Hierarchical Control of Ride Height System for Electronically Controlled Air Suspension Based on Variable Structure and Fuzzy Control Theory

The current research of air suspension mainly focuses on the characteristics and design of the air spring. In fact, electronically controlled air suspension （ECAS） has excellent performance in flexible height adjustment during different driving conditions. However, the nonlinearity of the ride height adjusting system and the uneven distribution of payload affect the control accuracy of ride height and the body attitude. Firstly, the three-point measurement system of three height sensors is used to establish the mathematical model of the ride height adjusting system. The decentralized control of ride height and the centralized control of body attitude are presented to design the ride height control system for ECAS. The exact feedback linearization method is adopted for the nonlinear mathematical model of the ride height system. Secondly, according to the hierarchical control theory, the variable structure control （VSC） technique is used to design a controller that is able to adjust the ride height for the quarter-vehicle anywhere, and each quarter-vehicle height control system is independent. Meanwhile, the three-point height signals obtained by three height sensors are tracked to calculate the body pitch and roll attitude over time, and then by calculating the deviation of pitch and roll and its rates, the height control correction is reassigned based on the fuzzy algorithm. Finally, to verify the effectiveness and performance of the proposed combined control strategy, a validating test of ride height control system with and without road disturbance is carried out. Testing results show that the height adjusting time of both lifting and lowering is over 5 s, and the pitch angle and the roll angle of body attitude are less than 0.15°. This research proposes a hierarchical control method that can guarantee the attitude stability, as well as satisfy the ride height tracking system.

Design and evaluation of a hierarchical control architecture for an autonomous underwater vehicle

This paper researches on a kind of control architecture for autonomous undelwater vehicle （AUV）. After describing the hybrid property of the AUV control system, we present the hierarchical AUV control architecture. The architecture is organized in three layers： mission layer, task layer and execution layer. State supervisor and task coordinator are two key modules handling discrete events, so we describe these two modules in detail. Finally, we carried out a series of tests to verify this architecture The test results show that the AUV can perform autonomous missions effectively and safely. We can conclude the control architecture is valid and practical.

A New Three-Level Hierarchical Control Algorithm for Large-Scale Systems

This paper presents a new three-level hierarchical control parallel algorithm for large-scale systems by spatial and time decomposition. The parallel variable metric (PVM)method is found to be promising third-level algorithm. In the subproblems of second-level, the constraints of the smaller subproblem requires that the initial state of a subproblem equals the terminal state of the preceding subproblem. The coordinating variables are updated using the modified Newton method. the low-level smaller subproblems are solved in parallel using extended differential dynamic programmeing (DDP). Numerical result shows that comparing with one level DDP. the PVM /DDP algorithm obtains significant speed-ups.

Compensation/consumption hierarchical control strategy based on wind-solar-hydrogen coupling grid connection

In the process of grid-connected wind and solar power generation,there are problems of high rate of abandoning wind and light and insufficient energy.In order to solve these problems,we construct a grid-connected wind-solar hydrogen storage(alkaline electrolyzer(AE)-hydrogen storage tank-battery-proton exchange membrane fuel cell(PEMFC))coupled system architecture.A grid-connected compensation/consumption hierarchical control strategy based on wind-solar hydrogen coupling is proposed.During the grid-connected process of wind and solar power generation,the upper-level control allocates power reasonably to the hydrogen energy storage system by dispatching the power of wind and solar power generation.At the same time,the control strategy ensures that the pressure of the hydrogen storage tank is within the safety range limit,and the lower control completes the control of the duty cycle of the converter in the system.Due to the randomness of wind and light,the hydrogen energy storage system is divided into three working conditions,namely compensation,balance and consumption,and five working modes.The simulation results show that the hydrogen energy storage system compensates for 40%of the power shortage,and consumes 27.5%of the abandoned wind and solar energy,which improves the utilization rate of clean energy.

