Upper-level Control Research Articles

Bi-level decentralized active and reactive power control for large-scale wind farm cluster

This paper proposes a bi-level decentralized active and reactive power control (DARPC) for the large-scale wind farm cluster (WFC) composed of several wind farms. The WFC tracks the active power reference from the transmission system operator (TSO) while controlling the bus voltage of the point of connection (POC), and maintaining the wind turbine (WT) terminal voltages stable in each wind farm. In the upper level, a distributed active and reactive power control scheme based on the consensus protocol is designed for the WFC, which can achieve fair active and reactive power sharing among multiple wind farms, and generates active and reactive power references for each wind farm. In the lower level, a centralized control scheme based on Model Predictive Control (MPC) is proposed, which can effectively regulates active and reactive power outputs of all WTs within the wind farm. The proposed centralized control scheme can maintain WTs terminal voltage close to the rated voltage while tracking the power reference from the upper level control. The DARPC can effectively reduce the computation burden of the WFC controller by distributing the computation and monitoring tasks to several wind farm controllers. Moreover, the communication cost is reduced. A WFC with 8 wind farms and totally 128 WTs was used to validate the proposed DARPC scheme.

Lateral stability integrated with energy efficiency control for electric vehicles

Abstract A hierarchical controller is designed to enhance the lateral stability of electric vehicles (EVs) with as low dissipation energy as possible in this paper. In particular, a reference dynamic model based on the estimated tire cornering stiffness is established for different driving conditions, the lateral stability control can be transformed into tracking the desired sideslip angle and yaw rate by the reference dynamic model. At the upper-level, the controller is consisted of an integral terminal sliding mode (ITSM) controller and a speed tracking controller. The ITSM controller considering parameter uncertainties is proposed to quickly achieve the lateral stability, the speed tracking is used to stabilize the longitudinal dynamics. At the lower-level, in order to reduce the computational burden of the tire energy consumption, a penalty function with the longitudinal slip ratio is introduced to automatically modulate the weight factor of each wheel torque. Then, an optimal torque control allocation (CA) strategy utilizes the designed penalty function to allocate the control command from the upper-level controller. Simulation results show that the designed controller can guarantee the lateral stability under different driving conditions. Moreover, compared to other CA methods, the tire dissipation energy can be effectively decreased by the proposed CA based on the longitudinal slip ratio.

Initialization of Modular Multilevel Converter Models for the Simulation of Electromagnetic Transients

This paper presents an accurate steady-state initialization method for electromagnetic transient (EMT) models of modular multilevel converters (MMCs). The proposed method uses steady-state arm voltages and currents to initialize internal electrical variables and control systems of the converter, including capacitor voltage and gating signals of each sub-module. In addition to typical voltage source converter upper level control, MMC specific controls are also considered, including circulating current control, dc ripple control, and capacitor voltage balancing algorithm. EMT simulations on 101-level and 401-level MMC-HVDC systems confirm the accuracy of the proposed method.

Необходимость применения интеллектуальных систем управления в экспериментальных ядерно-физических комплексах (типа NICA). Ч.I: Проблема нештатных ситуаций

In the article (Part I) the necessity of application of end-to-end quantum technologies of intelligent computing in problems of structure elements control of complex experimental accelerator complex NICA is analyzed. Given a description of possible unforeseen situations, their classification is given to include adjustments to the decision-making application of production rules, logic knowledge bases of intelligent control systems based on emerging information risk increment. In the second part (Part II) the proposed two-level intelligent control system, a physical experimental setup of the NICA complex, in which the lower Executive level is a traditional control system based on expert control using the Tango control system Controls, while the upper (intelligent) level control actions are generated using the methods of quantum end-to-end IT design quantum fuzzy controller. Part II presents the QSCIT (Quantum Soft Computational Intelligence Toolkit), based on soft and quantum computing, to design robust knowledge bases in self-organizing intelligent control systems.

