An Energy Efficient Control Strategy for Electric Vehicle Driven by In-Wheel-Motors Based on Discrete Adaptive Sliding Mode Control

This paper presents an energy-efficient control strategy for electric vehicles(EVs)driven by in-wheel-motors(IWMs)based on discrete adaptive sliding mode control(DASMC).The nonlinear vehicle model,tire model and IWM model are established at first to represent the operation mechanism of the whole system.Based on the modeling,two virtual control variables are used to represent the longitudinal and yaw control efforts to coordinate the vehicle motion control.Then DASMC method is applied to calculate the required total driving torque and yaw moment,which can improve the tracking performance as well as the system robustness.According to the vehicle nonlinear model,the additional yaw moment can be expressed as a function of longitudinal and lateral tire forces.For further control scheme development,a tire force estimator using an unscented Kalman filter is designed to estimate real-time tire forces.On these bases,energy efficient torque allocation method is developed to distribute the total driving torque and differential torque to each IWM,considering the motor energy consumption,the tire slip energy consumption,and the brake energy~?recovery.Simulation results of the proposed control strategy using the co-platform of Matlab/Simulink and CarSim way.

A novel reaching law approach of quasi-sliding-mode control for uncertain discrete-time systems

A novel discrete-time reaching law was proposed for uncertain discrete-time system,which contained process noise and measurement noise.The proposed method reserves all the advantages of discrete-time reaching law,which not only decreases the band width of sliding mode and strengthens the system robustness,but also improves the dynamic performance and stability capability of the system.Moreover,a discrete-time sliding mode control strategy based on Kalman filter method was designed,and Kalman filter was employed to eliminate the influence of system noise.Simulation results show that there is no chattering phenomenon in the output of controller and the state variables of controlled system,and the proposed algorithm is also feasible and has strong robustness to external disturbances.

Variable structure control with sliding mode prediction for discrete-time nonlinear systems

A new variable structure control algorithm based on sliding mode prediction for a class of discrete-time nonlinear systems is presented. By employing a special model to predict future sliding mode value, and combining feedback correction and receding horizon optimization methods which are extensively applied on predictive control strategy, a discrete-time variable structure control law is constructed. The closed-loop systems are proved to have robustness to uncertainties with unspecified boundaries. Numerical simulation and pendulum experiment results illustrate that the closed-loop systems possess desired performance, such as strong robustness, fast convergence and chattering elimination.

Robust Sliding-mode Filtering for a Class of Uncertain Nonlinear Discrete-time State-delayed Systems

This paper is concerned with the problem of robust sliding-mode filtering for a class of uncertain nonlinear discrete-time systems with time-delays. The nonlinearities are assumed to satisfy global Lipschitz conditions and parameter uncertainties are supposed to reside in a polytope. The resulting filter is of the Luenberger type with the discontinuous form. A sufficient condition with delay-dependency is proposed for existence of such a filter. And the desired filter can be found by solving a set of matrix inequalities. The resulting filter adapts for the systems whose noise input is real functional bounded and not be required to be energy bounded. A numerical example is given to illustrate the effectiveness of the proposed design method.

Robust Sliding Mode Control for Nonlinear Discrete-Time Delayed Systems Based on Neural Network

This paper presents a robust sliding mode controller for a class of unknown nonlinear discrete-time systems in the presence of fixed time delay. A neural-network approximation and the Lyapunov-Krasovskii functional theory into the sliding-mode technique is used and a neural-network based sliding mode control scheme is proposed. Because of the novality of Chebyshev Neural Networks (CNNs), that it requires much less computation time as compare to multi layer neural network (MLNN), is preferred to approximate the unknown system functions. By means of linear matrix inequalities, a sufficient condition is derived to ensure the asymptotic stability such that the sliding mode dynamics is restricted to the defined sliding surface. The proposed sliding mode control technique guarantees the system state trajectory to the designed sliding surface. Finally, simulation results illustrate the main characteristics and performance of the proposed approach.