A Fuzzy Logic Based Supervisory Hierarchical Control Scheme for Real Time Pressure Control

This paper describes a supervisory hierarchical fuzzy controller （SHFC） for regulating pressure in a real-time pilot pressure control system. The input scaling factor tuning of a direct expert controller is made using the error and process input parameters in a closed loop system in order to obtain better controller performance for set-point change and load disturbances. This on-line tuning method reduces operator involvement and enhances the controller performance to a wide operating range. The hierarchical control scheme consists of an intelligent upper level supervisory fuzzy controller and a lower level direct fuzzy controller. The upper level controller provides a mechanism to the main goal of the system and the lower level controller delivers the solutions to a particular situation. The control algorithm for the proposed scheme has been developed and tested using an ARM7 microcontroller-based embedded target board for a nonlinear pressure process having dead time. To demonstrate the effectiveness, the results of the proposed hierarchical controller, fuzzy controller and conventional proportional-integral （PI） controller are analyzed. The results prove that the SHFC performance is better in terms of stability and robustness than the conventional control methods.

Hierarchical Control Strategy for Load Regulation Based on Stackelberg Game Theory Considering Randomness

Demand response has been recognized as a valuable functionality of power systems for mitigating power imbalances.This paper proposes a hierarchical control strategy among the distribution system operator(DSO),load aggregators(LAs),and thermostatically controlled loads(TCLs);the strategy includes a scheduling layer and an executive layer to provide load regulation.In the scheduling layer,the DSO(leader)offers compensation price(CP)strategies,and the LAs(followers)respond to CP strategies with available regulation power(ARP)strategies.Profits of the DSO and LAs are modeled according to their behaviors during the load regulation process.Stackelberg game is adopted to capture interactions among the players and leader and to obtain the optimal strategy for each participant to achieve utility.Moreover,considering inevitable random factors in practice,e.g.,renewable generation and behavior of users,two different stochastic models based on sample average approximation(SAA)and parameter modification are formulated with improved scheduling accuracy.In the executive layer,distributed TCLs are triggered based on strategies determined in the scheduling layer.A self-triggering method that does not violate user privacy is presented,where TCLs receive external signals from the LA and independently determine whether to alter their operation statuses.Numerical simulations are performed on the modified IEEE-24 bus system to verify effectiveness of the proposed strategy.

An autonomous Unmanned Aerial Vehicle exploration platform with a hierarchical control method for post‐disaster infrastructures

Catastrophic natural disasters like earthquakes can cause infrastructure damage.Emer-gency response agencies need to assess damage precisely while repeating this process for infrastructures with different shapes and types.The authors aim for an autonomous Unmanned Aerial Vehicle(UAV)platform equipped with a 3D LiDAR sensor to comprehensively and accurately scan the infrastructure and map it with a predefined resolution r.During the inspection,the UAV needs to decide on the Next Best View(NBV)position to maximize the gathered information while avoiding collision at high speed.The authors propose solving this problem by implementing a hierarchical closed‐loop control system consisting of a global planner and a local planner.The global NBV planner decides the general UAV direction based on a history of measurements from the LiDAR sensor,and the local planner considers the UAV dynamics and enables the UAV to fly at high speed with the latest LiDAR measurements.The proposed system is vali-dated through the Regional Scale Autonomous Swarm Damage Assessment simulator,which is built by the authors.Through extensive testing in three unique and highly constrained infrastructure environments,the autonomous UAV inspection system suc-cessfully explored and mapped the infrastructures,demonstrating its versatility and applicability across various shapes of infrastructure.

Frequency Regulation of Alternating Current Microgrid Based on Hierarchical Control Using Fuzzy Logic

An alternating current(AC)microgrid is a system that integrates renewable power,power converters,controllers and loads.Hierarchical control can manage the frequency of the microgrid to prevent imbalance and collapse of the system.The existing frequency control methods use traditional proportion integration(PI)controllers,which cannot adjust PI parameters in real-time to respond to the status changes of the system.Hierarchical control driven by fuzzy logic allows real-time adjustment of the PI parameters and the method used a two-layer control structure.The primary control used droop control to adjust power distribution,and fuzzy logic was used in the voltage loop of the primary control.The secondary control was added to make up for frequency deviation caused by droop control,and fuzzy logic was used in the secondary frequency control to deal with the dynamic change of frequency caused by the disturbances of loads.The proposed method was simulated in Matlab/Simulink.In the primary control,the proposed method reduced the total harmonic distortion(THD)of two cycles of the output voltage from 4.19%to 3.89%;in the secondary control,the proposed method reduced the frequency fluctuation of the system by about 0.03 Hz and 0.04 Hz when the load was increased and decreased,respectively.The results show that the proposed methods have a better effect on frequency maintenance and voltage control of the AC microgrid.

