Output feedback tracking control for rigid body attitude via immersion and invariance angular velocity observers

A novel immersion and invariance (I&I) angular velocity observer is presented for the attitude tracking control of a rigid body with the lack of angular rate. Global exponential convergence of angular velocity estimate errors are guaranteed by an innovative filter design for the estimates' Euclidean norm. The proposed method requires fewer filter states compared with existing I&I angular velocity observer designs, which achieves a simpler closed-loop structure (dynamic reduction). The observer synthesis and convergence are independent of the control torque, which leads to much convenience in establishing “separation property” when combining a proportional-derivative attitude tracking controller driven by angular velocity estimates. A rigorous stability analysis is provided to ensure the (almost) global asymptotic convergence of the overall closed-loop tracking errors, and several numerical simulations are carried out to demonstrate the effectiveness of the combined implementation of proposed angular velocity observer and full-state feedback attitude tracking controller.     

Adaptive tracking control for dynamic nonholonomic mobile robots with uncalibrated visual parameters

The trajectory tracking control problem of uncertain dynamic nonholonomic mobile robots is addressed in this paper. A novel uncertain camera‐object visual servoing kinematic tracking error model is proposed firstly. And then, on the basis of this model, a new adaptive torque tracking controller is presented in the presence of parametric uncertainties associated with the camera system and mechanical dynamic system. The controller synthesis is based on Lyapunov's direct method and backstepping technique. Simulation results are provided to illustrate the performance of the control law. Copyright © 2012 John Wiley & Sons, Ltd.     

A power‐performance tunable logic with adjustable threshold pseudo‐dynamic building blocks and CMOS compatibility

The continued downscaling of CMOS technology has resulted in very high performance devices, but power dissipation is a limiting factor on this way. Power and performance of a device are dependent on process, temperature, and workload variation that makes it impossible to find a single power optimal design. As a result, adaptive power and performance adjustment techniques emerged as attractive methods to improve the effective power efficiency of a device in modern design approaches. Focusing on this issue, in this paper, a novel logic family is proposed that enables tuning the transistor's effective threshold voltage after fabrication for higher speed or lower power. This method along with dynamic voltage scaling allows simultaneous optimization of static and dynamic power based on the workload requirement. The externally static topology of the proposed logic makes it possible to replace static circuits without requiring significant changes in the system. Experimental results obtained using 90‐nm CMOS standard technology show that the proposed logic improves the average power‐delay product by about 40% for the attempted benchmarks.     

Dual high‐gain‐based adaptive output‐feedback control for a class of nonlinear systems

We propose an adaptive output‐feedback controller for a general class of nonlinear triangular (strict‐feedback‐like) systems. The design is based on our recent results on a new high‐gain control design approach utilizing a dual high‐gain observer and controller architecture with a dynamic scaling. The technique provides strong robustness properties and allows the system class to contain unknown functions dependent on all states and involving unknown parameters (with no magnitude bounds required). Unlike our earlier result on this problem where a time‐varying design of the high‐gain scaling parameter was utilized, the technique proposed here achieves an autonomous dynamic controller by introducing a novel design of the observer, the scaling parameter, and the adaptation parameter. This provides a time‐invariant dynamic output‐feedback globally asymptotically stabilizing solution for the benchmark open problem proposed in our earlier work with no magnitude bounds or sign information on the unknown parameter being necessary. Copyright © 2007 John Wiley & Sons, Ltd.     

基于新型模糊自适应惯量VSG的微网频率波动抑制

传统的恒输出校正因子模糊自适应惯量控制器的计算结果变化平缓,会导致在频率偏差接近许可值时无法提供足够的惯量以阻止频率进一步偏离.为解决该问题,提出了一种改进型模糊自适应惯量虚拟同步发电机(VSG)技术抑制微网频率波动.其创新性体现在提出了频率偏差界限的概念,并将其融入至模糊控制器设计过程中,实现了当微网频率偏差小于偏差...     

Decentralized adaptive multi‐dimensional Taylor network tracking control for a class of large‐scale stochastic nonlinear systems

This paper investigates the problem of adaptive multi‐dimensional Taylor network (MTN) decentralized tracking control for large‐scale stochastic nonlinear systems. Minimizing the influence of randomness and complex nonlinearity, which increases computational complexity, and improving the controller's real‐time performance for the stochastic nonlinear system are of great significance. With combining adaptive backstepping with dynamic surface control, a decentralized adaptive MTN tracking control approach is developed. In the controller design, MTNs are used to approximate nonlinearities, the backstepping technique is employed to construct the decentralized adaptive MTN controller, and the dynamic surface control technique is adopted to avoid the “explosion of computational complexity” in the backstepping design. It is proven that all the signals in the closed‐loop system remain bounded in probability, and the tracking errors converge to a small residual set around the origin in the sense of a mean quartic value. As the MTN contains only addition and multiplication, the proposed control method is more simplified and of good real‐time performance, compared with the existing control methods for large‐scale stochastic nonlinear systems. Finally, a numerical example is presented to illustrate the effectiveness of the proposed design approach, and simulation results demonstrate that the method presented in this paper has good real‐time performance and control quality, and the dynamic performance of the closed‐loop system is satisfactory.     

