An NMOS output-capacitorless low-dropout regulator with dynamic-strength event-driven charge pump

In this paper,an NMOS output-capacitorless low-dropout regulator(OCL-LDO)featuring dual-loop regulation has been proposed,achieving fast transient response with low power consumption.An event-driven charge pump(CP)loop with the dynamic strength control(DSC),is proposed in this paper,which overcomes trade-offs inherent in conventional structures.The presented design addresses and resolves the large signal stability issue,which has been previously overlooked in the event-driven charge pump structure.This breakthrough allows for the full exploitation of the charge-pump structure's poten-tial,particularly in enhancing transient recovery.Moreover,a dynamic error amplifier is utilized to attain precise regulation of the steady-state output voltage,leading to favorable static characteristics.A prototype chip has been fabricated in 65 nm CMOS technology.The measurement results show that the proposed OCL-LDO achieves a 410 nA low quiescent current(IQ)and can recover within 30 ns under 200 mA/10 ns loading change.

A Capacitor-Free CMOS Low-Dropout Regulator for System-on-Chip Application

A stable CMOS low drop-out regulator without an off-chip capacitor for system-on-chip application is presen- ted. By using an on-chip pole splitting technique and an on-chip pole-zero canceling technique, high stability is achieved without an off-chip capacitor. The chip was implemented in CSMC＇s 0.5μm CMOS technology and the die area is 600μm×480μm. The error of the output voltage due to line variation is less than -＋ 0.21% ,and the quiescent current is 39.8μA. The power supply rejection ratio at 100kHz is -33.9dB, and the output noise spectral densities at 100Hz and 100kHz are 1.65 and 0.89μV √Hz, respectively.

CMOS low-dropout regulator with 3.3 μA quiescent current without off-chip capacitor

A CMOS （complementary metal-oxide-semiconductor transistor） low-dropout regulator （LDO） with 3. 3 V output voltage and 100 mA output current for system-on-chip applications to reduce board space and external pins is presented. By utilizing a dynamic slew-rate enhancement（SRE） circuit and nested Miller compensation （NMC） on the LDO structure, the proposed LDO provides high stability during line and load regulation without off-chip load capacitors. The overshot voltage is limited within 550 mV and the settling time is less than 50 μs when the load current decreases from 100 mA to 1 mA. By using a 30 nA reference current, the quiescent current is 3.3 μA. The proposed design is implemented by CSMC 0. 5 μm mixed-signal process. The experimental results agree with the simulation results.

Theoretical Study of Double Cost Function Linear Quadratic Regulator(LQR)

Double cost function linear quadratic regulator (DLQR) is developed from LQR theory to solve an optimal control problem with a general nonlinear cost function. In addition to the traditional LQ cost function, another free form cost function was introduced to express the physical need plainly and optimize weights of LQ cost function using the search algorithms. As an instance, DLQR was applied in determining the control input in the front steering angle compensation control (FSAC) model for heavy duty vehicles. The brief simulations show that DLQR is powerful enough to specify the engineering requirements correctly and balance many factors effectively. The concept and applicable field of LQR are expanded by DLQR to optimize the system with a free form cost function.

Adaptive Linear Quadratic Regulator for Continuous-Time Systems With Uncertain Dynamics

In this paper, adaptive linear quadratic regulator(LQR) is proposed for continuous-time systems with uncertain dynamics. The dynamic state-feedback controller uses inputoutput data along the system trajectory to continuously adapt and converge to the optimal controller. The result differs from previous results in that the adaptive optimal controller is designed without the knowledge of the system dynamics and an initial stabilizing policy. Further, the controller is updated continuously using input-output data, as opposed to the commonly used switched/intermittent updates which can potentially lead to stability issues. An online state derivative estimator facilitates the design of a model-free controller. Gradient-based update laws are developed for online estimation of the optimal gain. Uniform exponential stability of the closed-loop system is established using the Lyapunov-based analysis, and a simulation example is provided to validate the theoretical contribution.