Adaptive state-constrained/model-free iterative sliding mode control for aerial robot trajectory tracking

This paper develops a novel hierarchical control strategy for improving the trajectory tracking capability of aerial robots under parameter uncertainties.The hierarchical control strategy is composed of an adaptive sliding mode controller and a model-free iterative sliding mode controller(MFISMC).A position controller is designed based on adaptive sliding mode control(SMC)to safely drive the aerial robot and ensure fast state convergence under external disturbances.Additionally,the MFISMC acts as an attitude controller to estimate the unmodeled dynamics without detailed knowledge of aerial robots.Then,the adaption laws are derived with the Lyapunov theory to guarantee the asymptotic tracking of the system state.Finally,to demonstrate the performance and robustness of the proposed control strategy,numerical simulations are carried out,which are also compared with other conventional strategies,such as proportional-integralderivative(PID),backstepping(BS),and SMC.The simulation results indicate that the proposed hierarchical control strategy can fulfill zero steady-state error and achieve faster convergence compared with conventional strategies.

Group-Consensus of Hierarchical Containment Control for Linear Multi-Agent Systems

The existing containment control has been widely developed for several years, but ignores the case for large-scale cooperation. The strong coupling of large-scale networks will increase the costs of system detection and maintenance. Therefore, this paper is concerned with an extensional containment control issue, hierarchical containment control. It aims to enable a multitude of followers achieving a novel cooperation in the convex hull shaped by multiple leaders. Firstly, by constructing the three-layer topology, large-scale networks are decoupled. Then,under the condition of directed spanning group-tree, a class of dynamic hierarchical containment control protocol is designed such that the novel group-consensus behavior in the convex hull can be realized. Moreover, the definitions of coupling strength coefficients and the group-consensus parameter in the proposed dynamic hierarchical control protocol enhance the adjustability of systems. Compared with the existing containment control strategy, the proposed hierarchical containment control strategy improves dynamic control performance. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed hierarchical control protocol.

Distributed Fault-Tolerant Containment Control for Nonlinear Multi-Agent Systems Under Directed Network Topology via Hierarchical Approach

This paper investigates the distributed fault-tolerant containment control(FTCC)problem of nonlinear multi-agent systems(MASs)under a directed network topology.The proposed control framework which is independent on the global information about the communication topology consists of two layers.Different from most existing distributed fault-tolerant control(FTC)protocols where the fault in one agent may propagate over network,the developed control method can eliminate the phenomenon of fault propagation.Based on the hierarchical control strategy,the FTCC problem with a directed graph can be simplified to the distributed containment control of the upper layer and the fault-tolerant tracking control of the lower layer.Finally,simulation results are given to demonstrate the effectiveness of the proposed control protocol.

Hierarchical control of a class of uncertain linear systems

Hierarchical control method which is based on a hierarchical architecture has been developed to be mainly aimed at large-scale complex systems.In order to analyse and control this kind of systems,we construct first an appropriate and low-dimensional abstract system,then synthesise and lift the control law from the obtained abstraction to the original system.As far as the linear systems with uncertain terms are concerned,this paper studies the robust control problem of high-dimensional uncertain linear systems and derives the results by employing hierarchical controlmethod.Furthermore,the LMI toolbox is allowed to be used for the computation of interface functions.Finally,our method framework is illustrated on a five-dimensional uncertain linear system.

