Hierarchical Control Method Research Articles

Hierarchical Control of Trajectory Planning and Trajectory Tracking for Autonomous Parallel Parking

For the parallel parking problem in narrow space, this paper proposes a trajectory tracking control method with a novel trajectory planning layer for autonomous parallel parking based on a numerical optimization algorithm and model predictive control. In the trajectory planning layer, the vehicle kinematics model suitable for the low-velocity parking scene is established. Considering the vehicle physical constraints, boundary condition constraints, and obstacle avoidance constraints during the parking process, the parking trajectory planning task is described as an optimal control problem, further transformed into a nonlinear programming problem by Gauss pseudo-spectral method. Taking the shortest parking completion time as the optimization objective function, the parking trajectories of the large, medium and small parking spaces are obtained, respectively. A parking trajectory tracking controller based on the model predictive control algorithm is designed in the trajectory tracking control layer. The linear error model is used as the prediction model, and the quadratic programming is adopted as the rolling optimization algorithm in the tracking controller. The velocity and front-wheel swing angle are obtained as control signals for parking trajectory tracking. Through CarSim and Simulink's co-simulation, the feasibility and effectiveness of the proposed parallel parking trajectory planning and tracking control method are verified. The co-simulation results show that the maximum tracking errors of horizontal and longitudinal positions are less than 0.15m. The maximum tracking errors of heading angle are less than 2° under three different parking spaces. Real vehicle tests are carried out to verify the effectiveness of the proposed hierarchical control method. The test results show that the vehicle can park in the parking space safely, quickly and accurately when the actual parking space is detected. The proposed method can plan the parking trajectory with the constraints and the shortest time and control the vehicle to complete the parking operation accurately along the planned trajectory.

An IoT-based Hierarchical Control Method for Greenhouse Seedling Production

The development of agriculture modernization leads to a flourish in high-tech equipment agricultural production, IoT-based greenhouse seedling production is the most presentative one. However, for the great majority of the seedling production factories, the data stream collected from IoT sensors only be applied for display, failing to assist the resource utilization and order target completion. To fill this gap, this paper provides an IoT-based system implementation architecture and a hierarchical control method for greenhouse seedling production, which make use of history monitoring data, real-time monitoring data, and seedling growth model, aiming at achieving the target growth along the predefined timeline as well as saving the additional energy cost. The proposed method is easy to implement in practical production and offers a valuable reference to other precise agricultural projects.

Hierarchical optimization control based on crop growth model for greenhouse light environment

It is of great significance to study the optimization control of greenhouse light environment that can meet the demands of crop growth and reduce the regulation cost to improve the production efficiency and economic benefits of greenhouse crops. However, due to the complexity of the actual optimization control problem of greenhouse light environment, such as multi-objective, high dimensionality and numerous constraints, the optimization control of greenhouse light environment is still a challenging research topic. Therefore, a hierarchical optimization control method based on crop growth model is proposed, which divides the optimization control problem of light environment into two levels, namely optimal-level and control-level. This method simplifies the computational complexity of the original optimization control problem of light environment by means of hierarchical structure, and thus realizes the solution of the optimization control problem of light environment. Meanwhile, the multi-objective optimization control of light environment is realized through the hierarchical decision-making for the control target of light environment and the operation of light supplement. Finally, taking tomato in solar greenhouse as the research object, the simulation results show that the method is effective. In addition, the average regulation cost of this method is 0.3084$, which is lower than 0.3677 $ of the optimization control method of light environment with fixed threshold as target, it further proves the energy-saving effect of the proposed optimization control method.

Two-level hierarchical optimal control for urban traffic networks

A two-level hierarchical optimal control method is proposed in this paper. At the upper level, the reference signals (set-point) are optimized with a data-driven model-free adaptive control (MFAC) method. Traffic signals are regulated with the model predictive control (MPC) with the desired reference signals specified by the upper level. The main contribution is that the set-point optimization is addressed by using the MFAC method which does not need modeling of the traffic system dynamics. Moreover, through this scheme, the planning of vehicle distribution in a road network and the operation of traffic signal control can be executed simultaneously. The effectiveness of the proposed method is testified by an urban traffic network based on MATLAB and VISSIM 9.0 and is also demonstrated by the comparison results with the back-pressure traffic signal control and traditional MPC.