Design of fuzzy sliding mode controller for SISO discrete-time systems

According to a class of nonlinear SISO discrete systems, the fiizzy sliding mode control problem is considered. Based on Takagi-Sugeno fuzzy model method, a fuzzy model is designed to describe the local dynamic performance of the given nonlinear systems. By using the sliding mode control approach, the global controller is constructed by integrating all the local state controllers and the global supervisory sliding mode controller. The tracking problem can be easily dealt with by taking advantage of the combined controller,and the robustness performance is improved finally. A simulation example is given to show the effectiveness and feasibility of the method proposed.

Robust sliding mode control for uncertain discrete time systems

A novel variable structure control (VSC) strategy with a dynamic disturbance compensator based on the reaching law for a class of uncertain discrete systems is presented. The robust stability to disturbance and the system dynamics in the vicinity of the switching plane are studied. A measure of the uncertain parameters and external disturbance is obtained through delaying every sampling time. Theoretical analysis and experimental simulation results demonstrate that the dynamic performance and robustness of the closed-loop system are improved effectively.

Discrete Sliding Mode Control of an Input-output System with Stochastic Disturbance

这份报纸论述输入产量的分离适应滑动模式控制非最小的阶段系统面对随机的骚乱。非最小的阶段系统能被一个操作员转变成一个最小的阶段系统。根据最小的阶段系统，控制器和我们设计了的适应算法保证系统的稳定性并且认为从滑动表面的吝啬平方的偏差被最小化。

Approximation law for discrete-time variable structure control systems

Two approximation laws of sliding mode for discrete-time variable structure control systems are proposed to overcome the limitations of the exponential approximation law and the variable rate approximation law. By applying the proposed approximation laws of sliding mode to discrete-time variable structure control systems, the stability of origin can be guaranteed, and the chattering along the switching surface caused by discrete-time variable structure control can be restrained effectively. In designing of approximation laws, the problem that the system control input is restricted is also considered, which is very important in practical systems. Finally a simulation example shows the effectiveness of the two approximation laws proposed.

DISCRETE VARIABLE STRUCTURE CONTROL OF LINEAR TIME-INVARIANT SYSTEMS WITH TIME DELAY

A discrete variable structure control(DVSC) method for the linear time invariant systems with time delay was presented. The continuous time delay systems are first transformed into the standard discrete form which contains no time delay by augmenting the state variables. Then the switching surface is determined by using the ideal quasi sliding mode. As it is difficult for the state trajectory to reach the switching surface exactly, the reaching condition in the form of approach law is used to design the controller. The deduced switching surface and controller contain not only the current step of state feedback but also some former steps of controls. Stability analysis with and without time delay information is also investigated in this paper. Numerical simulation was carried out to demonstrate the effectiveness and feasibility of the presented control method.

基于ESMDO的级联双模型永磁同步电机鲁棒控制

考虑永磁同步电机调速控制系统中传统电流环数学模型的耦合非线性,结合无模型控制的优势,提出了一种基于扩展滑模观测器(extended sliding mode disturbance observer,ESMDO)的级联双模型永磁同步电机鲁棒控制方法,有效解决了传统PI控制器的鲁棒性差、动态响应慢的问题。首先,在转速环利用传统永磁同步电机数学模型设计了引入自校正开关增益的离散滑模转速控制器,通过离散的ESMDO观测综合扰动项并进行补偿。然后,在考虑电机参数的不确定性和外部扰动的情况下,建立了电流环超局部模型,设计了基于离散的ESMDO的无模型无差拍电流预测控制器。最后,以PI控制为对比方法进行仿真分析,仿真结果表明了所提方法的可行性与有效性。

基于干扰观测器的升力式飞行器改进离散滑模控制研究

升力式飞行器具有飞行空域宽、速度变化范围大、机动性强等特点,是近年来国内外的研究热点。本文针对升力式飞行器模型大不确定及外界干扰强带来的控制难题,提出了一种基于干扰观测器的改进离散滑模变结构控制方法。首先,建立了俯仰通道的离散控制模型。其次,设计了一种基于干扰估计的改进离散滑模变结构控制律,并证明了其稳定性。再次,分析了参数选择对控制系统的影响,验证了控制律的有效性。最后,与传统的离散滑模变结构控制方法进行了比较。仿真结果表明,与传统的离散滑模控制方法相比,本文提出的控制律控制精度更高、鲁棒性更强、滑模面收敛速度更快及抖振更小,可有效提高升力式飞行器的飞行品质,实现复杂任务的稳定控制。

