Interaction and coordinated development between desertification control and social economy in Xizang,China

Based on the general requirements of the coordinated development of"ecological livable"and"affluent life"in the rural revitalization strategy,the evaluation index system of desertification control was constructed,the interaction between desertification control and regional social economy and the internal space-time coordination mechanism were explored,and the quality of desertification control and its coordination degree with regional economic development were quantitatively analyzed.The decoupling mechanism of desertification governance society economy system were analyzed,and the high level for the government to promote desertification governance,constructing ecological economy coordinated development pattern to provide decision basis to Xizang desertification governance-social economic system interaction and coupling coordination development as the research object,introducing the coupling decoupling model to measure the coupling coordination model and system coordination and decoupling decoupling.Desertification control in Xizang shows a trend of gradual improvement,but the overall level is still not high and there is a lot of room for optimization.The coupling coordination degree of desertification control-social and economic system is in a steady fluctuation trend,rising from D value less than 0.55 in 2004 to 0.87 in 2018,in a state of coordinated development(good),and grey prediction analysis shows that D value is in a continuous rise.The coupling coordination degree of the six prefecture-level cities in Xizang and Ngari region is different in time and space,but the overall development trend is coordinated.The development index of desertification control and the socio-economic development index show the interaction of strong decoupling,strong negative decoupling and weak decoupling,and there are interaction effects of desertification control,economic development and social development at different scales.

Adaptive Coordinated Path Tracking Control Strategy for Autonomous Vehicles with Direct Yaw Moment Control

It is a striking fact that the path tracking accuracy of autonomous vehicles based on active front wheel steering is poor under high-speed and large-curvature conditions.In this study,an adaptive path tracking control strategy that coordinates active front wheel steering and direct yaw moment is proposed based on model predictive control algorithm.The recursive least square method with a forgetting factor is used to identify the rear tire cornering stiffness and update the path tracking system prediction model.To adaptively adjust the priorities of path tracking accuracy and vehicle stability,an adaptive strategy based on fuzzy rules is applied to change the weight coefficients in the cost function.An adaptive control strategy for coordinating active front steering and direct yaw moment is proposed to improve the path tracking accuracy under high-speed and large-curvature conditions.To ensure vehicle stability,the sideslip angle,yaw rate and zero moment methods are used to construct optimization constraints based on the model predictive control frame.It is verified through simulation experiments that the proposed adaptive coordinated control strategy can improve the path tracking accuracy and ensure vehicle stability under high-speed and largecurvature conditions.

Path-Following Based on Nonlinear Model Predictive Control with Adaptive Path Preview

This paper presents a Nonlinear Model Predictive Controller(NMPC)for the path following of autonomous vehicles and an algorithm to adaptively adjust the preview distance.The prediction model includes vehicle dynamics,path following dynamics,and system input dynamics.The single-track vehicle model considers the vehicle’s coupled lateral and longitudinal dynamics,as well as nonlinear tire forces.The tracking error dynamics are derived based on the curvilinear coordinates.The cost function is designed to minimize path tracking errors and control effort while considering constraints such as actuator bounds and tire grip limits.An algorithm that utilizes the optimal preview distance vector to query the corresponding reference curvature and reference speed.The length of the preview path is adaptively adjusted based on the vehicle speed,heading error,and path curvature.We validate the controller performance in a simulation environment with the autonomous racing scenario.The simulation results show that the vehicle accurately follows the highly dynamic path with small tracking errors.The maximum preview distance can be prior estimated and guidance the selection of the prediction horizon for NMPC.

Optimal control based coordinated taxiing path planning and tracking for multiple carrier aircraft on flight deck

Coordinated taxiing planning for multiple aircraft on flight deck is of vital importance which can dramatically improve the dispatching efficiency.In this paper,first,the coordinated taxiing path planning problem is transformed into a centralized optimal control problem where collision-free conditions and mechanical limits are considered.Since the formulated optimal control problem is of large state space and highly nonlinear,an efficient hierarchical initialization technique based on the Dubins-curve method is proposed.Then,a model predictive controller is designed to track the obtained reference trajectory in the presence of initial state error and external disturbances.Numerical experiments demonstrate that the proposed“offline planningþonline tracking”framework can achieve efficient and robust coordinated taxiing planning and tracking even in the presence of initial state error and continuous external disturbances.

