BTT导弹神经网络自适应控制器设计

在导弹系统存在非匹配不确定性的情况下 ,提出了一种基于RBF神经网络和反演控制技术的神经网络自适应导弹控制系统的设计方法。首先应用RBF神经网络在线辨识系统中存在的不确定性 ,然后利用反演控制技术设计了导弹非线性自适应控制器 ,成功的处理了非匹配不确定性 ,并应用Lyapunov稳定性理论推导出RBF神经网络权重矩阵及中心点值的调节律 ,保证了系统的稳定性。证明了系统的所有信号均有界且全局指数收敛至原点的一个邻域。最后给出的BTT导弹非线性六自由度数字仿真结果显示了该设计方法的有效性。

某智能接驳车自主转向系统鲁棒性控制

智能转向系统作为自动驾驶关键落地技术之一,影响着智能接驳车转向性能。设计了一种在原有的线控转向的基础上去掉方向盘,转而由电机直接提供转向动力,驱动转向系统转向,实现车辆的智能驾驶功能。通过建立智能接驳车自主转向系统动力学方程,构建出车辆闭环控制系统,提出考虑被控对象参数或模型发生摄动时的自适应内模控制方法。将智能接驳车转向系统模型作为被控对象,当被控过程发生改变时,通过在线更新控制器,实现对前轮转角的鲁棒性控制。仿真和实验结果表明,与常规IMC控制相比较,该方法对模型摄动具有较好的控制效果,提高了转向控制系统的自适应性,增强了智能接驳车转向系统的鲁棒性。

Global Robust and Adaptive Output Feedback Dynamic Positioning of Surface Ships

A constructive method was presented to design a global robust and adaptive output feedback controller for dynamic positioning of surface ships under environmental disturbances induced by waves, wind, and ocean currents. The ship's parameters were not required to be known. An adaptive observer was first designed to estimate the ship's velocities and parameters. The ship position measurements were also passed through the adaptive observer to reduce high frequency measurement noise from entering the control system. Using these estimate signals, the control was then designed based on Lyapunov's direct method to force the ship's position and orientation to globally asymptotically converge to desired values. Simulation results illustrate the effectiveness of the proposed control system. In conclusion, the paper presented a new method to design an effective control system for dynamic positioning of surface ships.

Adaptive output feedback control for uncertain nonholonomic chained systems

An adaptive output feedback control was proposed to deal with a class of nonholonomic systems in chained form with strong nonlinear disturbances and drift terms. The objective was to design adaptive nonlinear output feedback laws such that the closed-loop systems were globally asymptotically stable, while the estimated parameters remained bounded. The proposed systematic strategy combined input-state-scaling with backstepping technique. The adaptive output feedback controller was designed for a general case of uncertain chained system. Furthermore, one special case was considered. Simulation results demonstrate the effectiveness of the proposed controllers.

Design and Simulation of Single Neuron Adaptive PID Controller

The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial neurons have the adaptive, parallel processing, selflearning learning, and mare fault-tolerant characteristics. When the artificial neurons are used to control the process, the syste^n will enabled to en-sure that the accused has strong anti-interference capability and ro. bustness.

Adaptive controller design based on input-output signal selection for voltage source converter high voltage direct current systems to improve power system stability

An input-output signal selection based on Phillips-Heffron model of a parallel high voltage alternative current/high voltage direct current(HVAC/HVDC) power system is presented to study power system stability. It is well known that appropriate coupling of inputs-outputs signals in the multivariable HVDC-HVAC system can improve the performance of designed supplemetary controller. In this work, different analysis techniques are used to measure controllability and observability of electromechanical oscillation mode. Also inputs–outputs interactions are considered and suggestions are drawn to select the best signal pair through the system inputs-outputs. In addition, a supplementary online adaptive controller for nonlinear HVDC to damp low frequency oscillations in a weakly connected system is proposed. The results obtained using MATLAB software show that the best output-input for damping controller design is rotor speed deviation as out put and phase angle of rectifier as in put. Also response of system equipped with adaptive damping controller based on HVDC system has appropriate performance when it is faced with faults and disturbance.

Multi-loop Constrained Iterative Model Predictive Control Using ARX -PLS Decoupling Structure

A multi-loop constrained model predictive control scheme based on autoregressive exogenous-partial least squares(ARX-PLS) framework is proposed to tackle the high dimension, coupled and constraints problems in industry processes due to safety limitation, environmental regulations, consumer specifications and physical restriction. ARX-PLS decoupling character enables to turn the multivariable model predictive control(MPC) controller design in original space into the multi-loop single input single output(SISO) MPC controllers design in latent space.An idea of iterative method is applied to decouple the constraints latent variables in PLS framework and recursive least square is introduced to identify ARX-PLS model. This algorithm is applied to a non-square simulation system and a stirred reactor for ethylene polymerizations comparing with adaptive internal model control(IMC) method based on ARX-PLS framework. Its application has shown that this method outperforms adaptive IMC method based on ARX-PLS framework to some extent.

THE FURTHER RESULT ON GLOBAL PRACTICAL TRACKING FOR HIGH-ORDER UNCERTAIN NONLINEAR SYSTEMS

This paper extends the unknown control coefficients with lower and upper constant bounds to the ones which may take arbitrarily large and /or small values.Since the existing methods are no longer applicable and the technical obstacles caused by the extensions are essential,new control design scheme should be exploited to the global practical tracking.By the approaches of Nussbaum-gain and adding a power integrator,the authors successfully propose the design scheme of the adaptive practical tracking controller for the systems.It is shown that the designed controller guarantees that all the closed-loop system states are bounded and the tracking error becomes prescribed arbitrarily small after a finite time.

L_1 adaptive controller design for hypersonic formation flight

The design of an L_1 adaptive controller for hypersonic formation flight is presented. The traditional leader/wingman formation control problem is considered, with focused attention on dealing with the input disturbance and parametric variations, both of which are intrinsic properties of the system that result in undesired control performance. A proportional-derivative control scheme based on nonlinear dynamic inversion is implemented as the baseline controller, and an L_1 adaptive controller is augmented to the baseline controller to attenuate the effects of input disturbance and parametric variations. Simulation results illustrate the effectiveness of the proposed control scheme.