基于动态面控制的间接自适应神经网络块控制

针对一类可转化为"标准块控制形"的多输入多输出的非线性系统,基于动态面控制技术,提出一种间接自适应神经网络控制器的设计方案.该方法通过引入1阶滤波器,消除了后推设计中由于反复对虚拟控制的求导而导致的复杂性问题,同时完全避免了反馈线性化方法中可能出现的控制器奇异性问题,且无需控制增益矩阵正定、可逆的条件.利用李亚普诺夫方法,证明了闭环系统是半全局一致终结有界,通过适当选取设计常数,跟踪误差可收敛到原点的一个小邻域内.仿真结果表明所提控制方法的有效性.     

基于调整函数的永磁直线伺服电动机非线性自适应Back-stepping跟踪控制

对永磁直线伺服电动机提出基于调整函数的非线性自适应Back-stepping跟踪控制。在控制器设计中,提出一个新的设计思路,即d轴电流的动态规划:用某一参数估计的动态过程作为d轴电流的动态过程,只要参数估计值能精确估计未知参数,d轴电流必然收敛于零,从而直线伺服电动机获得最大电磁动力。仿真结果表明,本文推导出的控制律,利用不精确估计值,实现了永磁直线伺服电动机的加减速精确跟踪控制。     

Cooperative adaptive neural partial tracking errors constrained control for nonlinear multi‐agent systems

This paper considers the problem of partial tracking errors constrained for high‐order nonlinear multi‐agent systems in strict‐feedback form. In the control design, radial‐based function neural networks are utilized to identify uncertain nonlinear functions, and a cooperative adaptive dynamic surface control is proposed to avoid the explosion of complexity in the backstepping technique. Based on the minimal learning parameter technique and the predefined performance approach, a novel cooperative adaptive neural network control method is developed. The proposed controller is able to guarantee that all the closed‐loop network signals are cooperative semi‐globally uniformly ultimately bounded, and partial tracking errors confine all times within the predefined bounds. Finally, simulation example and comparative example with previous methods are given to verify and clarify the effectiveness of the new design procedure. Copyright © 2016 John Wiley & Sons, Ltd.     

A highly sensitive and ultra low‐power forward body biasing circuit to overcome severe process,voltage and temperature variations and extreme voltage scaling

Dynamic voltage scaling is one of the most popular methods used to reduce energy consumption in today's digital electronic systems. However, addressing process, voltage and temperature variations at subthreshold voltages has become an inevitable procedure. Using a variation‐sensitive and ultra low‐power design, this paper proposed a novel technique capable of sensing and responding to process, voltage and temperature variations as well as dynamic voltage scaling by providing an appropriate forward body bias so that energy‐delay product of the whole system was improved. Theoretical analysis for process variation probability, confirmed by post‐layout HSPICE (Synopsys, Inc., Mountain View, CA) simulations for an 8‐bit pipelined Kogge–Stone adder, showed that the circuit performance was enhanced in severe variations and extreme voltage scaling situation. For this adder, for example, assuming a voltage scaling from 0.8 to 0.3 V and temperature changes of ?15 to 75 °C, the proposed technique brought about a seven times less delay variation, whereas energy‐delay product improved by 23% compared with a zero body biased adder. Copyright © 2013 John Wiley & Sons, Ltd.     

基于改进型粒子群算法的扩张状态观测器

为了解决自抗扰控制器核心模块的参数难以整定的问题,提出了利用改进型粒子群算法的扩张状态观测器设计方法。研究了扩张状态观测器的数学模型,分析了影响观测信号跟踪精度的因素,给出了待定参数设计方法的具体步骤。该设计方法选择改进后的适应度函数作为性能优化指标,增加了惯性系数的自适应性,并引入速度钳制以防止陷入局部最优。最后通过计算和仿真实验分析,验证了所提方法的正确性和鲁棒性,对解决自抗扰控制器中其他模块的待定参数整定问题具有一定的意义。     

采用GA提高模糊控制器适应性的方法及应用研究

对于工业控制中广泛存在的多容量、大惯性、大延迟的被控对象,模糊控制是一种较有效的方法,模糊控制中隶属函数的正确选择是模糊控制器设计的关键,针对传统的获取隶属度函数方法的不足,本文设计了一种基于遗传算法的模糊控制器,系统采用遗传算法优化模糊控制器的隶属函数及其量化因子和比例因子的初值.仿真结果表明,采用该算法设计的模糊控制器较传统的PID控制器与模糊控制器具有鲁棒性强、超调量小的特点.这种改进型的模糊控制器具有良好的控制性能,体现了遗传算法在参数寻优方面的优越性.     