Wind Farm Coordinated Control for Power Optimization

以降低风电场尾流损失、优化风场出力为目标,设计基于Laguerre函数非线性预测控制（nonlinear modelpredictive control,NLMPC）方案的风场集群控制器。该控制器应用风场动态尾流模型,通过NLMPC统一调整风场内各机组转速以提升风场功率。在控制器设计中,使用有效风速预测误差校正对预测模型失配及超短期风速预测误差进行补偿,引入Laguerre函数降低滚动时域优化计算负担并分析了控制器对风速预测误差的鲁棒性能。仿真研究表明,集群控制器能够在不同风速条件下提升风场功率、降低优化计算负担,且对风速预测模型失配与风场自然风速预测误差具有鲁棒性。

Coordinated Control Architecture for Motion Management in ADAS Systems

Advanced driver assistance systems(ADAS) seek to provide drivers and passengers of automotive vehicles increased safety and comfort. Original equipment manufacturers are integrating and developing systems for distance keeping, lane keeping and changing and other functionalities. The modern automobile is a complex system of systems. How the functionalities of advanced driver assistance are implemented and coordinated across the systems of the vehicle is generally not made available to the wider research community by the developers and manufactures. This paper seeks to begin filling this gap by assembling open source physics models of the vehicle dynamics and ADAS command models. Additionally, in order to facilitate ADAS development and testing without having access to the details of ADAS, a coordinated control architecture for motion management is also proposed for distributing ADAS motion control commands over vehicle systems. The architecture is demonstrated in a case study where motion is coordinated between the steering and the braking systems, which are typically used only for a single functionality. The integrated vehicle and system dynamics using the coordinated control architecture are simulated for various driving tasks. It is seen that improved trajectory following can be achieved by the proposed coordinated control architecture. The models, simulations and control architecture are made available for open access.

Coordinated voltage control of renewable energy power plants in weak sending-end power grid

The utilization of renewable energy in sending-end power grids is increasing rapidly,which brings difficulties to voltage control.This paper proposes a coordinated voltage control strategy based on model predictive control(MPC)for the renewable energy power plants of wind and solar power connected to a weak sending-end power grid(WSPG).Wind turbine generators(WTGs),photovoltaic arrays(PVAs),and a static synchronous compensator are coordinated to maintain voltage within a feasible range during operation.This results in the full use of the reactive power capability of WTGs and PVAs.In addition,the impact of the active power outputs of WTGs and PVAs on voltage control are considered because of the high R/X ratio of a collector system.An analytical method is used for calculating sensitivity coefficients to improve computation efficiency.A renewable energy power plant with 80 WTGs and 20 PVAs connected to a WSPG is used to verify the proposed voltage control strategy.Case studies show that the coordinated voltage control strategy can achieve good voltage control performance,which improves the voltage quality of the entire power plant.

Angle Control of a Pneumatically Driven Musculoskeletal Model Based on Coordination of Agonist-Antagonist Muscle

In recent years, researchers have been actively pursuing research into developing robots that can be useful in many fields of industry （e.g., service, medical, and aging care）. Such robots must be safe and flexible so that they can coexist with people. Pneumatic actuators are useful for achieving this goal because they are lightweight units with natural compliance. Our research focuses on joint angle control for a pneumatically driven musculoskeletal model. In such a model, we use a one-degree-of-freedom joint model and a five-fingered robot hand as test beds. These models are driven by low pressure-driven pneumatic actuators, and mimic the mechanism of the human hand and musculoskeletal structure, which has an antagonistic muscle pair for each joint. We demonstrated a biologically inspired control method using the parameters antagonistic muscle ratio and antagonistic muscle activity. The concept of the method is based on coordination of an antagonistic muscle pair using these parameters. We have investigated the validity of the proposed method both theoretically and experimentally, developed a feedback control system, and conducted joint angle control by implementing the test beds.

A Survey of Model Predictive Control Methods for Traffic Signal Control

Enhancing traffic efficiency and alleviating(even circumventing) traffic congestion with advanced traffic signal control(TSC) strategies are always the main issues to be addressed in urban transportation systems. Since model predictive control(MPC) has a lot of advantages in modeling complex dynamic systems, it has been widely studied in traffic signal control over the past 20 years. There is a need for an in-depth understanding of MPC-based TSC methods for traffic networks. Therefore, this paper presents the motivation of using MPC for TSC and how MPC-based TSC approaches are implemented to manage and control the dynamics of traffic flows both in urban road networks and freeway networks. Meanwhile, typical performance evaluation metrics, solution methods, examples of simulations,and applications related to MPC-based TSC approaches are reported. More importantly, this paper summarizes the recent developments and the research trends in coordination and control of traffic networks with MPC-based TSC approaches. Remaining challenges and open issues are discussed towards the end of this paper to discover potential future research directions.

