Optimization Of Control Strategy Research Articles

An Optimal Hierarchical Control Strategy for 4WS-4WD Vehicles Using Nonlinear Model Predictive Control

Advanced driving algorithms, control strategies, and their optimization in self-driving vehicles in various scenarios are hotspots in current research; 4WS-4WD (four-wheel steering and four-wheel drive) is another hotspot in the study of new concept models; and the nonlinear dynamic characteristics of self-driving vehicles (AVs) are prominent in the fast cornering mode, which leads to a significant reduction in the accuracy and stability of trajectory tracking. Based on these research backgrounds, this paper proposes a control strategy optimization idea based on the 4WS4WD vehicle and its optimization model. The main content includes the establishment of a 3D vehicle model that takes into account vehicle load transfer and position change, and the establishment of a hierarchical control strategy based on the optimized NMPC and 4WS4WD models. The controller consists of two parts: an upper tracking controller based on the new vehicle model and NMPC, and a lower decoupled controller. The tracking control effect of the algorithmic control strategy based on the model and controller is validated in the high-speed serpentine motion mode and double-shift linear motion mode on the joint simulation platform of Car Sim and Simulink.

Stepper motor open-loop control system modeling and control strategy optimization

Stepper motor open-loop control system modeling and control strategy optimization

Research on the Path of Cost Control and Economic Benefit Enhancement in Construction Engineering Projects

Abstract The increasingly competitive market situation in the construction industry requires that construction enterprises strengthen the cost control of construction projects in order to improve the economic efficiency of enterprises. This paper is based on the improved genetic algorithm to realize the optimization of the cost control strategy of the construction project and effectively overcome the problems of weak cost control consciousness and high material procurement cost in the previous cost control. A construction company is selected as the object for the case study, and the genetic algorithm is used to calculate and analyze the cost control of the construction company. The return on investment, net present value, and internal rate of return are used as indicators to measure the economic benefits before and after optimizing cost control strategies. The improved genetic algorithm calculates that among the cost control factors of the construction company, procurement management, and field operation have a high probability of being selected in the genetic calculation, and the final project cost is 36.7849 million yuan through the genetic algorithm, which achieves the goal of project cost control. At the same time, this paper finds that cost control has a significant positive effect on the improvement of economic efficiency, and the economic efficiency of this construction company before and after the optimization of the cost control strategy is significantly improved.

Bi-level Optimization of Sizing and Control Strategy of Hybrid Energy Storage System in Urban Rail Transit Considering Substation Operation Stability

Bi-level Optimization of Sizing and Control Strategy of Hybrid Energy Storage System in Urban Rail Transit Considering Substation Operation Stability

Control strategy and capacity optimization of energy-storage-based railway power conditioner

Electrified railroad has the characteristics of high safety factors, high comfort, large transportation capacity, and less time-consuming, which is an effective means to solve traffic congestion. However, with the rapid development of China’s electrified railroad, harmonic, negative sequence and other power quality problems have also been widely concerned, while more and more regenerative braking energy in the traction power supply system can not be effectively utilized. The input of railroad power regulators makes the power quality problem be solved effectively, this paper studies the control strategy of traditional railroad power regulators. Combined with the actual working conditions of railroad vehicles, the simulation model of traction network, vehicles, and railroad power conditioner is established, and the load characteristics of traction substation are simulated by this model. Secondly, for a domestic substation field collection data processing to obtain the actual train operation load changes, to the battery energy storage device life within the maximum economic returns as the optimization goal, for the peak load reduction judgment threshold and the capacity of the battery energy storage device through the genetic algorithm to process the data of previous years to optimize the design.

Optimization of Control Strategy for Fuel Cell Vehicles by Integrating Fuzzy Algorithm

Optimization of Control Strategy for Fuel Cell Vehicles by Integrating Fuzzy Algorithm

UKF-Based Optimal Tracking Control for Uncertain Dynamic Systems With Asymmetric Input Constraints.

To enhance system robustness in the face of uncertainty and achieve adaptive optimization of control strategies, a novel algorithm based on the unscented Kalman filter (UKF) is developed. This algorithm addresses the finite-horizon optimal tracking control problem (FHOTCP) for nonlinear discrete-time (DT) systems with uncertainty and asymmetric input constraints. An augmented system is constructed with asymmetric control constraints being considered. The augmented problem is addressed with a DT Hamilton-Jacobi-Bellman equation (DTHJBE). By analyzing convergence with regard to the cost function and control law, the UKF-based iterative adaptive dynamic programming (ADP) algorithm is proposed. This algorithm approximates the solution of the DTHJBE, ensuring that the cost function converges to its optimal value within a bounded range. To execute the UKF-based iterative ADP algorithm, the actor-estimator-critic framework is built, in which the estimator refers to system state estimation through the application of UKF. Ultimately, simulation examples are presented to show the performance of the proposed method.