Investigation on hierarchical control for driving stability and safety of intelligent HEV during car-following and lane-change process

The longitudinal and lateral coordinated control for autonomous vehicles is fundamental to achieve safe and comfortable driving performance.Aiming at this for hybrid electric vehicles(HEV)during the car-following(CF)and lane-change(LC)process while accelerating,a hierarchical control strategy for vehicle stability control is proposed.This new approach is different from the conventional hierarchical control.On the basis of model predictive control(MPC)theory,a two-layer MPC controller is designed at the top level of the control structure.The upper layer is a linear time-varying MPC(LTV-MPC),while the lower layer is a hybrid MPC(HMPC).For the LTV-MPC controller,a control-oriented linear discrete model for HEV is established,which integrates the dynamic model with three degrees of freedom(DOF)and the car-following model.The lower-layer HMPC controller is designed on the basis of the analysis for HEV hybrid characteristics and the modelling for the mixed logic dynamic(MLD)model of the HEV powertrain.As for the bottom level,a control plant including the HEV powertrain model and the 7 DOF nonlinear dynamics of the vehicle body is established.In addition,the system stability is proven.A deep fusion of vehicle dynamics control and energy management is achieved.Compared with LC-ACC control and conventional ACC control,the simulation and the hardware-in-the-loop(HIL)test results under different driving scenarios show that the proposed hierarchical control strategy can effectively maintain lateral stability and safety under severe driving conditions.Additionally,the HEV powertrain output torque and the gear-shift point are coordinated and controlled by the HMPC controller.

Hierarchical Control of DC Microgrids Robustness and Smartness

This paper investigates the hierarchical control of DC microgrids.Compared to AC microgrids,DC microgrids encounter complicated converter-level control,and simplified system-level management.To address these characteristics,a new three-level control hierarchy is introduced.The converter control level encapsulates sophisticated converter topologies and inner control loops into a black-box representation.The voltage coordination level uses DC voltage signals to coordinate both static and transient power sharing.The energy management level optimizes the power flow and power quality in a broader scope through communication.This architecture lowers the focus of control to bottom levels.More functions are allocated to the converter control and voltage coordination levels.They can maintain basic microgrid performance with fully local control,thereby ensuring reliable power supply in case of communication failures.Moreover,taking advantage of DC microgrids’simplified system-level operation patterns,the energy management level uses straightforward algorithms to achieve intelligent functions.As a result,this architecture achieves both robust and smart control by exploring DC microgrids’critical features.

Hierarchical-control-based output synchronization of coexisting attractor networks

This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the rightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme.

Hierarchical control for parallel bidirectional power converters of a grid-connected DC mlcrogrnd

The DC microgrid is connected to the AC utility by parallel bidirectional power converters （BPCs） to import/export large power, whose control directly affects the performance of the grid-connected DC microgrid. Much work has focused on the hierarchical control of the DC, AC, and hybrid microgrids, but little has considered the hierarchical control of multiple parallel BPCs that directly connect the DC microgrid to the AC utility. In this paper, we propose a hierarchical control for parallel BPCs of a grid-connected DC mierogrid. To suppress the potential zero-sequence circulating cm-cent in the AC side among the parallel BPCs and realize feedback linearization of the voltage control, a d-q-O control scheme instead of a conventional d-q control scheme is proposed in the inner current loop, and the square of the DC voltage is adopted in the inner voltage loop. DC side droop control is applied to realize DC current sharing among multiple BPCs at the primary control level, and this induces DC bus voltage deviation. The quantified relationship between the current sharing error and DC voltage deviation is derived, indicating that there is a trade-off between the DC voltage deviation and current sharing error. To eliminate the current sharing error and DC voltage deviation simultaneously, slope-adjusting and voltage-shifting approaches are adopted at the secondary control level. The pro- posed tertiary control realizes precise active and reactive power exchange through parallel BPCs for economical operation. The proposed hierarchical control is applied for parallel BPCs of a grid-connected DC microgrid and can operate coordinately with the control for controllable/uncontrollable distributional generation. The effectiveness of the proposed control method is verified by corresponding simulation tests based on Matlab/Simulink, and the performance of the hierarchical control is evaluated for prac- tical applications.

