Robust Adaptive Control of Nonholonomic Systems with Nonlinear Parameterization

全球适应的州的反馈控制策略与强壮的非线性的飘移和未知非线性的参数在锁住的形式为 nonholonomic 系统的一个类被介绍。一种参数分离技术被介绍把非线性的 parameterization nonholonomic 系统转变成一个象线性一样 parameterized nonholonomic 系统。然后，反馈支配设计被使用设计一个全球适应稳定控制器，切换的策略被开发消除 uncontrollability 的现象。建议控制器能保证那得到状态全球性集成到起源的所有系统，当另外的信号仍然保持围住时。模拟例子表明有效性和建议控制器的柔韧的特征。

Parameterized design of nonlinear feedback controllers for servo positioning systems

To achieve fast, smooth and accurate set point tracking in servo positioning systems, a parameterized design of nonlinear feedback controllers is presented, based on a so-called composite nonlinear feedback （CNF） control technique. The controller designed here consists of a linear feedback part and a nonlinear part. The linear part is responsible for stability and fast response of the closed-loop system. The nonlinear part serves to increase the damping ratio of closed-loop poles as the controlled output approaches the target reference. The CNF control brings together the good points of both the small and the large damping ratio cases, by continuously scheduling the damping ratio of the dominant closed-loop poles and thus has the capability for superior transient performance, i.e. a fast output response with low overshoot. In the presence of constant disturbances, an integral action is included so as to remove the static bias. An explicitly parameterized controller is derived for servo positioning systems characterized by second-order model. Practical application in a micro hard disk drive servo system is then presented, together with some discussion of the rationale and characteristics of such design. Simulation and experimental results demonstrate the effectiveness of this control design methodology.

FBFN-based adaptive repetitive control of nonlinearly parameterized systems

An adaptive repetitive control scheme is presented for a class of nonlinearly parameterized systems based on the fuzzy basis function network （FBFN）. The parameters of the fuzzy rules are tuned with adaptive schemes. To attenuate chattering effectively, the discontinuous control term is approximated by an adaptive PI control structure. The bound of the discontinuous control term is assumed to be unknown and estimated by an adaptive mechanism. Based on the Lyapunov stability theory, an adaptive repetitive control law is proposed to guarantee the closed-loop stability and the tracking performance. By means of FBFNs, which avoid the nonlinear parameterization from entering into the adaptive repetitive control, the controller singularity problem is solved. The proposed approach does not require an exact structure of the system dynamics, and the proposed controller is utilized to control a model of permanent-magnet linear synchronous motor subject to significant disturbances and parameter uncertainties. The simulation results demonstrate the effectiveness of the proposed method.

Experimental Evaluation of Parameterized Nonlinear MPC Applied to PEM Fuel Cell

This paper proposes a parameterized nonlinear model-based predictive control (NMPC) strategy to tackle the oxygen excess ratio regulation challenge of a proton exchange membrane fuel cell. In practice, the most challenging part regarding NMPC strategies remains the on-line implementation. In fact, NMPC strategies, at least in their basic form, involve heavy computation to solve the optimization problem. In this work, a specific parameterization of control actions has been designed to address this limitation and achieve on-line implementation. To assess the effectiveness and relevance of the proposed strategy, the controller has been implemented on-line, experimentally validated on a real fuel cell and compared to the built-in controller. Performance of the parameterized NMPC controller in terms of setpoint tracking accuracy, disturbances rejection and computational cost, have tested under several control scenarios. Experimental results have shown the excellent tracking capability, disturbances rejection ability and low computational cost of the NMPC controller, regardless of the operating conditions. Moreover, compared to the built-in controller the proposed strategy has demonstrated better disturbances rejection capability. Overall, the proposed parameterized NMPC controller appears as an excellent candidate to address the oxygen excess ratio regulation issue.

Advances in structural vibration control application of magneto-rheological visco-elastomer

Magneto-rheological visco-elastomer （MRVE） as a new smart material developed in recent years has several significant advantages over magneto-rheological liquid. The adjustability of structural dynamics to random environmental excitations is required in vibration control. MRVE can supply considerably adjustable damping and stiffness for structures, and the adjustment of dynamic properties is achieved only by applied magnetic fields with changeless structure design. Increasing researches on MRVE dy- namic properties, modeling, and vibration control application are presented. Recent advances in MRVE dynamic properties and structural vibration control application including composite structural vibration mitigation under uniform magnetic fields, vibration response characteristics improvement through harmonic parameter distribution, and optimal bounded parametric control design based on the dynamical programming principle are reviewed. Relevant main methods and results introduced are beneficial to understanding and researches on MRVE application and development.

