一类非线性系统的积分变结构模糊自适应跟踪控制

针对一类具有未知常数控制增益的不确定非线性系统,基于变结构控制原理,并利用具有非线性可调参数的模糊系统逼近等价控制,提出一种具有监督控制器的积分变结构模糊自适应跟踪控制策略.该策略通过监督控制器保证闭环系统所有信号有界.进一步,通过引入最优逼近误差的自适应补偿项来消除建模误差的影响.理论分析证明了跟踪误差能够收敛到零.仿真结果表明了该方法的有效性.     

机电控制系统的模型参考自适应控制

本文给出一种可供机电控制系统应用的自适应算法,其在调速系统中的应用说明了这种算法是可行的。当对象的转动惯量、外加负载以及放大倍数发生大范围变化时,控制系统的性能保持不变。系统用TP801单板机作为控制器,完成全部的自适应算法。     

Adaptive observer and nonlinear control strategy for chemical reactors via neural networks

An adaptive observer and nonlinear feedback control strategy with constraints on control action are developed by using a supervised learning rule of a neural network and the theory of functional-link networks. The convergence of the adaptive observer and the stability of the control system are proven. They are applied to the control of an exothermic stirred-tank reactor. It is shown that an adaptive observer for concentration can be constructed for a reaction system when only temperature measurements are available on line. An adaptive observer is used to identify the pre-exponential Arrhenius constant and to provide on line estimation of the unmeasured reactant concentration for a nonlinear state-feedback controller. Simulations show that the combined observer/controller provides satisfactory closed-loop behaviour, fast responses and strong robustness. Estimated and actual concentration are in good agreement. A nonlinear feedback controller can provide effective feedback control over a wide range of operating conditions.     

Tuning an adaptive controller using a robust control approach

This article proposes a new technique for the tuning of a discrete adaptive controller that is designed based on Lyapunov stability concepts. The tuning is based on the minimisation of a performance index that can be calculated from a generalised eigenvalue problem (GEVP) using LMI's (Linear Matrix Inequalities). The proposed technique results in an adaptive controller with time-varying tuning gains. The solution is based on an approximation of the optimal dual adaptive control problem. The tuning technique was used to perform on-line control of a first-order system and an isothermal and a non-isothermal CSTR. The results show that the proposed approach provides better performance than an adaptive algorithm with the same structure, but with constant adaptation gains. Also, the proposed algorithm is shown to be superior to an adaptive controller based on a Recursive Least Squares (RLS) estimator during sudden changes in model parameters.     

Development and analysis of adaptive fuzzy controllers for photovoltaic system under varying atmospheric and partial shading condition

Control of power electronics converters used in PV system is very much essential for the efficient operation of the solar system. In this paper, a modified incremental conduction maximum power point tracking (MPPT) algorithm in conjunction with an adaptive fuzzy controller is proposed to control the DC–DC boost converter in the PV system under rapidly varying atmospheric and partial shading conditions. An adaptive hysteresis current controller is proposed to control the inverter. The proposed current controller provides constant switching frequency with less harmonic content compared with fixed hysteresis current control algorithm and sinusoidal PWM controller. The modeling and simulation of PV system along with the proposed controllers are done using MATLAB/SIMSCAPE software. Simulation results show that the proposed MPPT algorithm is faster in transient state and presents smoother signal with less fluctuations in steady state. The hardware implementation of proposed MPPT algorithm and inverter current control algorithms using Xilinx spartran-3 FPGA is also presented. The experimental results show satisfactory performance of the proposed approaches.     

Design of adaptive robust guaranteed cost controller for wind power generator

According to the increasing requirement of the wind energy utilization and the dynamic stability in the variable speed variable pitch wind power generation system, a linear parameter varying (LPV) system model is established and a new adaptive robust guaranteed cost controller (AGCC) is proposed in this paper. First, the uncertain parameters of the system are estimated by using the adaptive method, then the estimated uncertain parameters and robust guaranteed cost control method are used to design a state feedback controller. The controller’s feedback gain is obtained by solving a set of linear matrix inequality (LMI) constraints, such that the controller can meet a quadratic performance evaluation criterion. The simulation results show that we can realize the goal of maximum wind energy capture in low wind speed by the optimal torque control and constant power control in high wind speed by variable pitch control with good dynamic characteristics, robustness and the ability of suppressing disturbance.     

Adaptive tracking and asymptotic rejection of unknown but bounded disturbances in nonlinear MIMO systems

The goal of this paper is global disturbance rejection in nonlinear systems. An output feedback controller with disturbance rejection is developed for a class of nonlinear multi input-multi output (MIMO) systems. The availability of state variables and the bound of disturbances are not required to be known in advance and reference tracking will is guaranteed. By the aid of designing an adaptive observer, a robust adaptive nonlinear state feedback controller using the estimated states is proposed. For tracking problem, an adaptive pre-compensator is used. The control methodology is robust against both constant and time varying bounded disturbances, maintaining effective performance. The adaptive laws are derived based on the Lyapunov synthesis method, therefore closed-loop asymptotic stability is also guaranteed. Moreover, for chattering reduction we use a low-pass filter. Consequently, small gain theorem is adopted to prove the stability of the closed-loop system. Simulation results are employed to illustrate the effectiveness of the proposed controller.     