Steering Stability Control of a Four In-Wheel Motor Drive Electric Vehicle on a Road With Varying Adhesion Coefficient

In order to improve the steering stability of a four in-wheel motor independent-drive electric vehicles (4MIDEVs) on a road with varying adhesion coefficient, such as on a joint road and a μ-split road, this paper presents a hierarchical electronic steering control (ESC) strategy. The upper level controller of the proposed ESC strategy achieves the adaptive control of the yaw rate and sideslip angle in the direct yaw-moment control based on the influence of road adhesion. The lower level controller is designed as a two-hierarchy structure, which can adaptively change the torque allocation algorithm and achieve different weight controls of each wheel torque according to road adhesion coefficient. The results of real-time simulation conducted in the RT-LAB testing platform and a real-car test indicate an improvement in the steering stability of the 4MIDEV on a road with varying adhesion coefficient. Particularly the “double lane change”testing carried out on a joint road and a μ-split road shows a yaw rate error reduction of up to 55.1%, compared with the ordinary control strategy, with output torque and its fluctuation of each in-wheel motor significantly reduced.

Dual-level consensus-based frequency regulation using vehicle-to-grid service

To coordinate plug-in electric vehicles (PEVs) to support the primary frequency control, this paper presents a dual-level consensus-based frequency control method. The upper-level control aims to minimize the frequency deviation of multi-area power system, and the lower-level control aims to minimize the frequency regulation cost and battery degradation cost for individual PEVs. The incremental cost functions are formulated based on the objectives of the dual control levels, in this case, no objective function needs to be solved, and instead, the optimal results can be achieved by reaching a consensus incremental cost among neighboring individuals. The graph theory is applied to build the communication network among neighboring control areas in upper-level control, and among neighboring PEVs in lower-level control. The consensus algorithm is applied to specify the information updating and exchange among neighboring individuals. In addition, the dynamic models of multi-area power system and PEVs are developed for controller implementation and investigation. The simulation with different case studies are conducted to validate the performance of the proposed dual-level frequency control. The simulation results show that, with limited communication, the connected PEVs can be efficiently coordinated via dual-level controller to provide primary frequency regulation service, and meanwhile meet the battery charging/discharging constraints.

Distributed Robust Control Strategy of Grid-Connected Inverters for Energy Storage Systems’ State-of-Charge Balancing

Battery energy storage system (BESS) plays an important role in enhancing system flexibility, stability, and reliability of the power grid. This paper proposes a fully distributed two-level control strategy of the grid-connected inverters for BESSs. The upper-level control determines the charging/discharging power references for the BESS units according to the state of charge levels and the supply demand balance among intermittent distributed generations and time-varying load demands. The lower-level control adopts the proposed discrete robust control algorithm which enables the BESS to track the power references accurately. The uncertainty and disturbance are estimated by the disturbance estimation technique and the chattering problem is alleviated by introducing a saturation function. The convergence and stability of the proposed distributed control strategy are guaranteed through rigorous analysis and the effectiveness is validated by simulation results.

Collaborative configuration for distributed energy storages and cyber systems in low‐voltage distribution networks with high penetration of PV systems

Energy storage systems (ESSs) have recently been incorporated into low-voltage distribution networks (DNs) for promoting hosting capacity of photovoltaic (PV) systems. On the other hand, applications of information communications technologies enhance the self-regulation ability of LVDNs and are playing an important role to resolve integration problems of PV systems. Although the two aspects influence each other, they are generally configured separately in LVDNs. This study proposes a collaborative configuration scheme based on a bi-level optimisation model for distributed ESSs and cyber systems in LVDNs with high penetration of PV systems. In the upper level, the ESSs and wireless control terminals are deployed to minimise investment and operation cost with consideration of specific control of ESSs. In the lower level, communication topology is further optimised according to the upper-level results to promote control performance and balance communication topology complexity. The economy and effectiveness of the proposed configuration scheme are demonstrated by comparing with separated cyber and physical configuration schemes in case studies.