Stability Coordinated Control of Distributed Drive Electric Vehicle Based on Condition Switching

The distributed drive electric vehicle is a complex hybrid system including discrete events and continuous events. In order to coordinate the longitudinal and lateral motion of the distributed drive electric vehicle, a hierarchical control method was proposed. In the upper layer, the body attitude tracking controller based on sliding mode control algorithm was established to accurately analyze the driving expectation and to track the longitudinal speed, the lateral speed, and the yaw rate of the vehicle. In the lower layer, the switching controller based on the hybrid theory was established to improve the driving stability under various working conditions. The switching controller can switch between control strategies according to the working conditions. The joint simulation was carried out under various working conditions using Simulink and CarSim software. The results showed that the controller can coordinate the longitudinal and lateral motion of the vehicle well in linear acceleration and sinusoidal acceleration conditions and can strictly track the driving expectation and maintain the desired body posture. And another, the controller can be switched according to the working conditions and control strategies accurately and smoothly and can ensure stable driving in the constant speed single lane change condition. The controller can reveal the continuous behavior characteristics of the vehicle and reflect the characteristics of discrete events by coordinating the longitudinal and lateral motion of the vehicle. It improves the stability and control performance of the distributed drive electric vehicle under various working conditions.

Torque allocation strategy for two axles four wheel drive electric vehicle with improvement of economy and stability

Two axles four wheel drive electric vehicle is an important development tendency of electric vehicle. However, how to coordinate the torque distribution between front and rear axles thus ensuring vehicle stability while maximizing motor’s efficiency still confronts great challenges. In this paper, we propose a three-layer hierarchical control method, which not only incorporates prior engineering knowledge into the control policy so as to relieve computational burden for real-time usage, but also properly deals with the priority between safety and system efficiency. Simulations are conducted to verify the effectiveness of the proposed method. Results show that the derived control policy can ensure high system efficiency when safety is guarenteed. Simultaneously, it can actively decrease the motor torque to improve vehicle stability when wheel slip occurs.

Accurate oscillatory current‐sharing in DC microgrids using distributed cooperative control method

In DC microgrids, if the oscillatory current is not shared among DGs, it may cause unallowable voltage distortion and overcurrent. In this paper, a distributed cooperative control scheme is introduced for DC microgrids in order to effectively share both the DC and the oscillatory components of current among DC sources. The hierarchical control method comprises four primary controllers namely voltage controller, conventional droop, oscillatory current droop and virtual conductance units, and three secondary controller units based on cooperative control principles. The primary controllers on each DG unit only use DGs' local information, while secondary controllers also require information of other DG units. In the secondary control part, firstly, via using the cooperative control, the DC current-sharing becomes accurate. Then, a novel droopbased oscillatory current-sharing controller unit is proposed in which by using the consensus method the error of oscillatory current-sharing is significantly reduced. A voltage observer, based on cooperative control is employed to compensate the inevitable voltage drop in DC microgrid, caused by droop controller. The voltage oscillation caused by oscillatory current-sharing unit is decreased through implementation of a virtual conductance signal applied to the inner current controller. The presented method is validated by a simulation with several cases.

Hierarchical model predictive control of wind farm with energy storage system for frequency regulation during black-start

In high wind power penetration power system, using wind farm equipped with energy storage system (WF-ESS) as black-start (BS) source needs to maintain system frequency stability when starting up ancillary machine or picking up load. A hierarchical model predictive control (HMPC) method of WF-ESS for frequency regulation during BS is proposed in this paper, which consists of two control modes: frequency regulation mode and reserve recovery mode. For the first control mode, a PI controller is used to generate reference power for WF-ESS and to recover system frequency to 50 Hz. The proposed HMPC is divided into WF level and wind turbine (WT) level to accurately track the reference power and guarantee secure operation of each WT. Considering WTs’ different operation conditions, WF level MPC distributes reference power to WTs according to the proportion of single WT reserve to total WF reserve. The ESS power is utilized as supplementary when WF output power is insufficient. The rotor speed and pitch angle constraints are included in the WT level MPC while providing frequency response. After frequency deviation is eliminated, WF and ESS are coordinated by the second control mode to avoid a second frequency drop meanwhile reserve a certain proportion of WF available power for managing potential frequency disturbances in the future. A case study is conducted to show the effectiveness of the proposed control method under both low and high wind conditions.