X-Q自适应PID及其在多目标满意控制系统中的应用

给出一种新型X-Q自适应控制器,它具有新颖的自适应频率特性对于控制信号而言,它是一个没有任何相位落后的PID,且高频段为一放大倍数为k的放大器,低频段为一积分时间常数为     

掘进机恒功率自适应调速与记忆截割系统研究

由于掘进机在进给过程中截割头工作面负载变化存在随机性且幅度很大,设计并开发一套以可编程序控制器为数据采集和控制核心,上位机采用组态软件构建远程监控系统的掘进机自适应控制系统,采用多信息融合技术综合分析负载的变化,实现恒功率自适应调速,同时采用记忆截割与自适应调节相结合的控制方法,在记忆截割的基础上根据反馈信号进行局部调节,更新记忆曲线,保证掘进机的恒功率进给,延长掘进机截割头的使用寿命.     

Stable multirate algorithm for robust adaptive control

A new multirate adaptive control algorithm for plants with unmodelled dynamics and bounded disturbances is presented. Different rates are employed for parameter estimation, controller design and controller implemeniation. A modified constant trace least-square algorithm with dead zone and pole placement are used for the algorithm, It is shown that the closed-loop system is globally stable and that set point tracking can be well achieved.     

时滞系统关于时滞参数的自适应输出反馈控制

对存在状态时滞的线性时滞系统，给出符合分离性原理的动态输出反馈控制器形式，当时滞参数不能精确已知时，给出基于观测器的关于时滞参数的自适应动态输出反馈控制器设计方案，通过求解两个相应的Riccati型矩阵不等式即可求得满足设计要求的动态输出反馈控制器及关于时滞参数的自适应律，且控制器的存在性与时滞参数精确已知时相同．最后给出了一个应用仿真示例．     

AUV深度的神经网络辨识和学习控制仿真研究

将自主水下航行器（AUV）的深度控制问题转换为对非线性严格反馈系统的分析,提出了一种结合反步法和确定学习理论的自适应学习控制方法。通过反步法设计了一种输入状态稳定（ISS）神经网络控制器,其中引入小增益定理,避免了控制器设计中存在的奇异值问题,并在满足持续激励（PE）条件下,利用神经网络辨识实现了对系统未知动态的局部准确逼近和部分神经网络权值的收敛,保证了闭环系统的稳定。将从动态模式中学到的知识静态保存,提取动态特征设计学习控制器,仿真结果表明,该控制器避免了执行同样任务时的重复训练,改善了系统控制性能,验证了所提控制方法的有效性。     

A Neuro-interface with fuzzy compensator for controlling nonholonomic mobile robots

This paper describes a control method for mobile robots represented by a nonlinear dynamical system, which is subjected to an output deviation caused by drastically changed disturbances. We here propose some controllers in the framework of neuro-interface. It is assumed that a neural network (NN)-based feedforward controller is construcetd by following the concept of virtual master-slave robot, in which a virtual master robot as a feedforward controller is used to control the slave (i.e., actual) robot. The whole system of the present neuro-interface consists of an NN-based feedforward controller, a feedback PD controller and an adaptive fuzzy feedback compensator. The NN-based feedforward controller is trained offline by using a gradient method, the gains of the PD controller are to be chosen constant, and the adaptive fuzzy compensator is constructed with a simplified fuzzy reasoning. Some simulations are presented to confirm the validity of the present approach, where a nonholonomic mobile robot with two independent driving wheels is assmued to have a disturbance due to the change of mass for the robot.     

奇异时滞系统对时滞参数的自适应控制

针对一类状态时滞奇异系统,研究状态反馈控制器的设计问题。基于Lyapunov稳定性理论和线性矩阵不等式（LMI）工具,当时滞常数精确已知时,设计带有记忆的状态反馈控制器,使得相应的闭环系统渐近稳定;当时滞常数不能精确已知时,通过求解相应的线性矩阵不等式,得到满足设计要求的对时滞参数的自适应控制器,使得时滞系统镇定。最后,仿真实例表明此方法的有效性。     

一类非自治混沌系统的自适应脉冲同步

研究了一类具有未知Lipschitz常数的非自治混沌系统的自适应脉冲同步问题.首先基于Lyapunov稳定性理论、自适应控制理论及脉冲控制理论设计了自适应控制器、脉冲控制器及参数自适应律,然后利用推广的Barbalat引理,理论证明响应系统与驱动系统全局渐近同步,并给出了相应的充分条件.两个数值仿真例子表明本方法的有效性.     