POSITIVE PERIODIC SOLUTION FOR A NONAUTONOMOUS LOGISTIC MODEL WITH LINEAR FEEDBACK REGULATION

A nonautonomous delayed logistic model with linear feedback regulation is proposed in this paper. Sufficient conditions are derived for the existence, uniqueness and global asymptotic stability of positive periodic solution of the model

An Ultra-Low Quiescent Current CMOS Low-Dropout Regulator with Small Output Voltage Variations

An ultra-low quiescent current low-dropout regulator with small output voltage variations and improved load regulation is presented in this paper. It makes use of dynamically-biased shunt feedback as the buffer stage and the LDO regulator can be stable for all load conditions. The proposed structure also employs a momentarily current-boosting circuit to reduce the output voltage to the normal value when output is switched from full load to no load. The whole circuit is designed in a 0.18 μm CMOS technology with a quiescent current of 550 nA. The maximum output voltage variation is less than 20 mV when used with 1 μF external capacitor.

Computing of LQR Technique for Nonlinear System Using Local Approximation

The main idea behind the present research is to design a state-feedback controller for an underactuated nonlinear rotary inverted pendulum module by employing the linear quadratic regulator(LQR)technique using local approximation.The LQR is an excellent method for developing a controller for nonlinear systems.It provides optimal feedback to make the closed-loop system robust and stable,rejecting external disturbances.Model-based optimal controller for a nonlinear system such as a rotatory inverted pendulum has not been designed and implemented using Newton-Euler,Lagrange method,and local approximation.Therefore,implementing LQR to an underactuated nonlinear system was vital to design a stable controller.A mathematical model has been developed for the controller design by utilizing the Newton-Euler,Lagrange method.The nonlinear model has been linearized around an equilibrium point.Linear and nonlinear models have been compared to find the range in which linear and nonlinear models’behaviour is similar.MATLAB LQR function and system dynamics have been used to estimate the controller parameters.For the performance evaluation of the designed controller,Simulink has been used.Linear and nonlinear models have been simulated along with the designed controller.Simulations have been performed for the designed controller over the linear and nonlinear system under different conditions through varying system variables.The results show that the system is stable and robust enough to act against external disturbances.The controller maintains the rotary inverted pendulum in an upright position and rejects disruptions like falling under gravitational force or any external disturbance by adjusting the rotation of the horizontal link in both linear and nonlinear environments in a specific range.The controller has been practically designed and implemented.It is vivid from the results that the controller is robust enough to reject the disturbances in milliseconds and keeps the pendulum arm deflection angle to zero degrees.

Kalman Filter and H_(∞)Filter Based Linear Quadratic Regulator for Furuta Pendulum

This paper deals with Furuta Pendulum(FP)or Rotary Inverted Pendulum(RIP),which is an under-actuated non-minimum unstable non-linear process.The process considered along with uncertainties which are unmodelled and analyses the performance of Linear Quadratic Regulator(LQR)with Kalman filter and H∞filter as two filter configurations.The LQR is a technique for developing practical feedback,in addition the desired x shows the vector of desirable states and is used as the external input to the closed-loop system.The effectiveness of the two filters in FP or RIP are measured and contrasted with rise time,peak time,settling time and maximum peak overshoot for time domain performance.The filters are also tested with gain margin,phase margin,disk stability margins for frequency domain performance and worst case stability margins for performance due to uncertainties.The H-infinity filter reduces the estimate error to a minimum,making it resilient in the worst case than the standard Kalman filter.Further,when theβrestriction value lowers,the H∞filter becomes more robust.The worst case gain performance is also focused for the two filter configurations and tested where H∞filter is found to outperform towards robust stability and performance.Also the switchover between the two filters is dependent upon a user-specified co-efficient that gives the flexibility in the design of non-linear systems.The non-linear process is tested for set point tracking,disturbance rejection,un-modelled noise dynamics and uncertainties,which records robust performance towards stability.