Power Control Strategy Optimization to Improve Energy Efficiency of the Hybrid Electric Propulsion Ship

Power Control Strategy Optimization to Improve Energy Efficiency of the Hybrid Electric Propulsion Ship

Model Predictive Control Optimization Strategy for Integrated Energy Systems: A Two-stage Dual-loop Optimization Framework

Model Predictive Control Optimization Strategy for Integrated Energy Systems: A Two-stage Dual-loop Optimization Framework

An Adaptive Congestion Control Optimization Strategy in SDN-Based Data Centers

An Adaptive Congestion Control Optimization Strategy in SDN-Based Data Centers

Landing trajectory and control optimization for helicopter encountering different tail rotor pitch lockups

In recent years, tail rotor failure has been a significant factor in helicopter accidents, contributing to around 30 % of all incidents. Among these failures, tail rotor pitch lockup accounts for nearly 2/3. However, there is currently a lack of research on the landing trajectory and control optimization for piloted helicopters facing tail rotor pitch lockup. Therefore, this paper aims to study the landing trajectory and pilot control strategy optimization during helicopter tail rotor pitch lockup. The findings of this research are expected to provide valuable insights and serve as a reference for subsequent real-time pilot-in-the-loop simulations and final flight tests. In this paper, we utilize the UH-60A helicopter as a prototype to establish a flight dynamics model and a pilot model. The aerodynamic forces and induced velocity of the main rotor are calculated using the blade element method and Pitt-Peters model. The rotor flap motion is simplified to a first-order harmonic quantity. We then formulate the problem of safe landing and control optimization as a nonlinear optimal control problem, with the cost function designed to reflect safety and feasibility during the flight and touchdown process. To solve the optimal control problem numerically, we use direct multiple shooting and sequential quadratic programming algorithms. Flight test data for the UH-60A, encompassing steady-state flight, dynamic response, and autorotation landing, are utilized to validate the accuracy of the flight dynamics model and the effectiveness of the optimal control algorithm. Finally, the paper investigates the safe landing trajectories and control strategies for the sample helicopter when encountering high tail rotor pitch lockup and low tail rotor pitch lockup, respectively. Simulation results demonstrate that when the tail rotor is stuck at a high pitch, it is advisable for pilots to execute a high-power state landing by maintaining the engine at high power while reducing forward speed and descent rate. Conversely, when the tail rotor is stuck at a low pitch, flying at an economical speed (in a low-power state) is advantageous, but it does not facilitate a safe landing thereafter. If the pilot attempts a conventional landing, the yaw rate at touchdown would be very high and potentially dangerous. In contrast, if an autorotation landing is executed, the landing will be safer with a much lower yaw rate at touchdown. The optimal landing trajectory and control process align with the recommendations from actual helicopter flight tests. The proposed method provides feasible pilot control strategies for safe landing when helicopters encounter various tail rotor pitch lockup situations. This research can serve as a reference for pilots before conducting actual flight tests.

A Comparative Study on the Performance of the Induction Motor with Fuzzy-Based Power Converters

This study investigates the influence of load conditions on grid voltage stability and the performance of a proposed compensator, encompassing a 1.5 hp 4-pole induction motor (IM) exposed to grid voltage disturbances. Through rigorous grid current analysis, our research demonstrates the effective mitigation of total harmonic distortion (THD) without necessitating passive filters. The comprehensive study covers multiple facets, including control strategy optimization, fine-tuning of control parameters, component ratings, output voltage analysis, operating principles, pulse width modulation, and the integral role of the fuzzy logic controller. Specifically, it underscores the significant impact of a Predictive Torque Control-based Diode Clamped Inverter in enhancing the dynamic and steady-state performance of the IM. The research delves into traditional PTC control methods and advanced techniques, such as fuzzy and evolutionary control, addressing the persistent challenge of reducing torque ripple under varying load conditions. By implementing model prediction control-based DCI, our method achieves rapid torque response without compromising the motor’s stator characteristics. Utilizing MATLAB’s environmental package, we thoroughly evaluate motor performance across diverse scenarios, encompassing stable, and rapid load changes. Despite inherent winding impedance challenges, our proposed approach consistently delivers satisfactory output responses, contributing to a more efficient, and resilient IM performance under diverse operating conditions.