Design and implementation of a multi-degrees-of-freedom cable-driven parallel robot with gripper

Cable-driven parallel robots comprise driven actuators that allow controlled cables to act in parallel on an end-effector. Such a robotic system has a potentially large reachable workspace, large load capacity, high payload-to-weight ratio, high reconfigurability, and low inertia, relative to rigid link serial and parallel robots. In this work, a multi-degrees-of-freedom cable-suspended robot that can carry out pick-and-place tasks in large workspaces with heavy loads is designed. The proposed cable-driven parallel robot is composed of a rigid frame and an end-effector that is suspended from eight cables—four upper cables and four lower cables. The lengths of the cables are computed from the given positions of the suspended end-effector using a kinematic model. However, most multi-cable-driven robots suffer from interference among the cables, requiring a complex control methodology to find a target goal. Owing to this issue with cable-driven parallel robots, the whole control structure decomposes positioning control missions and allocates them into upper level and lower level. The upper level control is responsible for tracking the suspended end-effector to the target region. The lower level control makes fine positional modifications. Experimental results reveal that the hybrid control mode notably improves positioning performance. The wide variety of issues that are considered in this work apply to aerostats, towing cranes, locomotion interfaces, and large-scale manufacturing that require cable-driven parallel robots.

Bilevel optimal coordinated control strategy for park-level integrated energy system

A bilevel optimal coordinated control strategy for park-level integrated energy system is proposed in this paper. In the case of normal operation, the minimization of operation cost is set as the goal for lower-level and upper-level control system, with the purpose of optimal control for their own resources. In the case of overload, the minimization of peak load shifting cost is set as the goal for the upper-level control system, which can be achieved by coordinating directly controlled upper-level resources and various demand response resources in the industrial park.

Bi‐level decentralised active power control for large‐scale wind farm cluster

This study presents a bi-level decentralised active power control (DAPC) for a large-scale wind farm cluster (WFC), consisting of several wind farms for better active power dispatch. In the upper level, a distributed active power control scheme based on the distributed consensus is designed to achieve fair active power sharing among multiple wind farms, which generates the power reference for each wind farm. A distributed estimator is used to estimate the total available power of all wind farms. In the lower level, a centralised control scheme based on the model predictive control is proposed to regulate active power outputs of all wind turbines (WTs) within a wind farm, which reduces the fatigue loads of WTs while tracking the power reference obtained from the upper-level control. A WFC with 8 wind farms and totally 160 WTs, was used to test the control performance of the proposed DAPC scheme.

Robust H∞ fault tolerant control for quadrotor attitude regulation

This article investigates the robust H∞ fault tolerant control of quadrotor attitude regulation. The hover stability is heavily dependent on the thrust forces generated by the four rotors of the quadrotor. If faults occur in the rotors, the quadrotor becomes unstable, and possibly out of control. To this end, this article proposes a robust H∞ fault tolerant control schema, consisting of two level controllers, for regulation of the quadrotor attitude. The functions of the upper level controller and lower level controller are to generate the desired control input, and obtain the real input of the four rotors, respectively. In addition, the external disturbances are considered and attenuated by the controller. The simulation details are presented, and the effectiveness of the proposed control schema is verified.

Integrated stability control of AFS and DYC for electric vehicle based on non-smooth control

ABSTRACTA controller which ensures the driving stability of a four-wheel-independent-drive electric vehicle (4WID-EV) is designed in this paper. The controller is structurally hierarchically designed. In order to keep the 4WID-EV running steadily, an upper-level controller integrating the active front-wheel steering control method (AFS) and direct yaw moment control method (DYC) is designed to keep the sideslip angle and yaw rate tracking the ideal values. A non-smooth control method is used to improve the closed-loop system's convergence and anti-disturbance performance. The additional yaw moment generated by the upper-level controller is distributed to four driving wheels by the lower-level controller. An optimal control algorithm is used in the lower-level controller to achieve the minimum sum of tire utilisation, and ensure the power performance and driving stability of the 4WID-EV. In order to verify the effectiveness of the designed controller, a simulation model of the stability control system is established based on Carsim-Matlab/Simulink. And the simulation is performed under double lane change road considering the disturbances. The results of the simulation show that the 4WID-EV with the designed controller achieves smaller sideslip angle than sliding-mode control and the actuator chatter is slight. Then the stability and safety of the 4WID-EV are greatly improved.