无人驾驶车辆路径跟踪混合控制策略研究

针对单一控制算法无法同时满足无人驾驶车辆对路径跟踪精度和控制器求解速度需求的问题,提出一种基于线性二次型调节器(LQR)和模型预测控制(MPC)的混合控制策略。该策略在低速工况下使用线性二次型调节器、在高速工况下使用模型预测控制算法进行路径跟踪控制,在此基础上设计基于有限状态机(FSM)的控制算法切换机制,并通过遗传算法(GA)对控制参数进行优化,基于CarSim和MATLAB/Simulink仿真平台对混合控制策略进行仿真验证,并进一步完成了实车试验。试验结果表明,所设计的混合控制策略能够在提高跟踪精度的基础上缩短计算时间,与单一控制算法相比,平均横向误差和平均航向误差分别减小了26.3%和39.6%,平均计算时间缩短了10.9%。

履带车辆主动悬挂多点布置优化

为实现履带车辆主动悬挂减振性能和能耗达到综合最优,基于正交试验方法开展履带车辆主动悬挂多点布置优化设计。首先,建立了履带车辆悬挂系统动力学模型,并通过道路模拟试验验证了该模型的合理性;其次,开展了履带车辆悬挂系统正交试验,分析了4种典型路面下各子悬挂对悬挂系统减振性能影响的敏感性;最后,设计了主动悬挂作动器的6个布置方案,通过建立基于线性二次最优(linear quadratic regulator,简称LQR)控制的履带车辆主动悬挂动力学模型,分析了典型路面下各布置方案对悬挂系统减振性能的影响规律及能耗变化规律。结果表明,通过对履带车辆主动悬挂作动器的布置优化,可以实现悬挂减振性能和能耗之间的平衡。

基于自适应分布式滤波观测器的多智能体系统编队控制

本文考虑了全局指令系统输出信息受到信道扰动情况下线性多智能体系统的编队控制问题.首先,基于协作式输出调节理论框架对线性多智能体系统的编队控制问题进行数学建模.其次,针对受到信道扰动的全局指令系统输出信息,提出了一类基于受扰输出的自适应分布式滤波观测器,在降低网络信息交换量的同时消除扰动的影响.最后,设计了输出反馈确定等价控制律,解决了线性多智能体系统的分布式编队控制问题.给出了数值仿真结果检验控制性能.

宽范围负载CL-LDO的设计

针对规模与功耗骤增的集成电路发展趋势,设计了一种可以提供宽范围负载电流的无片外电容型低压差线性稳压器(CL-LDO).为了解决宽范围负载电流与无片外电容等需求所带来的稳定性问题与瞬态特性问题,提出了动态零点补偿的方式与瞬态增强电路结构,既保障了整体电路在全负载范围内保持稳定,又实现了较好的瞬态特性.基于0.11μm CMOS工艺,完成电路设计、版图设计与仿真,仿真结果表明,在0~500 mA的负载范围内,整体环路增益可以达到68 dB;最小相位裕度为56°;当负载电流在1~500 mA之间发生跳变时(Δt=500 ns),输出过冲和下冲分别为56 mV和141 mV,建立时间分别为2μs和0.78μs;PSR为-67.2 dB@1 kHz,负载调整率为0.137μV/mA.

采用转角补偿LQR的自动驾驶集卡路径跟踪控制

为了解决自动驾驶集卡中半挂车在行驶过程中的路径偏移问题,提出了一种引入铰接角偏差和转角补偿的线性二次调节器(LQR)控制方法。基于集卡三自由度动力学模型建立了考虑铰接角偏差的路径跟踪误差模型;通过采用比例-积分-微分(PID)算法进行转角补偿设计了LQR路径跟踪控制器;通过MATLAB/Simulink和TruckSim搭建联合仿真平台,在不同工况下进行仿真分析验证。结果表明:通过采用提出的路径跟踪算法,引入PID转角补偿,牵引车平均距离偏差降低62%以上,半挂车平均距离偏差降低31%以上,航向偏差和铰接角偏差也均有所改善。因此,该文提出的控制算法具有较好的路径跟踪性能,提高了对期望路径跟踪的精度和稳定性。

基于改进势场法的智能车超车动态路径规划

为了改进人工势场法(artificial potential field,APF)在智能车高速超车状态下规划出的轨迹规范性差、安全性得不到保障、以及路径不平滑的问题。设计用于指引智能车换道的换道引力势场,以保证换道轨迹的规范性;构建异向分布结构的障碍车斥力势场提高换道的安全性;并建立带有转向缺口的道路中心线斥力势场和设计平滑代价函数优化规划出的轨迹点,使规划出的路径更加平滑。基于线性二次型调节器(linear quadratic regulator,LQR)设计路径跟踪控制器跟踪规划出的路径。通过Simulink与Carsim联合仿真,结果表明:所改进的APF算法能规划出更加合理的路径,设计的LQR路径跟踪控制器跟踪误差趋近于零,能够较好地控制车辆完成超车换道。