A CALCULATION OF OPTIMAL FLIGHT TRAJECTORY USING THE PARAMETERIZED OPTIMIZATION METHOD

ＡＣＡＬＣＵＬＡＴＩＯＮＯＦＯＰＴＩＭＡＬＦＬＩＧＨＴＴＲＡＪＥＣＴＯＲＹＵＳＩＮＧＴＨＥＰＡＲＡＭＥＴＥＲＩＺＥＤＯＰＴＩＭＩＺＡＴＩＯＮＭＥＴＨＯＤＡＣＡＬＣＵＬＡＴＩＯＮＯＦＯＰＴＩＭＡＬＦＬＩＧＨＴＴＲＡＪＥＣＴＯＲＹＵＳＩＮＧＴＨＥＰＡＲＡ...

过载和攻击时间约束下的非线性最优制导方法

考虑导弹过载受限条件下,对以期望时间为攻击目标的非线性最优制导问题进行了研究。首先,建立了非线性最优制导问题的理论模型,基于庞特里亚金极大值原理和饱和函数方法建立了最优轨迹的最优性条件。其次,根据最优性条件和哈密尔顿轨迹参数化方法,建立了最优轨迹的参数化微分方程组,使得通过数值积分即可生成从飞行状态到最优制导指令映射关系的数据集。然后,通过前馈神经网络对上述映射关系进行近似,实现了非线性最优制导指令的毫秒量级实时生成。最后,通过数值仿真验证了所提非线性最优制导指令生成方法的有效性。

基于最小二乘法的欠驱动水面船舶模型预测控制

针对欠驱动水面船舶轨迹跟踪控制问题,根据模型预测控制(Model Predictive Control, MPC)原理,提出一种基于参数化模型的非线性模型预测控制(Parameterized Model-Nonlinear Model Predictive Control, PM-NMPC)方法。采用最小二乘法对船舶的参数化模型进行辩识,设计PM-NMPC控制器。对环境干扰下的某集装箱船艏向角控制和轨迹跟踪进行试验,验证控制算法的有效性,并将该控制器与比例积分微分控制器(Proportional plus Integral plus Derivative cotroller, PID cotroller)控制器进行对比。仿真结果表明,PM-NMPC控制器轨迹跟踪效果更好,对未知干扰具有更强的稳健性。

非线性参数化系统的鲁棒自适应控制器的设计和仿真

本文介绍了针对单摆模型,这个非线性参数化系统的鲁棒自适应控制,给出了参数自适应律和控制律,使得单摆模型很快跟踪上参考信号,且系统内各变量都全局有界。

基于控制参数化方法的列车节能操纵优化研究

以列车运行全过程牵引能耗最小为目标,综合考虑定时、变坡道、线路限速、牵引力和制动力限制以及驾驶舒适度等约束条件,建立列车节能操纵最优控制模型。基于控制参数化方法,将列车节能操纵最优控制问题转化为以线路子分段上的列车控制力为优化参数的非线性规划问题。为克服常规方法不能有效处理阶梯状线路限速的不足,提出一种离散化方法,使无限维状态约束简化为有限维不等式约束。针对牵引力上边界约束随速度非光滑变化的特点,利用二次函数对列车牵引特性曲线进行光滑化近似,进而将上边界约束转化为不等式约束,最终得到的非线性规划问题可由序列二次规划算法求解。仿真结果表明:该算法能够在精确满足所有约束的前提下,有效获取列车节能最优操纵序列及相应的参考速度曲线。

非线性约束系统H_∞鲁棒预测控制

针对一类具有状态约束和控制约束的离散非线性系统,本文采用有限维参数化方法提出了一种基于闭环优化的H∞鲁棒预测控制算法.这种算法把预测控制的滚动优化机制同微分对策理论和非线性H∞控制理论做了有机结合;在闭环优化中通过有限维参数化方法把控制变量参数化为多项式控制变量,并且引入被控系统的过渡平衡点.这样算法不但可以处理不确定系统,而且降低了在线闭环优化的计算复杂度.进一步,证明了算法的可行性和对有界不确定性系统的鲁棒稳定性.最后,用数值仿真验证了算法的有效性.