Research on Hybrid Energy Hierarchical Coordination Control Method for Grid-connected Micro-Grid

In order to effectively solve the problem that it is difficult to coordinate the operation state of grid-connected micro-grid, a hierarchical coordinated control method of hybrid energy in grid-connected micro-grid is proposed. The mathematical model of the relationship between system power and cost function and the hierarchical model of micro-grid are established. As optimisation objectives are provided by constructing objective functions, the information exchange and energy control between the systems are used to realise the grid connection. Simulation results show that the frequency of the proposed method is always around 50HZ, which is the closest to the planned value. The difference between the power value and the planned value is less than 1 kW, which is more in line with the actual needs than other methods. It is proved that this method can effectively control energy and ensure the smooth operation of micro-grid.

Fuzzy CMAC-Based Adaptive Scale Force Control of Body Weight Support Exoskeletons

The body weight support method of exoskeletons is useful for the rehabilitation of patients with lower limb dyskinesia and performance augmentation of elders. Rather than enhancing the human joint strength directly, the body weight support exoskeleton provides assistance by supporting part of the human body weight and thus releasing the burden experienced by human legs. This paper proposes a two-level hierarchical control method aiming to achieve task-free and strong system robustness. A scale force control method, which can be simply described as making the supporting force of the robot several times the magnitude of a human leg, is developed as the high-level controller. The low-level controller is designed as a fuzzy cerebellar model articulation controller (CMAC)-based adaptive control to enhance the system robustness. The proposed method is applied to a squat movement and a single leg stance movement and is simulated in a combined simulation environment. The results show that the exoskeleton can always provide improved support according to the foot reaction force that is controlled by the user and that the system handles model errors and external disturbances well.

An Adaptive Hierarchical Control Method for Microgrid Considering Generation Cost

Many power distribution methods of microgrid (MG) are all limited by fixed structure of MG and mathematical model, which will be out of effect once the structure changes. In order to solve the above problems, this paper proposed an adaptive hierarchical control method considering generation cost. Firstly, the distributed generators (DGs) of MG are considered as multi-agent system, and the secondary controller based on finite-time theory is constructed. Secondly, the improved gray wolf optimization (IGWO) algorithm is used as the tertiary controller to dynamically optimize the rated power of DG, and the objective function and constraints are established. Thirdly, the adaptive virtual impedance is introduced to realize accurate power sharing and the closed-loop control is formed by combining the current loop and voltage loop controllers. Finally, by dynamically optimizing the rated power, the on-line real-time optimal power distribution of MG is achieved, and the stability of the system is proved by the theories of multi-agent consistency and finite-time stability. The control method proposed in this paper accelerates the convergence speed of MG, and the calculation results have high accuracy. At the same time, the flexibility and reliability of MG are improved. The simulation model is established in Matlab/Simulink environment, and the simulation results show that the method is effective.

Modular Multi-terminal Flexible DC Micro-grid and Its Hierarchical Control Method

In the traditional DC micro-grid, the structure is complex, the control is difficult and there is no fixed networking mode. Thus the construction of micro-grid is expensive and the output is slow. In this paper, a hierarchical control method of modular multi-terminal flexible DC micro-grid is proposed, which simplifies the structure and control method of DC micro-grid and is beneficial to the construction of micro-grid. The structure of flexible multi-terminal DC micro-grid and the modularized method of network construction are discussed. The feasibility of the study is confirmed by a specific example of DC micro-grid. On the basis of the above research, the hierarchical control method of DC micro-grid, the specific control method and control logic in each layer are determined. PSCAD/EMTDC simulation is established to verify the effectiveness of the proposed theory and control method.

Hierarchical ramp metering in freeways: An aggregated modeling and control approach