基于模型预测控制的车辆路径跟踪控制技术研究

以车辆三自由度动力学模型为研究对象,对自动驾驶车辆模型预测控制算法进行研究。结合魔术轮胎模型线性区域和小角度假设理论对车辆动力学模型进行简化处理,设计基于模型预测控制算法的路径跟踪控制器。使用MATLAB/CarSim联合仿真平台,选用多组工况进行仿真试验。设定车辆的速度分别为低速、中速、高速3种状态,并且使用线性二次型最优控制器进行换道工况路径跟踪,与模型预测控制器进行控制效果对比与分析,结果表明,模型预测控制算法路径跟踪控制效果更加优秀。

一种宽输入范围高PSRR线性稳压器设计

针对一般线性稳压器输入电压范围较窄,对电源纹波抑制能力较差的问题,设计了一款宽输入范围、高电源抑制比的线性稳压器。采用折叠式共源共栅结构的误差放大器提升环路增益,与负载相关的零点移动频率补偿结构保证整个环路的稳定性。结果表明:基于180 nm 45 V BCD工艺完成电路设计,在输入电压范围为6~45 V,负载电流范围0~100 mA的条件下,能够稳定输出5 V电压,具有良好的线性调整率。当输入电压为24 V,负载电流为50 mA时,低频段下电源抑制比为85.5 dB。

计及风力发电机转速安全约束的DFIG一次调频模型预测控制策略

针对传统方法控制双馈感应发电机(DFIG)的调频效果过于依赖参数整定的问题,该文提出了一种基于模型预测控制(MPC),计及转速安全约束的风力发电机参与一次调频控制策略。该方法结合风力发电机动力学模型与频率响应模型建立预测模型,通过线性回归方法变参考值将风力发电机转速的稳定性纳入考虑。相较于虚拟惯性控制等方法将系统频率偏差与转子动能直接关联,该文方法通过建立全新的预测模型,实时统筹考虑整个系统的状态信息,无需反复调整参数,在考虑转速安全性的同时兼顾全局性能。最后,通过实际算例分析验证了该文调频策略的有效性以及相对现有方法的优越性。

无人车换道轨迹与跟踪控制研究

无人车换道是自动驾驶领域的关键技术,针对无人车换道轨迹规划与跟踪控制问题,选择纯电动汽车作为研究对象,设计了一种考虑横纵向协同控制的轨迹跟踪控制器。首先,通过解耦将车辆换道简化为横向运动和纵向运动。根据路径跟踪误差动力学模型设计了线性二次型调节器路径跟踪控制器,并引入前馈控制设计了前馈-反馈LQR横向控制器,以此降低系统稳态误差。随后,考虑位置-速度误差设计了双PID纵向控制器,对车辆速度进行跟踪。选用五次多项式曲线规划换道轨迹。最后,通过Matlab和CarSim搭建联合仿真平台,对所设计的换道轨迹跟踪横纵向协同控制器进行测试研究。结果表明:在双车道换道工况下,该控制器能够较高精度地跟踪换道轨迹,车辆的距离偏差和航向角偏差最大分别为0.01 m和0.007 rad,可见具有良好的精确性和稳定性。

单级旋转倒立摆系统辨识与随动稳定控制方法研究

针对单级旋转倒立摆系统参数辨识和随动稳定控制问题,首先建立倒立摆在不受外力控制,摆杆自然下垂的顺摆模型,基于顺摆模型采用快速傅里叶变换方法对系统参数进行辨识;然后推导顺摆模型与倒摆模型之间的关系,进一步得到倒立摆的倒摆模型;根据辨识出的倒摆模型,采用线性二次型控制器对其进行稳定控制,并进行了数值仿真与实物实验验证。研究结果表明,通过辨识得到的系统模型更加精确,对比直接测量参数得到的系统模型,控制效果更好,且能对随动输入指令进行更优的跟随。该方法可以有效避免量测误差,提高模型的准确性,为火炮随动稳定控制提供参考。