Adaptive interconnection and damping assignment passivity-based control for linearly parameterized discrete-time port controlled Hamiltonian systems via I&I approach

In this paper, discrete-time adaptive control of linearly parameterized fully actuated Port-controlled Hamiltonian systems with parameter uncertainties in energy function is considered. A discrete-time adaptive interconnection and damping assignment passivity-based control (IDA-PBC) method, utilizing the immersion and invariance (I&I) approach, for the considered uncertain Hamiltonian system, is presented. A discrete-time parameter estimator based on the immersion and invariance approach is derived to obtain an automatic tuning mechanism for the IDA-PBC controller. The stability analysis for the estimator and the closed-loop system is done using the Lyapunov theory. The proposed method is applied to two fully actuated physical systems and its performance is tested by simulations. Simulation results show that the proposed I&I-based adaptive IDA-PBC controller successfully preserves the performance of the IDA-PBC controller designed with true parameters under a large amount of uncertainty.     

基于改变比例因子的变步长最大功率跟踪算法

通过仿真模拟分析光伏电池特性,针对传统的变步长电导增量(INC)法存在无法同时满足跟踪速率和减少振荡的问题,提出了一种基于改变步长比例因子的变步长最大功率算法,实时判断工作点的状态来选择不同的步长比例因子,从而解决MPPT控制过程中动态响应和稳态波动的这一矛盾关系。仿真结果表明:改进的算法和传统的变步长INC相比,跟踪过程更快速,跟踪结果更精确,系统输出功率在最大功率点处的振荡得以有效降低,动态性能和稳态性能都更优异。     

Simple approximate phase cancellation for repetitive control of CVCF PWM inverters

In this paper, a simple approximate phase cancellation repetitive controller is proposed for a constant‐voltage constant‐frequency pulse‐width modulation inverter. The compensator is a linear combination of linear phase compensators, which can better fit the inverse of a plant model phase curve compared with the conventional linear phase compensator. Repetitive controllers with the proposed phase compensator can improve pulse‐width modulation inverter system's stability, tracking accuracy, and error convergence rate. An optimization method is applied to design the parameters of the proposed phase compensation repetitive controller. Analysis and design of the proposed repetitive controller are presented. Furthermore, simulations and experiments are provided to demonstrate the advantages of the approximate phase cancellation repetitive controller design.     

基于改进型最小二乘法的感应电机转动惯量辨识

为减小感应电机转动惯量对机械特性的影响,基于最小二乘法,引入开关控制器,构建了一种新型的最小二乘参数辨识器。当转动惯量发生变化时,通过开关控制对辨识器进行初始化,实现对参数更快更好地在线辨识。仿真试验表明:该方法克服了传统的带遗忘因子的最小二乘辨识器的波动现象,辨识速度快,精度高,可以有效提高系统的性能。     

基于机电扰动传播特性的电网惯量分布辨识方法

大规模新能源通过电力电子设备并入电网,影响电力系统的动态运行特性。惯量是反映电网抗频率扰动能力的重要特性指标。基于机电扰动传播特性建立数学模型,通过分析扰动传播速度与惯量之间的映射关系,提出了电网母线节点的惯量分布辨识方法,实现对电网不同节点的频率抗扰动能力的在线评估。基于惯量分布结果,进一步评估了新能源接入对电力系统惯量特性的影响。通过IEEE 39节点系统仿真验证了所提惯量分布辨识方法的有效性,分析了新能源接入对电网惯量分布的影响。     

发电机的浸入与不变自适应反步鲁棒励磁控制器

针对含有不确定参数的发电机励磁控制系统,设计了一种新型的自适应反步鲁棒励磁控制器。在设计过程中,基于反步法逐步进行控制器的设计,并引入非线性阻尼算法来减小反步法的"计算膨胀"问题,有效地增强了控制器的鲁棒性。接着介绍了应用浸入与不变自适应控制设计阻尼系数的自适应估计律。通过MATLAB软件进行仿真研究,验证了该算法的有效性和优越性。     

A study on robust adaptive modulation controller for TCSC based on COI signal in interconnected power systems

This paper proposes a novel robust adaptive modulation controller (RAMC) for thyristor controlled series capacitor (TCSC) in interconnected power systems to damp low frequency oscillation. The main idea of the controller is to drive the area centers of inertia (COI) to a stable equilibrium point and keep system synchronization. COI-coordinate-based model is derived first. Then RAMC for TCSC is derived using back-stepping method with COI dynamic signals from WAMS. The new controller performance is tested through a three-area power system and the simulation results show clearly that the new controller using COI signals has superior performance as compared with the conventional controller.     

带变惯量负载的感应电机模糊控制策略研究

文章对带非线性变惯量负载下感应电机控制系统提出了几种模糊控制策略.将数学模型和启发式学习方法、模糊逻辑和线性多变量控制技术相结合设计了矢量控制系统中的内部电流控制器;采用基于模糊模型的预测控制技术设计了系统外部的转速/位置控制环,以解决电机模型和负载情况的非线性特性.在非线性动态过程的建模中,融入了模糊逻辑和局部线性模型.仿真和实验结果显示,这种新颖的模糊控制策略具备优良的动态性能、较高的鲁棒性,完全满足高精度位置伺服系统的要求.