The Contribution of Internal Audit to the Improvement of Internal Control System

In order to be more flexible in a perpetual mutational environment and face up to damaging effects of an economic situation in strong growth, organizations have to acquire efficient management tools allowing them to accomplish their objectives and to protect themselves against inherent risks. The implementation of an internal control system is considered to be the guarantor of an invincible organizational system and a means of control of risky operations. However, an applied and well conceived internal control provides the organization just a reasonable and not an absolute insurance about its objectives realization and sustainability. It is the reason for which an upper level control, accomplished by the internal audit function, seems to be a palliative to the internal control deficiencies, and a means of supervising and evaluating the application of procedures and internal control rules. Thus, this research aims at demonstrating how internal audit can participate to the improvement of internal control system. In this context, we have introduced a qualitative study, which was based on a sample of 10 Moroccan publicly traded companies that operate in many industries. Through the interviews conducted with this sample, we had identified firstly, the different control levels within organizations, and their degree of effectiveness and their capacity to face up risks as well as the limits of each type of control. Secondly, this research explored that internal audit is considered as a response to the insufficiencies of different lower control levels, and a means of monitoring and piloting the effectiveness of internal control system, across notably the recommendations provided.

Selection of Actuator Combination in Integrated Chassis Control Using Taguchi Method

This paper presents a method to select the actuator combination in integrated chassis control using Taguchi method. Electronic stability control (ESC), active front and rear steering (AFS/ARS) are used as an actuator, which is needed to generate a control tire force. After computing the control yaw moment in the upper-level controller, it is distributed into the control tire forces, generated by ESC, AFS and ARS in the lower-level controller. In this paper, the weighted pseudo-inverse control allocation (WPCA) with variable weights is used to determine the control tire forces of each actuator. Taguchi method is adopted for sensitivity analysis on variable weights of WPCA in terms of the control performances such as the maneuverability and the lateral stability. For sensitivity analysis, simulation is performed on a vehicle simulation package, CarSim. From sensitivity analysis, the most effective actuator combination is selected.

Power flow optimization for DC distribution grid with distributed energy access based on Newton–Raphson method through upper level control

DC distribution grids with distributed energy integration have been gaining a continually increasing interest in recent years both in academia and industry, power flow of the grids is a key issue to make use of these energy effectively and reliably, paper aims at optimizing the power flow of DC distribution through the upper level control, by considering the factors of distributed energy permeability and DC grid topology, without hardware investment increase nor using complex algorithm. firstly, the change rule of the network loss and voltage distribution are studied under different distributed energy permeability values and DC grid topology, Secondly, one OPF mathematical model of DC distribution network is established taking the index of network loss and voltage imbalance degree as objective function. According to the change of system flow, the optimized instruction value is provided by the system through calculation for each AC/DC, DC/DC converter; an optimization method of DC power flow is presented by controlling converter instruction. At last, two typical cases are demonstrated by simulation of PSCAD/EMTDC, indexes of the network loss and voltage imbalance degree of the DC distribution network are compared before and after the optimization, Simulation results show that the presented method is feasible to promote DC Distribution Grid.