Improving flexibility of thermal power plant through control strategy optimization based on orderly utilization of energy storage

Operational flexibility in thermal power plants has assumed a growing significance in maintaining power grid stability primarily driven by the increased penetration of intermittent renewable energy sources. Substantial energy resides within the deaerator and boiler subsystems of thermal power plants, and optimizing the utilization of the stored energy is crucial for enhancing the operational flexibility of these plants. A novel coordinated control strategy, informed by the characteristics of distributed energy storage and power ramping stages of thermal power plants, is proposed. This control strategy systematically activates energy reserves within the deaerator, regenerative heaters, and boiler subsystems through load decomposition, valve regulation, and revised coal feeding rate, respectively. Control performance is subsequently assessed within a reference scenario. The results demonstrate a notable improvement in the control performance. The variations in the reheat steam temperature, main steam pressure, and output power are reduced by 2.0 °C, 0.47 MPa, and 2.4 MW, respectively. Moreover, the maximum power ramp rate increases from 1.5 % to 5.5 % Pe0 min−1. Furthermore, a substantial reduction in coal consumption of up to 7.09 % is achieved through the orderly utilization of energy storage. This study provides a comprehensive reference for enhancing the operational flexibility of power plants.

A deterministic robust control with parameter optimization for uncertain two-wheel driven mobile robot

The uncertainty in mobile robot greatly affects control accuracy. This makes it difficult to apply to more rigorous high-precision engineering fields. Therefore, the fuzzy set theory is introduced to describe the uncertainty. Based on that, the fuzzy mobile robot system is established. The virtual speed controller using backstepping method is designed. Then, a robust control method is proposed to guarantee the uniform boundedness and uniform ultimate boundedness of the controlled system. Furthermore, the balance optimization problem of the performance and cost of the controlled system is explored. By minimizing the performance index containing fuzzy numbers, the optimal control parameter is obtained. Compared with the linear quadratic regulator algorithm, which is the representative optimal robust controller, the proposed control method and optimization strategy based on fuzzy set theory are verified to be effective. The control accuracy is further improved.

Metal hydrides in hydrogen storage: optimization of dynamic control strategies

Metal hydrides have emerged as a promising solution for efficient hydrogen storage in solid matter. While the charging and discharging kinetics of these systems are well-known, dynamic control strategies from a system’s perspective still need a detailed analysis by the scientific community. In this research work, a metal hydrides system and its dynamic controls have been numerically studied. AB2-type metals (ZrMn2) are involved as a storage medium, which is coupled to a conditioning system via a heat pump and a hydrogen compressor; therefore, both operating temperature and pressure can be controlled. Results showed that hydrogen pressure is a fundamental component in accelerating reaction dynamics and increasing stored mass. However, it is also the most energy-intensive component. The use of a conditioning system, which works at a proper set temperature, can reduce the hydrogen compressor energy to achieve the same performance, although requiring higher power input from the heat pump’s compressor. Furthermore, the operational strategy must be chosen based on either the minimization of charging/discharging time or energy expenses.

Design and Optimization of Low Impact Shift Control Strategy for Aviation Transmission Power System Based on Response Surface Methodology

The utilization of a variable-speed power system significantly improves the forward flight speed and cruising range of the helicopter. Nevertheless, the shock of speed and torque during the shift process brings stability and safety problems that cannot be ignored. Thus, swift and stable shift control is a key issue in the research on aviation power systems. This study focuses on the design and optimization of low-impact shift control strategies for a variable-speed power system, which involves multiple control variables, long adjustment times, and uncontrollable risks due to the nonsteady state. A comprehensive power system model that integrates the engine, a two-speed dual-clutch transmission system, and the main rotor was proposed. By selecting the engine fuel flow, friction clutch hydraulic pressure, and rotor pitch angle as input signals, regression fitting models between the input signals’ starting time points and speed or torque shock were obtained using Response Surface Methodology (RMS). The interaction effect of multiple time series was analyzed, and four kinds of low-impact nonlinear programming multi-objective optimized models for speed or torque are proposed. The results indicate that the P values of the RMS fitting models at upshift and downshift are less than 0.0001 and 0.05, respectively, which are highly significant and can effectively predict the shift dynamic response; under the optimized upshift and downshift control strategy, the speed and torque shock are reduced by 5–10%.