A robust adaptive controller for constant turning force regulation

A robust adaptive controller for the constant turning force regulation problem under varying cutting conditions is presented. The control structure is an RST pole-placement controller based on a shaping method of the output sensitivity function proposed by Landau. The controller scheme is robust in the presence of cutting process nonlinearities and disturbances. The proposed adaptive scheme uses an estimation and controller algorithm including prior knowledge of the system. Simulations and experimental results obtained with an industrial lathe show the effectiveness of the proposed solution.     

Adaptive Fuzzy PD+ Control for Attitude Maneuver of Rigid Spacecraft

In this paper, an adaptive fuzzy PD+ controller is proposed for the attitude maneuver of rigid spacecraft. The novel controller adjusts the gains of the PD+ attitude controller online according to attitude errors and angular velocity errors during the maneuver procedure. Therefore, quick response and avoidance of actuator saturation can be achieved simultaneously. Furthermore, the adaptation mechanism is designed, based on Lyapunov theory, to guarantee the stability of the closed‐loop system. To achieve good performance of the closed‐loop system under the constraint of actuator saturation, controller parameter optimization is developed on the basis of a genetic algorithm. Simulation results show that the transient performance and robustness against parametric uncertainty and environmental disturbance of the adaptive fuzzy PD+ controller are better than those of a constant PD+ controller.     

一类不确定非线性系统基于特征模型的复合自适应控制

针对一类不确定非线性系统的跟踪控制问题,提出一种基于特征模型的复合自适应控制方法.该方法的创新性在于基于系统的误差特征模型,构建一种综合跟踪控制误差和模型估计误差的特征参量复合自适应律,该自适应律用于控制器设计和分析,可同时实现跟踪控制误差和模型估计误差的收敛.此外,为便于特征参量自适应律的设计和分析,根据特征参量的慢时变特性,将其视为未知标称常数项和时变误差项之和,并且选用其中常数项的估计量作为自适应控制参数.进一步,为抑制特征参量中时变误差项对系统稳定性和模型估计误差收敛性的影响,在控制器及复合自适应律设计中引入带饱和函数的非线性环节.理论分析证明闭环控制系统稳定,且跟踪控制误差和模型估计误差收敛到原点的一个邻域内.仿真结果表明,与现有仅根据模型估计误差调节的基于特征模型的自适应控制方法相比,所提出的复合自适应控制方法具有更好的控制性能.     

基于非线性L1自适应动态逆的飞行器姿态角控制

钊对常规动态逆控制器不能有效抵消系统中的不确定性这一缺点,提出了一种非线性L_1自适应动态逆控制方法.该方法能够克服常规动态逆的不足,在保证系统鲁棒性的前提下,提升飞行器姿态角控制效果.首先,采用时标分离原理,将姿态角控制系统分为内外两个回路:外回路采用常规动态逆控制器,用于姿态角的跟踪控制;内回路采用非线性L_1自适应控制器,用于角速率的控制.其中,L_1自适应控制器由静态反馈控制器和自适应控制器组成:静态反馈控制器通过状态反馈实现,用于保证内回路的稳定和具有期望的闭环特性;自适应控制器由状态观测器、自适应律和控制律组成,用于抵消系统中的不确定性.其次,对所提控制方法的稳定性进行了分析,结果证明了该控制方法能够保证内回路的稳定和外回路的误差有界.最后,在综合考虑多种不确定性的情况下,将本文提出的非线性L_1自适应动态逆控制方法用于某无人飞行器姿态角控制,仿真结果验证了该控制方法的有效性和鲁棒性.     

Adaptive controller design for underwater snake robot with unmatched uncertainties

Because of hydrodynamic model error of the present dynamic model, there is a challenge in controller design for the underwater snake-like robot. To tackle this challenge, this paper proposes an adaptive control schemes based on dynamic model for a planar, underwater snake-like robot with model error and time-varying noise. The adaptive control schemes aim to achieve the adaptive control of joint angles tracking and the direction of locomotion control. First, through approximation and reducibility using Taylor expansion method, a simplified dynamics model of a planar amphibious snake-like robot is derived. Then, the L1 adaptive controller based on piecewise constant adaptive law is applied on the simplified planar, underwater snake-like robot, which can deal with both matched and unmatched nonlinear uncertainties. Finally, to control the direction of locomotion, an auxiliary bias signal is used as the control input to regulate the locomotion direction. Simulation results show that this L1 adaptive controller is valid to deal with different uncertainties and achieve the joint angles tracking and fast adaptive at the same time. The modified L1 adaptive controller, in which the auxiliary bias item is added, has the ability to change the direction of locomotion, that is, the orientation angle is periodic with arbitrarily given constant on average.