Optimized and coordinated model predictive control scheme for DFIGs with DC-based converter system

This paper proposes an optimized and coordinated model predictive control(MPC) scheme for doublyfed induction generators(DFIGs) with DC-based converter system to improve the efficiency and dynamic performance in DC grids. In this configuration, the stator and rotor of the DFIG are connected to the DC bus via voltage source converters, namely, a rotor side converter(RSC) and a stator side converter(SSC). Optimized trajectories for rotorflux and stator current are proposed to minimize Joule losses of the DFIG, which is particularly advantageous at low and moderate torque. The coordinated MPC scheme is applied to overcome the weaknesses of the field-oriented control technique in the rotor flux-oriented frame, which makes the rotor flux stable and the stator current track its reference closely and quickly. Lastly, simulations and experiments are carried out to validate the feasibility of the control scheme and to analyze the steady-state and dynamic performance of the DFIG.

Dynamic Coordination of Uncalibrated Hand/Eye Robotic System Based on Neural Network

A nonlinear visual mapping model is presented to replace the image Jacobian relation for uncalibrated hand/eye coordination. A new visual tracking controller based on artificial neural network is designed. Simulation results show that this method can drive the static tracking error to zero quickly and keep good robustness and adaptability at the same time. In addition, the algorithm is very easy to be implemented with low computational complexity.

Observation-Driven Multiple UAV Coordinated Standoff Target Tracking Based on Model Predictive Control

An observation-driven method for coordinated standoff target tracking based on Model Predictive Control(MPC)is proposed to improve observation of multiple Unmanned Aerial Vehicles(UAVs)while approaching or loitering over a target.After acquiring a fusion estimate of the target state,each UAV locally measures the observation capability of the entire UAV system with the Fisher Information Matrix(FIM)determinant in the decentralized architecture.To facilitate observation optimization,only the FIM determinant is adopted to derive the performance function and control constraints for coordinated standoff tracking.Additionally,a modified iterative scheme is introduced to improve the iterative efficiency,and a consistent circular direction control is established to maintain long-term observation performance when the UAV approaches its target.Sufficient experiments with simulated and real trajectories validate that the proposed method can improve observation of the UAV system for target tracking and adaptively optimize UAV trajectories according to sensor performance and UAV-target geometry.

面向多区域防洪的珠江流域水库群协同调度模型研究

珠江流域洪水组成与遭遇复杂多变,防洪保护对象多而分散,且兼顾供水、生态、发电、航运、库区安全等多种任务,水库群防洪调度面临多区域、多目标协同调度技术难题。以位于西江、北江、东江上的水库为研究对象,基于流域防洪格局和防洪任务阐明了水库群多区域协同防洪的调度节点和角色定位,提出了嵌套式多维属性的模型功能结构,构建了珠江流域水库群多区域协同防洪调度模型。以流域防洪极为不利的2005年6月中下游型大洪水为例进行流域水库群防洪调度模型研究,结果表明,通过龙滩水库加大拦蓄,岩滩水库、百色水库、西津水库、飞来峡水库等西江、北江水库群协同调度,可将西江梧州站洪峰流量削减至安全泄量50 400 m^(3)/s以下,较原设计调度方案多削减3 200 m^(3)/s,将三角洲思贤滘(马口+三水)断面洪峰削减至62 700 m^(3)/s,较原设计调度方案多削减4 500 m^(3)/s,有效保障了粤港澳大湾区城市的防洪安全。

基于Q学习的超超临界机组协调系统模型预测控制研究

超超临界机组具有多输入多输出、非线性严重、耦合强、时滞大的特点,其控制系统的设计要求是在保证系统稳定运行的同时,最大限度地提高机组的热效率和功率输出、快速准确地调节机组负荷、确保机组主蒸汽压力和温度在允许范围。通过调整系统模型以及阶段成本,进而获取最优策略。选取强化学习中的Q学习方法。将参数化模型预测控制作为Q学习中的一种新型函数逼近器,通过调整模型预测控制的参数来获取近似最优闭环控制策略以及最优的值函数。将该方法应用到1 GW超超临界锅炉汽轮机协调系统的控制中。在升负荷以及小范围升负荷变化情况下进行仿真。仿真结果表明,与传统模型预测控制方法对比,该方法可以在满足约束的情况下使系统输出值更加准确地到达设定值。

基于多端口直流变压器的氢燃料电池-储能协调控制策略

面向氢燃料电池在微网领域日趋广泛的应用,依托宁波慈溪氢电耦合直流微网示范工程中的风/光/氢燃料电池直流互联系统,研究其氢燃料电池接入的核心设备——三端口直流变压器的端口功率协调控制策略。为缩短仿真时间,提出并采用了一种适用于多模块串并联多有源桥结构直流变压器的开关周期平均模型,并应用该等效简化模型提出了一种燃料电池-储能混合供电系统能量协调控制策略。该控制策略可根据储能系统荷电状态、各端口功率容量、燃料电池动态响应速度等因素对各端口功率指令进行优化调整与智能分配,避免燃料电池发电功率过快变化、储能系统过充过放,并最大化氢能发电占比。经实际样机测试与MATLABSimulink仿真验证,该协调控制策略在直流变压器的多种控制模式下均有良好的工作性能,功率控制端口的实际功率可以跟随快速变化的指令值,负荷突变时电压控制端口的实际电压波动均能控制在4%以下。

