A novel adaptive backstepping design of turbine main steam valve control

The problem of transient stability for a single machine infinite bus system with turbine main steam valve control is addressed by means of a novel adaptive backstepping method in this paper. The recursive design procedure of the proposed controller is much simpler than that of the existing controller based on conventional adaptive backstepping method. In the system, the damping coefficient is measured inaccurately, and the reactance of transmission line also contains a few uncertainties. A nonlinear robust controller and parameter updating laws are obtained simultaneously. The system does not need to be linearized, and the closed-loop error system is guaranteed to be asymptotically stable. The design procedure and simulation results demonstrate the effectiveness of the proposed design.     

Controller design of high order nonholonomic system with nonlinear drifts

A controller design is proposed for a class of high order nonholonomic systems with nonlinear drifts. The purpose is to ensure a solution for the closed-loop system regulated to zero. Adding a power integrator backstepping technique and the switching control strategy are employed to design the controller. The state scaling is applied to the recursive manipulation. The simulation example demonstrates the effectiveness and robust features of the proposed method.     

Adaptive fuzzy dynamic surface control for uncertain nonlinear systems

In this paper, a robust adaptive fuzzy dynamic surface control for a class of uncertain nonlinear systems is proposed. A novel adaptive fuzzy dynamic surface model is built to approximate the uncertain nonlinear functions by only one fuzzy logic system. The approximation capability of this model is proved and the model is implemented to solve the problem that too many approximators are used in the controller design of uncertain nonlinear systems. The shortage of ＂explosion of complexity＂ in backstepping design procedure is overcome by using the proposed dynamic surface control method. It is proved by constructing appropriate Lyapunov candidates that all signals of closed-loop systems are semi-globally uniformly ultimate bounded. Also, this novel controller stabilizes the states of uncertain nonlinear systems faster than the adaptive sliding mode controller （SMC）. Two simulation examples are provided to illustrate the effectiveness of the control approach proposed in this paper.     

Robust stabilization of uncertain nonholonomic systems with strong nonlinear drifts

This paper investigates the robust stabilization of the nonholonomic control systems with strongly non- linear uncertainties. In order to make the state scaling effective and to prevent the finite time escape phenomenon from happening, the switching control strategy based on the state measurement of the first subsystem is employed to achieve the asymptotic stabilization. The recursive integrator backstepping technique is applied to the design of the robust controller. The simulation example demonstrates the efficiency and robust features of the proposed method.     

A new adaptive backstepping method for nonlinear control of turbine main steam valve

A new approach for nonlinear adaptive control of turbine main steam valve is developed. In comparison with the existing controller based on ＂classical＂ adaptive backstepping, this method does not follow the classical certaintyequivalence principle in the design of adaptive control law. We introduce this approach, for the first time, to power systems and present a novel parameter estimator and dynamic feedback controller for a single machine infinite bus （SMIB） system with steam valve control. This system contains unknown parameters such as reactance of transmission lines. Besides preserving useful nonlinearities and the real-time estimation of uncertain parameters, the proposed approach possesses better performances with respect to the response of the system and the speed of adaptation. The simulation results demonstrate that the proposed approach is better than the design based on ＂classical＂ adaptive backstepping in terms of properties of stability and parameter estimation, and recovers the performance of the ＂full-information＂ controller. Hence, the proposed method provides an alternative for engineers in applications.     

Adaptive fuzzy decentralized control for nonlinear large-scale systems based on high-gain observer

An adaptive fuzzy decentralized backstepping output-feedback control approach is proposed for a class of nonlinear large-scale systems with completely unknown functions,the interconnections mismatched in control inputs,and without the measurements of the states.Fuzzy logic systems are employed to approximate the unknown nonlinear functions,and an adaptive high-gain observer is developed to estimate the unmeasured states.Using the designed high-gain observer,and combining the fuzzy adaptive control theory with backstepping approach,an adaptive fuzzy decentralized backstepping output-feedback control scheme is developed.It is proved that the proposed control approach can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded(SUUB),and that the observer errors and the tracking errors converge to a small neighborhood of the origin by appropriate choice of the design parameters.Finally,a simulation example is provided to show the eectiveness of the proposed approach.     

The multi-objective optimal control with X - Q adaptive controller

This paper proposes a new type of nonlinear controllers and a large phase angle allowance design method based on the multi-objective optimal control system. With the proposed method, the performance of the system becomes better than that of the original system. Then, an example of the radar servo system is designed with a large phase angle allowance multi-objective optimal design method. Finally, the performance based on computer simulation demonstrates that the multi-objective optimal system is superior to linear optimal systems.     

Discretization of nonlinear non-affine time delay systems based on second-order hold

When calculating the sampled-date representation of nonlinear systems second-order hold(SOH) assumption can be applied to improving the precision of the discretization results. This paper proposes a discretization method based on Taylor series and the SOH assumption for the nonlinear systems with the time delayed non-affine input. The mathematical structure of the proposed discretization method is explored. This proposed discretization method can provide a precise and finite dimensional discretization model for the nonlinear time-delayed non-affine system by keeping the truncation order of the Taylor series. The performance of the proposed discretization method is evaluated by doing the simulation using a nonlinear system with the time-delayed non-affine input.Different input signals, time-delay values and sampling periods are considered in the simulation to investigate the proposed method.The simulation results demonstrate that the proposed method is practical and easy for time-delayed nonlinear non-affine systems.The comparison between SOH assumption with first-order hold(FOH) and zero-order hold(ZOH) assumptions is given to show the advantages of the proposed method.     

Adaptive sliding mode control for MIMO nonlinear systems based on fuzzy logic scheme

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.     