一类非线性参数系统的鲁棒自适应控制

针对一类具有非线性参数和未知非线性的非线性系统 ,提出了一种鲁棒自适应控制设计方法 ,该方法能保证所有信号全局一致有界 。

一类纯反馈非仿射非线性系统的自适应神经网络变结构控制

研究了一类非仿射的纯反馈单输入单输出非线性系统。针对此系统,在中值定理、神经网络参数化和解耦Backstepping的基础上,提出了一种自适应变结构神经网络控制策略,而且所给出的定理证明闭环系统的所有信号在平衡点上是半全局一致有界的。通过对一个非仿射CSTR对象的仿真验证了该方法的有效性。

用参数最优化方法计算最优飞行轨迹

介绍了如何应用参数最优化方法将具有状态变量不等式约束和控制变量不等式约束以及终端等式约束的最优控制问题转化为静态非线性规划问题，并提出了将求解静态约束最优化问题的系贯加权因子法，即ＳＷＩＦＴ（ＳｅｑｕｅｎｔｉａｌＷｅｉｇｈｔ－ＩｎｃｒｅａｓｉｎｇＦａｃｔｏｒＴｅｃｈｎｉｑｕｅ）法推广为求解动态约束最优化问题的增广ＳＷＩＦＴ法。最后用计算美国航天飞机的返回最优轨迹说明了该法的可行性。

双参数动力学系统的自适应混沌控制

在线性微扰参数自适应控制方法的基础上,讨论了基于非线性微扰的m维双参数动力学系统中的混沌自适应控制问题.以Henon映射为例的数值研究表明,该方法无须等待系统靠近待控的目标轨道就可加入控制,因此优于线性微扰参数自适应控制.

一类非线性系统的直接自适应控制器

针对带一类非线性参数系统的状态反馈自适应跟踪控制问题 ,通过设计一种新的李亚普诺夫函数———加权控制李亚普诺夫函数 ,由它作用于控制器和参数调整律 。

一类非线性系统鲁棒自适应控制器

反步设计法是针对不确定非线性系统的进行鲁棒自适应控制器设计的主要方法之一,它主要是靠递推来完成,方法简单,但存在过参数化问题。在反步设计法的基础上,通过引入调节函数,选取合适的虚拟控制律,设计一种鲁棒自适应控制器。然后,利用Lyapunov稳定性理论证明了该设计不仅能够克服过参数化的问题,而且能够保证所设计的系统具有鲁棒自适应稳定性。仿真实例证明了该方法的有效性。

直线电机位置伺服系统的增强复合非线性控制

针对高性能机电系统中常用的直线伺服电机,设计了一个能实现快速与准确的定点运动的位置控制器。控制器采用线性控制律与平滑非线性控制律相结合的方案,并利用一个降阶线性状态观测器对电机运动速度(未量测)加以估计。为了消除未知扰动带来的稳态误差,控制律中嵌入了积分控制作用。整个控制律采用全参数化设计,可实现动态增益控制,方便了在线参数整定与性能优化。控制方案应用于一个实际的永磁直线电机位置伺服系统,基于TMS320F28335 DSC进行了试验测试,结果表明系统能对各目标位置进行准确的跟踪,且具有理想的瞬态性能。

Active Disturbance Rejection Control for PMLM Servo System in CNC Machining

Uncertain friction is a key factor that influences the accuracy of servo system in CNC machine.In this paper,based on the principle of Active Disturbance Rejection Control(ADRC),a control method is proposed,where both the extended state observer(ESO) and the reduced order extended state observer(RESO) are used to estimate and compensate for the disturbance.The authors prove that both approaches ensure high accuracy in theory,and give the criterion for parameters selection.The authors also prove that ADRC with RESO performs better than that with ESO both in disturbance estimation and tracking error.The simulation results on CNC machine show the effectiveness and feasibility of our control approaches.

微生物批式流加发酵中的最优控制

提出了一个非线性动力系统用以描述微生物批式流加发酵生产1,3-丙二醇过程。以终端时刻1,3-丙二醇的浓度作为性能指标且以甘油和碱的流加速度作为控制函数,研究了含状态和控制约束的最优控制问题。最后,基于控制参数化方法和改进的差分演化算法构造了一种求解最优控制问题的计算方法。数值分析结果表明与已有结果相比,终端时刻1,3-丙二醇的浓度有显著提高。