基于改进无模型自适应控制的漂浮式海上风机转矩-变桨协调控制策略研究

针对漂浮式海上风机建模困难、频繁变桨造成的严重疲劳损伤等问题,提出一种基于改进无模型自适应控制的转矩-变桨协调控制策略。该策略不依赖漂浮式海上风机的数学模型,通过集成迭代学习控制策略改进无模型自适应控制方法,设计发电机电磁转矩和桨距角作为控制变量的多输入多输出控制器进行协调控制,允许非零度桨距角下风机用做动能缓冲,在平滑输出功率的同时减少变桨动作量。为证明所提出控制策略的有效性,在多种风场景下,与增益调度PI控制等方法进行了对比实验。结果表明:所提出的控制策略使漂浮式海上风机在满足发电功率平稳性的同时减缓了漂浮平台的俯仰运动,可有效降低漂浮式海上风机的疲劳载荷。

面向全矢量线控车辆极限运动的分层式协同控制

装配四轮分布式驱动-转向(4WID-4WIS)底盘的全矢量线控车辆具备多可控自由度、高速稳定性强的特点,是极限工况稳定裕度和安全性较高的理想车型。为了解决全矢量线控车辆在极限工况下纵横向控制冲突危害行车安全的问题,提出一种基于模型预测控制(MPC)的分层式车辆纵向和横向运动协同控制方法。建立基于单轨模型的期望运动状态识别方法,设计模型预测控制器转换动力学目标,采用泰勒展开和前向欧拉方法对预测模型进行线性离散化处理;设计基于负荷率的轮胎力优化分配方法,利用反正切轮胎逆模型求解控制执行量。仿真结果表明,协同控制方法能显著提高车辆在不同路面下的极限运动稳定性,更精准地跟踪期望运动状态,扩大稳定裕度,保障行车安全。

地形跟随飞行能量协调在线轨迹规划与跟踪

针对定速地形跟随飞行全局离线规划方案数据存储量大、机动飞行油耗大等问题,提出基于级联模型预测控制(cascaded model predictive control,CMPC)的能量协调在线轨迹规划与跟踪方案。首先,利用飞行器纵向质点运动学模型设计模型预测控制(model predictive control,MPC)在线轨迹规划器。从能量分配原理出发确定速度变化规律,对于飞行时总能量不变而导致能量分配不合理的情况,引入虚拟控制量实现总能量动态调节,完成能量协调策略设计。其次,引入地形粗糙度概念描述地形起伏程度,基于此提出规划器自适应时域方案,对于不同地形实现预测时域动态调节。结合MPC轨迹跟踪控制器,并利用真实地形数据进行仿真实验。实验结果表明,所提方案可在与全局离线规划方案航迹差异不大的前提下,实现在线轨迹规划,显著降低油耗,提高航程极限,完成复杂地形的机动飞行任务。

基于TD—PLS模型预测前馈的垃圾焚烧锅炉脱酸自动控制策略研究与应用

针对垃圾焚烧锅炉半干法脱酸系统自动控制投运率低、控制效果差的问题,在分析脱酸系统运行特性的基础上,设计了一种以PID控制和模型预测前馈相结合的HCl-SO_(2)协同控制策略。采用以HCl排放浓度作为主要控制目标,SO_(2)排放浓度作为次要目标的串级PID协同控制策略。在串级PID控制的基础上,基于时间差分偏最小二乘法(TD—PLS)建立HCl排放浓度预测模型作为控制前馈。该控制策略应用于某500 t/d垃圾焚烧机组脱酸系统,实际应用效果表明:脱酸控制投入前,HCl排放浓度波动变化较大,小时排放均值范围20~40 mg/m^(3),小时排放均值浓度相对标准偏差(RSD)为15.95%。脱酸自动控制投入后,HCl小时排放均值范围在25~30 mg/m^(3),小时排放均值浓度RSD为6.22%。在协同控制作用下,HCl小时排放均值波动显著减小,单位锅炉蒸发量的石灰浆液消耗量由0.034 m^(3)/t降低到0.027 m^(3)/t,相比投运前降低了21%,在保证出口HCl和SO_(2)浓度符合标准的情况下,提高了脱酸系统运行的稳定性和经济性。