This paper develops a model-based hierarchical control method for coordinated ramp metering on freeway networks with multiple bottlenecks and on- and off-ramps. The controller consists of two levels where at the upper level, a Model Predictive Control (MPC) approach is developed to optimize total network travel time by manipulating total inflow from on-ramps to the freeway network. The lower level controller distributes the optimal total inflows to each on-ramp of the freeway based on local traffic state feedback. The control method is based on a parsimonious aggregated traffic model that relates the freeway total outflow to the number of vehicles on the freeway sections.Studies on aggregated traffic modeling of networks have shown the existence of a well-defined and low-scatter Macroscopic Fundamental Diagram (MFD) for urban networks. The MFD links network aggregated flow and density (accumulation). However, the MFD of freeway networks typically exhibits high scatter and hysteresis loops that challenge the control performance of MFD-based controllers for freeways. This paper addresses these challenges by modelling the effect of density heterogeneity along the freeway and capacity drop on characteristics of freeway MFD using field traffic data. In addition, we introduce a model to predict the evolution of density heterogeneity that is essential to reproduce the dynamics of freeway MFD accurately. The proposed model is integrated as the prediction model of the MPC in the hierarchical control method.The proposed coordinated ramp metering method shows desirable performance to reduce the vehicles total time spent and eliminate congestion. The control approach is compared with other coordinated ramp metering controllers based on the MPC framework with different traffic prediction models (e.g.CTM and METANET). The outcomes of numerical experiments highlight that the MFD-based hierarchical controller (i) is better able to overcome the modeling mismatch between the prediction model and the plant (process model) in the MPC framework and (ii) requires less computation effort than other nonlinear controllers.

Coordination and Optimization of Urban Traffic Control and Path Guidance Based on Multi-Agent

With the development of society, the urbanization process is accelerating, the urban population is growing rapidly, and the traffic problems are becoming more and more prominent, which seriously affects the normal operation of the city. Transportation is the lifeblood of the city. Scientific management and control is an important way to improve the efficiency of urban traffic operation, and it is also an important symbol of urban transportation modernization, informationization and intelligence. This paper aims to study the new coordinated control method of traffic signals. Different from the traditional coordinated control method of centralized control and hierarchical control, a multi-agent distributed traffic signal coordination control system is established, which distributes the main functions of signal control to Signal control agents at various intersections reduce to the complexity of the control algorithm and improve the reliability and intelligence of the system.

Optimal Attitude Control of a Tethered System for Noncoplanar Orbital Transfer Under a Constant Thrust

The problem of an optimal attitude control is studied for a tethered system under a constant thrust in noncoplanar orbital transfer. The contributions of this article mainly include two aspects: first, a noncoplanar orbital transfer scheme and second, a closed-loop optimal control method. Based on a constant thrust, a noncoplanar orbital transfer scheme between two sun-synchronous orbits is proposed, enabling convenient engineering implementation. Compared with existing closed-loop control methods, the hierarchical finite-time attitude tracking control method is presented in the last cycle of the closed-loop optimal control to reduce the error at the final moment. A numerical case of a tethered system in noncoplanar orbital transfer is studied to demonstrate the effectiveness of the proposed control scheme.

Hierarchical control of thermostatically controlled loads oriented smart buildings

With the transition of energy systems, synergetic interaction between consumers and suppliers has been an inevitable trend. As a demand response (DR) resource, thermostatically controlled loads (TCLs) can respond to power fluctuations in power grids caused by renewable energy and load activities by means of TCLs’ characteristics of good thermal energy storage and slow-varying thermal inertia. Aggregating TCLs by clustering methods neglects the coupling of diverse thermal parameters with the scattered geographical locations of controlled TCLs, and will increase the complexity of communication systems and decrease scalability and availability of demand-side scheduling potential. This paper proposes a state transition interval matching (STIM) control strategy and a pinning control method based hierarchical framework. Considering the controlled tendency and compressor lockout of TCLs, STIM strategy achieves unified control of heterogeneous TCLs at the lower layer, which could reduce the relative error caused by a small number of high-power TCLs. Thus, the control accuracy and availability of TCLs’ scheduling potential are enhanced. What’s more, this could help reduce the complexity of communication systems among aggregators and TCLs. At the upper layer, pinning control coordinates the scheduling capacities provided by different buildings in a sparse communication network. This could enhance control stability in the event of a communication fault, and would facilitate the aggregation of newly participating buildings. The feasibility and scalability of TCLs’ participation in DR service are improved by the proposed method of hierarchical control. Finally, the validity of the proposed strategy is verified via comparison with temperature priority list strategy.