Performance analysis and optimization of a solar assisted heat pump concept

Solar-assisted heat pumps have become a popular choice for efficient and environmentally-friendly heating and hot water production. This article introduces a unique concept of integrating a solar thermal facade into buildings to provide the cold source for a heat pump, which is a novel approach compared to other available solutions. While accurate sizing is crucial for efficient system operation, evaluating the potential benefits of better control strategies is also important because these strategies can bring significant benefits to the system. However, at present, there is a shortage of tools that can facilitate accurate sizing and effective evaluation of various control strategies for such systems. This article explores the benefits and challenges associated with this innovative technology, highlighting the need for developing models with a good representation of the system behavior and accurate performance estimation. A parametric study will be conducting on the principal components sizing for various climates in France. The aim is to gain a comprehensive understanding of the installation’s potential performance, with the optimization of sizing and control strategies to be performed at a later stage.

Effect of roughness on droplet motion in a capillary channel: A numerical study

This study presents droplet dynamics in a rough capillary channel. Prior studies investigating the effect of roughness on fluid flow have mainly considered a continuous phase whose behavior is different from a discontinuous phase, i.e., an oil slug. To explore the dynamic behavior of droplet motion across a rough channel, a direct numerical simulation of in a three-dimensional channel is performed. Three models have been considered: model A had a rough surface only on the bottom walls, model B on both the bottom and top walls, and model C on all walls. The results show that in contrast with common observations, roughness promotes droplet mobility in comparison with smooth walls. The presence of roughness results to an additional energy required to move the droplet, and the degree of confinement increases with the roughness; thus, the difficult of mobilization increases with the increase in roughness. Different roughness parameter effects have been investigated. The results have shown that the critical pressure increases with the increase in the pillar's height and decreases with the pillars spacing. The offset leads to a decrease in flow resistance for larger contact angles. We noted also that it is more difficult to mobilize a discontinuous phase in a neutral-wet surface condition. Furthermore, discontinuous pillars in the lateral direction led to much higher resistance. Through our comprehensive numerical study, we provide valuable insights into the impact of roughness in capillary channels. These findings can be used as guidelines for designing droplet flow on complex and rough surfaces, such as microfluidic devices, and hold significant relevance in the optimization of droplet control strategies in enhanced oil recovery methods.

A Consensus-Based Distributed Secondary Control Optimization Strategy for Hybrid Microgrids

In this paper, a new consensus-based distributed secondary control (DSC) strategy is proposed for frequency control, dc-voltage regulation, and optimal dispatch (OD) in isolated hybrid ac/dc-microgrids (HMGs). At the same time, all the units are maintained within limits. The proposed control scheme dispatches the distributed generators (DGs) within the microgrid in compliance with the Karush-Kuhn-Tucker (KKT) conditions of a linear optimal power flow (OPF) formulation. Furthermore, the power through the interlinking converters (ICs) is also dispatched to help minimize the total operation cost of the microgrid. The controllers rely on local measurements and information from neighbouring devices at both sides of the microgrid (DGs and ICs). Thus, unlike conventional methods, the microgrid is considered a single entity and not as three independent systems interacting with one another, and the OD is calculated considering both the ac-DGs and dc-DGs. Extensive simulations demonstrate a good performance of the controller amid load step changes and unit congestion, driving the system to an optimal economic operation.

How to improve the energy performance of mid-deep geothermal heat pump systems: Optimization of heat pump, system configuration and control strategy

Mid-deep borehole heat exchangers (MDBHEs) extract heat from geothermal energy with depth of 2–3 km, and provide high-temperature heat source for heat pump heating system. To improve the energy performance, this paper conducted optimization analysis on heat pump, system configuration and control strategy. Firstly, the energy efficiency and regulation characteristic of magnetic bearing variable-speed centrifugal heat pump (MBC-HP) was examined through field tests and simulation analysis. Results showed that MBC-HP performed efficiently with wide-range variation of heating load and compression ratio. And average COP of MBC-HP reached 6.21 during heating season. Besides, as evaporator-side water temperature difference (dTe) reached about 10 °C, two-stage MBC-HPs connected in series was raised to fit the large dTe, and the average COP of heat pump was improved to 6.97. Furthermore, the evaporator-side water flow rate (Ge) affected the energy efficiency of heat pump system and heat transfer performance of MDBHEs significantly. Thus the water pumps were recommended to be connected in parallel and then connected with heat pumps. Then the numbers and frequency of water pumps should be regulated to maintain dTe about 9.0 °C. Compared with control strategy of constant Ge, the COPs of heat pump system increased to 5.28, showing 18.7 % improvement.