Control Allocation Based on All Wheel Control in the Dynamic Control of Eight In-wheel Motor Drive Vehicle

Control Allocation based on all wheel control in the Dynamic Control of an eight in-wheel motor drive vehicle is studied in this paper which adopts the hierarchical control strategy and all the wheels are controllable(AWC), including the upper level controller and the lower level controller. The upper level controller calculates the target force (yaw moment) according to the vehicle motion states. And the lower level controller undertakes the distribution of the target force to each tire accordingly. Furthermore, the control system proposed in this paper integrates active steering with direct yaw moment control strategy. Through driver-in-loop simulation under certain conditions, the proposed control allocation is contrasted with the direct yaw moment control(DYC) which only take the longitudinal force into account when distribute the tire force. And the results show that the control allocation based on all wheel control(AWC) is better than traditional direct yaw moment control(DYC), especially in the field of trajectory following as well as in-wheel motor torque distribution.

Continuous Steering Stability Control Based on an Energy-Saving Torque Distribution Algorithm for a Four in-Wheel-Motor Independent-Drive Electric Vehicle

In this paper, a continuous steering stability controller based on an energy-saving torque distribution algorithm is proposed for a four in-wheel-motor independent-drive electric vehicle (4MIDEV) to improve the energy consumption efficiency while maintaining the stability in steering maneuvers. The controller is designed as a hierarchical structure, including the reference model level, the upper-level controller, and the lower-level controller. The upper-level controller adopts the direct yaw moment control (DYC), which is designed to work continuously during the steering maneuver to better ensure steering stability in extreme situations, rather than working only after the vehicle is judged to be unstable. An adaptive two-hierarchy energy-saving torque distribution algorithm is developed in the lower-level controller with the friction ellipse constraint as a basis for judging whether the algorithm needs to be switched, so as to achieve a more stable and energy-efficient steering operation. The proposed stability controller was validated in a co-simulation of CarSim and Matlab/Simulink. The simulation results under different steering maneuvers indicate that the proposed controller, compared with the conventional servo controller and the ordinary continuous controller, can reduce energy consumption up to 23.68% and improve the vehicle steering stability.

Hierarchical Braking Torque Control of In-Wheel-Motor-Driven Electric Vehicles Over CAN

This paper proposes a hierarchical braking torque control system design over controller area network (CAN) for electric vehicle with four in-wheel motors. Based on nonlinear tyre-road friction estimation, an adaptive braking torque control scheme is devised in the upper level controller to simultaneously regulate the wheel slip ratio for both front and rear wheels. While in the lower-level controller, a frequency-depended braking torque allocator is developed to dynamically distribute the braking torques command from upper level controller into friction braking torque and regenerative braking torque. A braking supervisor is established to enable or disable proposed hierarchical braking controller according to wheel slip ratio as well as vehicle speed condition. To avoid undesired discontinuities in braking torque signal when proposed braking controller is enabled abruptly, an initial value of the estimated tyre-road friction is rescaled additionally. Dedicated CAN bus module is built by using SimEvent toolbox, by which vehicle states as well as control signals can be transmitted and shared. Co-simulation by using MATLAB/Simulink and CarSim is conducted to demonstrate the effectiveness of the proposed hierarchical braking torque controller. Random CAN-induced delays are considered in the braking control process, by which the robustness of the proposed hierarchical braking controller is further verified.

Contract-based Predictive Control for Modularity in Hierarchical Systems

Hierarchical control architectures pose challenges for control, as lower-level dynamics, such as from actuators, are often unknown or uncertain. If not considered correctly in the upper layers, the requested and the applied control signals will differ. Thus, the actual and the predicted plant behavior will not match, likely resulting in constraint violation and decreased control performance. We propose a model predictive control scheme in which the upper and lower levels—the controller and the actuator—agree on a “contract” that allows to bound the error due to neglected dynamics. The contract allows to guarantee a desired accuracy, enables modularity, and breaks complexity: Components can be exchanged, vendors do not need to provide in-depth insights into the components’ working principle, and complexity is reduced, as upper-level controllers do not need full model information of the lower level—the actuators. The approach allows to consider uncertain actuator dynamics with flexible, varying sampling times. We prove repeated feasibility and input-to-state stability and illustrate the scheme in an example for a hierarchical controller/plant cascade.