Hierarchical and Distributed Optimal Control Strategy for Power and Power Quality of Microgrid Based on Finite-Time Consistency

Droop control is one of the main control strategies of islanded microgrid(MG),but the droop control cannot achieve reasonable power distribution of microgrid,resulting in frequency and voltage deviation from the rating value,which needs the upper control link to eliminate the deviation.However,at present,most layered control requires a centralized control center,which excessively relies on microgrid central controller(MGCC)and real-time communication among distributed generation(DG),which has certain limitations.To solve the above problems,this paper proposes a hierarchical distributed power and power quality optimization strategy based on multi-agent finite time consistency algorithm(MA-FTCA).Firstly,based on the first layer droop control,MA-FTCA is applied to introduce frequency and voltage compensation to stabilize the system frequency and voltage at the rated value.Secondly,in the third layer,the MA-FTCA is adopted to estimate the total active power and total reactive power spare capacity of the system,to realize the reasonable distribution of active power and reactive power output of each DG according to its proportion of spare capacity when the system load side changes.The control strategy proposed in this paper adopts a completely distributed control method and does not need a centralized control center in each layer of control.Finally,MATLAB/Simulink simulation platform is used to verify the correctness and effectiveness of the proposed optimization strategy.

Movability of the tracked pipeline-robot based on hierarchical fuzzy control

The turning motion of a tracked pipeline-robot implemented by skid steering is a nonholonomic dynamic problem with intrinsic nonlinearity, to which the classical control method is inappropriate and cannot be applied. This paper presents a novel path tracking control method based on hierarchical fuzzy structure. The controller consists of three sub-level low dimensional fuzzy control systems： fuzzy supervisory control, fuzzy steering and fuzzy velocity control. As a result, establishing the bases of rules for the fuzzy control becomes feasible and simplified, and the related controller can be adapted to complicated ground and environment. Using this method, the number of fuzzy controt rules is greatly decreased so that the curse of dimensionality causing the multivariable problem does not occur. Simulation and experimental results validate the effectiveness of the proposed method with satisfied performance on path tracking. Autonomous navigation of the caterpillar-inspired pipeline-robot is also implemented based on the sensor feedbacks.

Hierarchical power control for OFDM based LTE system

3 GPP LTE has approved uplink intra-cell power control and defined overload indicator （OI） for uplink inter-cell power contrQ1 to mitigate the inter-cell interference （ICI）, respectively. In this pa- per, we propose a hierarchical power control （ HPC ） scheme where intra-eell and inter-cell power controls interact with each other. The inter-cell power control eommand is generated by radio re- source management （RRM） entity according to the ICI-load model together with the current ICI and served load information. This ICI-load model is proposed as a guideline for coordination among cells to enable the system to approach its system specific interference over thermal noise （IoT） work area. Simulation results show that for HPC scheme, the system＇ s IoT is well controlled to fit its pre-de- fined work area and the power efficiency is improved significantly. Our proposed scheme is also ro- bust to different settings of its inter-cell power control period.

Quality of Service Improvement with Optimal Software-Defined Networking Controller and Control Plane Clustering

The controller is indispensable in software-defined networking(SDN).With several features,controllers monitor the network and respond promptly to dynamic changes.Their performance affects the quality-of-service(QoS)in SDN.Every controller supports a set of features.However,the support of the features may be more prominent in one controller.Moreover,a single controller leads to performance,single-point-of-failure(SPOF),and scalability problems.To overcome this,a controller with an optimum feature set must be available for SDN.Furthermore,a cluster of optimum feature set controllers will overcome an SPOF and improve the QoS in SDN.Herein,leveraging an analytical network process(ANP),we rank SDN controllers regarding their supporting features and create a hierarchical control plane based cluster(HCPC)of the highly ranked controller computed using the ANP,evaluating their performance for the OS3E topology.The results demonstrated in Mininet reveal that a HCPC environment with an optimum controller achieves an improved QoS.Moreover,the experimental results validated in Mininet show that our proposed approach surpasses the existing distributed controller clustering(DCC)schemes in terms of several performance metrics i.e.,delay,jitter,throughput,load balancing,scalability and CPU(central processing unit)utilization.