A Hierarchical Energy Balance Control Method for M3C Based on Injecting Output Frequency Circulating Currents

This paper presents a simplified hierarchical energy balance control method for a modular multilevel matrix converter (M3C) operating as a frequency changer (50–50/3 Hz) for low-frequency ac transmission system. The proposed method employs an independent energy balance control for each subconverter of the M3C with only injecting the output frequency circulating current, aiming at balancing the energy among the three arms of the subconverter. Then, the modulation technique is redesigned to balance the energy among n submodules within each arm. The proposed method simplifies the computational complexity of the M3C by considering the subconverter independently, enabling an easy and efficient way to control the M3C. The feasibility of the proposed method is evaluated with normal and dynamic operation, which includes step changes in the output frequency and voltage. The performance and effectiveness of the proposed control strategy is demonstrated by extensive simulation studies and experimentally validated using a scaled-down laboratory prototype.

Lacustrine paleoshoreline determination under established sequence stratigraphic framework and its controls on sand bodies and hydrocarbon accumulations

Abstract The lacustrine palaeoshoreline is the intersection between lake level and ancient land in geological time, and it marks the boundary between onshore deposits and subaqueous deposits. Identifying lacustrine paleoshorelines is the process of reconstructing past depositional environments. The study establishes the sequence stratigraphic framework of the Ordos Yanchang Formation based on a comprehensive analysis of seismic and well log data. The hierarchical lithological cycles is determined through Fourier transform and band-pass filtering analysis of Gramma Ray data. Subsequently, the lacustrine paleoshoreline is determined using the shoreline hierarchical control method under the established sequence stratigraphic framework, with additional evidence from cores, well logs and cutting and seismic sections. Lacustrine paleoshorelines has controlling effects on the sand bodies and hydrocarbon accumulations. For one thing, different types of paleoshoreline control the genesis of sand bodies, and the location of paleoshoreline in sag basin controls sand-body distribution. Furthermore, the migration of lacustrine paleoshoreline in sag basin indicates stacking patterns of sand bodies, and hydrocarbon accumulations.

Cyber-physical cooperative response strategy for consensus-based hierarchical control in micro-grid facing with communication interruption

Recently, more and more consensus-based hierarchical control methods are proposed in micro-grid. The main components of these methods are primary and secondary controllers. And they are usually used to adjust the output frequency and voltages of distributed energy resources. But the implementation of these methods is highly dependent on the communication network which is consisted by sensors and communicators. Once the data transmit of some sensors or communicators is interrupted, it will directly affect the control effect of hierarchical control. To solve the above problems, a cyber-physical cooperative response strategy is proposed in this paper. The main designs are as follows: (1) To solve the interruption problem among communicators, there are two defense methods proposed in the cyber layer: path planning and path reconstruction. Both methods are combined with cyber-physical hybrid vulnerability assessment and improved genetic algorithm; (2) To solve the interruption problem in the output channels of sensors, a distributed predictive compensation method combined with extreme learning machine and model predictive control is proposed in physical layer; (3) Based on the designs in (1) and (2), a novel secondary controller is proposed in this paper. Finally, the simulation results confirm the effectiveness of the proposed cooperative response strategy.

Yaw and lateral stability control for four-wheel-independent steering and four-wheel-independent driving electric vehicle

Based on the traditional four-wheel steering system, this paper combines the steer-by-wire system and four-wheel-independent driving technology to develop a new steer-by-wire four-wheel-independent steering and four-wheel-independent driving electric vehicle, which can realize four-wheel-independent steering and four-wheel-independent driving. Aiming at the steering actuator redundancy characteristics of the four-wheel-independent steering and four-wheel-independent driving vehicle, a hierarchical control method is proposed in this paper. In view of parameters perturbation of vehicle speed and tire cornering stiffness and the model uncertainty problem, the structure singular value μ is used to study the stability control of four-wheel-independent steering and four-wheel-independent driving vehicle under multiple perturbations in the upper layer, and verifies the advantages of μ controller by comparing it with H∞ control and proportional-integral-derivative control. The lower layer is aimed at the redundancy of vehicle steering actuator, an on-line reconfigurable steering angle and driving force allocation control method based on tire force optimal allocation is proposed. This method can not only optimize the tire longitudinal force and lateral force distribution under normal conditions but also reconstruct the distribution control strategy on-line under fault conditions, realizing active fault tolerance. Finally, simulations by MATLAB/Simulink and hardware-in-the-loop experiments are conducted to verify the proposed control method. The simulation results show that the designed controller can maintain good stability under the conditions of model perturbation, separation pavement, and actuator failure.