全超导托卡马克核聚变发电装置快控电源的干扰抑制离散积分滑模电流控制

全超导托卡马克核聚变发电装置(EAST)快控电源的首要性能指标是快速跟踪参考信号,以输出电流实现负载线圈的励磁,对等离子体的垂直位移进行反馈控制。EAST快控电源负载线圈受装置内部部件和真空内等离子体的影响,线圈感值会出现小范围内慢时变波动以及线圈上存在互感电动势干扰,传统比例-积分(PI)控制方法在电流跟踪控制过程中存在不足。为了实现干扰的抑制和应对负载波动,提出一种带干扰抑制的离散积分滑模控制方法,根据系统状态方程设计离散积分滑模控制器,结合滑模干扰观测器实现集总干扰的观测,对集总干扰进行前馈补偿控制。为了抑制抖振和加快收敛速度,设计一种新型平滑饱和函数和增益自适应观测器,根据观测电流误差和跟踪电流误差自适应调整观测器增益。对比传统PI控制,仿真和实验验证了所提控制方法具有更加优良的电流跟踪特性,在输出电流超调更小的情况下动态响应更快,能够有效地抑制负载侧扰动,具有良好的鲁棒性。

基于模糊算法的双三相PMSM无传感器控制

针对现有高速情况下双三相永磁同步电机无传感器控制精度低,增益值固定的问题,提出一种提高精度同时可变换增益值的基于模糊离散型超螺旋滑模观测器。首先,对双三相永磁同步电机的数学模型与电流方程进行分析;其次,结合电流方程与超螺旋算法构建超螺旋滑模观测器并利用反向差分离散法进行离散化,同时加入模糊控制得到变换增益值,解决了超螺旋滑模观测器受固定增益值限制无法兼具收敛速度快和观测误差小的问题;最后,在MATLAB环境下搭建了仿真模型对所提算法进行验证,仿真结果表明了新型观测器精度高的同时也能够改变增益值从而快速收敛。

基于离散积分滑模的四旋翼编队跟踪控制

针对四旋翼编队的轨迹跟踪问题,提出一种基于离散积分滑模的分布式编队控制器。首先,建立四旋翼的离散模型,并将其分为位置系统和姿态系统。其次,基于一致性理论和图论知识建立四旋翼编队的拓扑图,对位置系统采用离散积分滑模控制方法,对姿态系统采用指数趋近律的滑模控制方法,并进行编队一致性分析。最后,利用离散扩张观测器估计并补偿外界干扰和不可建模部分。仿真结果表明,所设计的分布式控制器能使四旋翼形成编队并跟踪给定轨迹。

A New Sliding Function for Discrete Predictive Sliding Mode Control of Time Delay Systems

The control of time delay systems is still an open area for research. This paper proposes an enhanced model predictive discrete-time sliding mode control with a new sliding function for a linear system with state delay. Firstly, a new sliding function including a present value and a past value of the state, called dynamic surface, is designed by means of linear matrix inequalities （LMIs）. Then, using this dynamic function and the rolling optimization method in the predictive control strategy, a discrete predictive sliding mode controller is synthesized. This new strategy is proposed to eliminate the undesirable effect of the delay term in the closed loop system. Also, the designed control strategy is more robust, and has a chattering reduction property and a faster convergence of the system s state. Finally, a numerical example is given to illustrate the effectiveness of the proposed control.

Robust Neural Control of Discrete Time Uncertain Nonlinear Systems Using Sliding Mode Backpropagation Training Algorithm

This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the first step, a direct neural model(DNM)is used to learn the behavior of the system, then, an inverse neural model(INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation(BP) algorithm. In this work, the sliding mode-backpropagation(SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best configuration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the effectiveness of the proposed control strategy.