Sliding mode cont rol f or an aerodynamic missile based on backstepping design

In order to solve the mismatched uncertainties of a class of nonlinear systems ,a control method of sliding mode control (SMC) based on the backstepping design is proposed. It introduces SMC in to the last step of backstepping design to modify the backstepping algorithm. This combination not only enables the generalization of the backstepping design to be applied to more general nonlinear systems ,but also makes the SMC method become effective in solving the mismatched uncertainties. The SMC based on the backstepping design is applied to the flight control system design of an aerodynamic missile. The control system is researched through simulation. The simulation results show the effectiveness of the proposed control method.     

不确定非线性系统的自适应反推高阶终端滑模控制

针对一类非匹配不确定非线性系统,提出一种神经网络自适应反推高阶终端滑模控制方案.反推设计的前1步利用神经网络逼近未知非线性函数,结合动态面控制设计虚拟控制律,避免传统反推设计存在的计算复杂性问题,并抑制非匹配不确定性的影响;第步结合非奇异终端滑模设计高阶滑模控制律,去除控制抖振,使系统对于匹配和非匹配不确定性均具有鲁棒性.理论分析证明了闭环系统状态半全局一致终结有界,仿真结果表明了所提出方法的有效性.     

非匹配不确定非线性系统的自适应反演滑模控制

针对一类具有非匹配不确定性的最小相位仿射非线性系统,研究其在未知扰动作用下的调节问题。基于自适应反演设计方法和变结构控制设计了控制方案,实现不确定系统的鲁棒调节。与经典反演设计相比,本方案允许非参数化不确定性,增强了控制系统的鲁棒性。     

基于NDOB的匹配/非匹配不确定性系统滑模控制

针对一类n阶匹配与非匹配不确定性和扰动共存的系统,提出了一种新颖的基于非线性干扰观测器的滑模控制方法。将非匹配扰动的估计值融入到滑模面,设计了集成扰动观测的滑模控制。与传统的滑模控制方法相比,该方法在匹配与非匹配不确定性和扰动出现时具有较好的抑制能力,并能有效地抑制切换增益所引起的抖振现象。利用李雅普诺夫理论和输入-输出稳定性概念严格证明了闭环系统的稳定性。最后通过两个仿真实例验证了所提控制方法的有效性。     

Discrete-time adaptive sliding mode control for uncertain systems based on multi-rate output measurement

This article presents the design of a discrete-time adaptive sliding mode control (SMC) for uncertain systems using the noisy multi-rate output measurement. It is assumed that the dynamic systems are described by a discrete-time state equation with mismatched uncertainties. The proposed discrete-time adaptive SMC is composed of the equivalent and the nonlinear switching controls, and it is derived based on a new sliding surface. A new least squares estimator (LSE) to take the estimates for the un-measurable states and the uncertainties is designed without the information of the statistics for the measurement noises and the initial state. In the design of the proposed discrete-time adaptive SMC, the un-measurable states and the uncertainties are, respectively, replaced as their estimates obtained from the proposed LSE, and the sliding coefficient matrices are selected such that the states for the systems are ultimately bounded, and the effect of the external disturbances to give the states is reduced as small as possible. The effectiveness of the proposed method is indicated through the simulation experiment in a simple system.     

非匹配不确定系统的自适应反步非奇异快速终端滑模控制

针对一类n阶非匹配不确定系统,提出一种自适应反步非奇异快速终端滑模控制方法.控制的前n-1步采用自适应反步控制策略,消除非匹配不确定性的影响;最后一步利用误差的积分构造非奇异快速终端滑模面,设计控制律使系统第n个状态有限时间收敛.该方法对系统中匹配和非匹配不确定项均具有鲁棒性,比自适应反步终端滑模方法具有更快的收敛速度.理论分析证明了闭环系统的稳定性,仿真结果验证了该方法的有效性.     

基于块控原理的变结构控制

针对一类非匹配不确定性的线性系统 ,基于块控原理 ,提出了一种变结构控制设计方法 .利用反演设计方法来处理系统中的非匹配不确定性 ,再用变结构控制方法来改善系统的性能 .仿真实例证明了所提出的方法的正确性和有效性     

基于反步法的一类非线性切换系统控制器设计

研究一类子系统是纯反馈非线性系统的切换系统控制器设计问题．基于多Lyapunov函数和反步法，提出一种状态反馈控制律及切换规则设计方法。通过递推设计可得到使非线性切换系统稳定的反馈控制律和切换规则．将所提出的方法应用于该类非线性切换系统含有不确定性的情形，仿真算例结果表明了所提出方法的有效性．     

A New Adaptive Sliding Mode Control of Uncertain Nonlinear Systems

In this paper, a new adaptive sliding mode control is proposed to control nonlinear systems with parametric uncertainties and matched and unmatched external disturbances. The proposed method first combines immersion and invariance (I&I) adaptive scheme with sliding mode control (SMC), which preserves the advantages of the two methods. The proposed method is different from the approach of combining the backstepping adaptive scheme and sliding mode control in the parameter estimation law, which allows for prescribed dynamics to be assigned to the estimation error and is easier to tune. Finally, the method is applied to control a class of power systems, and simulation results show the advantages of the proposed method.     

基于神经网络的严反馈块非线性系统的鲁棒控制

针对非匹配不确定性的严反馈块非线性系统,基于神经网络提出一种鲁棒控制方法．利用Lyapunov稳定性定理推导出RBF神经网络的全调节律,用于处理系统中的非线性参数不确定性,提高了神经网络的在线逼近能力;采用神经网络和鲁棒控制方法,利用已知信息的同时,对控制系数矩阵未知时的设计问题进行处理,避免了控制器可能的奇异问题;引入非线性跟踪微分器,解决了Backstepping设计中的“计算膨胀”问题．运用Lyapunov稳定性定理证明了闭环系统的所有信号均最终一致有界．