the production of high-value chemicals in future.

This paper investigates the aperiodically intermittent adaptive dynamic event-triggered control strategy for general linear multi-agent systems. The aperiodically intermittent adaptive event-triggered control inherits the respective advantages of aperiodically intermittent control strategy, dynamic event-triggered control strategy and adaptive control strategy, which improves communication efficiency, reduces control update frequency and is closer to the practical situations. To reach leader-following consensus and save more control resources, a distributed aperiodically intermittent adaptive dynamic event-triggered scheme is devised, in which the transmission channels among agents only open if the local event-trigger condition is satisfied in predefined time intervals. Besides, the triggering mechanism can get rid of continuous inter-agent communication for monitoring the triggering condition and appropriately tune the feedback gains in real applications. With aid of the matrix theory, stability red theory of switching systems and Lyapunov function, some sufficient criteria are deduced. Finally, the effectiveness for the designed control strategies is validated by simulations.

A reasonable and effective control strategy for HEV (Hybrid Electric Vehicle) with HESS (Hybrid Energy Storage System) can improve the system efficiency and battery service life. A dynamic programming-based global optimal control strategy which fully considered the efficiency of each component in HEV is presented. To compare with the nonlinear proportion factor dynamic coordination strategy, the fuel consumption is not increased. The cycle numbers of battery are further decreased which benefits its cycle life improvement. The regenerative energy callback ratio improves 3% under the shanghai drive cycle as an example. Since this optimization algorithm considers efficiency of each subsystem, the efficiency optimum under the selected driving cycle was realized. It can also provide a reference for the non-linear scaling factor allocation strategies to determine the scale factors.

To effectively suppress the horizontal vibration of high-speed elevator cars caused by uncertainties such as unevenness of guide rails and piston wind in the shaft, a disturbance observer-based dynamic fuzzy sliding-mode control strategy is proposed, which is a combination of a dynamic fuzzy sliding-mode controller and an optimal nonlinear disturbance observer. First, a horizontal vibration dynamics model of the semi-active high-speed elevator car system is established, and the external disturbance of the airflow obtained by the dynamic grid technique and the uneven excitation of the guide rail are jointly applied as inputs to the dynamical model. Then, an active fuzzy sliding-mode controller is established, approximating the local optimum of the sliding mode surface parameters using a differential evolutionary algorithm, and the sliding mode surface is fuzzified to estimate the switching gain dynamically; next, a disturbance observer is designed by the response of the semi-active car system dynamics model to monitor and estimate the unpredictable state and compensate for the effect of external disturbances on the car system. The stability analysis shows that making the system's dynamic response converge at the origin is a Lyapunov stable process. In addition, real elevator experiments are conducted to analyze the horizontal vibration characteristics of the car system and verify the model. Finally, considering the limitations of actuators in real conditions, the simulation experiments are carried out under random excitation and pulse excitation respectively, and their results show that the proposed control strategy reduces the root mean square value of vibration acceleration by more than 70% and the output active control force is more stable, indicating that the proposed control strategy can effectively suppress the horizontal vibration of high-speed elevators.

To meet the rapid changes in power demand, and more efficient use of PEM fuel cell power supply, the equivalent hydrogen consumption minimization (EHCM) based dynamic penalty control (DPC) strategy was proposed for the modern PEMFC-LIB-SC hybrid tramway. And an effective informed adaptive based particle searching optimization (EIA-PSO) algorithm which is more robust in terms of global search capability and local search precision was utilized to optimize the derived parameter clusters to effectively achieve the optimization of equivalent hydrogen consumption. The results demonstrated that the proposed control strategy could realize the operation stabilization of the overall hybrid power system during the simulated driving cycle. Finally, the comparisons with other control strategies verify that the proposed energy management system can achieve better performance of the overall hybrid tramway.