An adaptive hierarchical control approach of vehicle handling stability improvement based on Steer-by-Wire Systems

This paper proposes a novel adaptive hierarchical control approach for Steer-by-Wire (SbW) vehicles to improve the handling stability. The high-level stability control scheme contains a variable steering ratio (VSR) strategy based on the adaptive-network-based fuzzy inference system (ANFIS) and an active front steering (AFS) controller designed with the integral sliding mode method by tracking the expected yaw rate, in which the desired front wheel angle is generated to enhance the cornering stability performance. Besides, an adaptive tracking controller (ATC) for the SbW system is designed by using the adaptive sliding mode control method to achieve desired steering performance in the lower level. The proposed adaptive control strategy is validated with different driving circles from ISO standards in simulation tests and hardware-in-the-loop (HiL) experiments. The results demonstrate that the designed control approach improve the vehicle handling stability significantly, even in some extreme driving conditions.     

Design and experimental research of observer-based adaptive type-2 fuzzy steering control for automated vehicles with prescribed performance

Steer-by-Wire (SbW) system is a significant electromechanical subsystem of automated vehicles. This paper proposes an observer-based type-2 fuzzy control method for the SbW system with uncertain nonlinearity, unknown modeling parameters, and unavailable state. First, an interval type-2 fuzzy logic system (IT2 FLS) and an IT2 FLS-based state observer are constructed to estimate the uncertain nonlinearity and unavailable state of SbW systems. Then, a prescribed performance control (PPC) method is proposed to achieve the prescribed tracking performance of SbW systems. Much importantly, a modified performance function is incorporated in this control method, such that the prescribed tracking performance can be guaranteed within a finite time regardless of the initial state. Finally, simulation and vehicle experiments are given to verify the effectiveness and superiority of the proposed methods.     

电液伺服系统的自适应滑模跟踪控制研究

针对电液伺服系统的跟踪控制问题,在系统模型不确定性参数的界未知的情况下,提出一种自适应滑模控制方案。该方案的主要思想是用滑模方法抑制系统中的外干扰力扰动,对系统不确定性参数进行自适应估计,用估计值来补偿不确定性参数的变化。对于系统全局稳定性,采用李雅普诺夫稳定性理论给出了严格的证明。仿真结果表明了该方案具有良好的跟踪性能和鲁棒性。     

Passivity-based fractional-order integral sliding-mode control design for uncertain fractional-order nonlinear systems

This paper concerns with the problem of designing a passivity-based fractional-order (FO) integral sliding mode controller for uncertain FO nonlinear systems. Utilizing the FO calculus, it is showed that the state trajectories of the closed-loop system reach the FO switching manifold in finite time. The control law ensures the asymptotical stability on the sliding surface. A parameter adjustment scheme for FO integral sliding surface is proposed by using the linear matrix inequality (LMI) approach. The proposed controller can be applied to different systems such as chaotic systems. Finally, simulation results are provided to show the effectiveness of the proposed method controlling chaos in FO Chua circuit and FO Van-der-Pol oscillator.     

Intelligent voltage control strategy for three-phase UPS inverters with output LC filter

This paper presents a supervisory fuzzy neural network control (SFNNC) method for a three-phase inverter of uninterruptible power supplies (UPSs). The proposed voltage controller is comprised of a fuzzy neural network control (FNNC) term and a supervisory control term. The FNNC term is deliberately employed to estimate the uncertain terms, and the supervisory control term is designed based on the sliding mode technique to stabilise the system dynamic errors. To improve the learning capability, the FNNC term incorporates an online parameter training methodology, using the gradient descent method and Lyapunov stability theory. Besides, a linear load current observer that estimates the load currents is used to exclude the load current sensors. The proposed SFNN controller and the observer are robust to the filter inductance variations, and their stability analyses are described in detail. The experimental results obtained on a prototype UPS test bed with a TMS320F28335 DSP are presented to validate the feasibility of the proposed scheme. Verification results demonstrate that the proposed control strategy can achieve smaller steady-state error and lower total harmonic distortion when subjected to nonlinear or unbalanced loads compared to the conventional sliding mode control method.     

拒绝服务攻击下的弹性事件触发负荷频率控制

针对互联电力系统负荷频率控制通信网络带宽受限及易遭受恶意网络攻击的问题,文中研究了拒绝服务攻击下弹性事件触发机制和负荷频率控制器的联合设计问题。在拒绝服务攻击参数已知的情况下,提出了一种既能缓解通信带宽压力,又可同时消除拒绝服务攻击影响的弹性事件触发机制。文中构建了一种基于弹性事件触发机制及拒绝服务攻击的负荷频率控制时滞切换系统模型。应用分段李亚普洛夫函数对切换系统稳定性进行了分析,并进行了触发参数和控制器的联合设计。最后,通过一个两区域互联电力系统仿真验证了所提方法的有效性。     

Congestion control in cognitive radio networks with event-triggered sliding mode

The increasing demand for assorted services from extensive wireline and wireless users place a significant burden on the band-limited radio spectrum. To settle the demand, smart reuse and management of the spectrum are necessary. In this contribution, Cognitive Radio being an emerging technology provides a platform to share the same spectrum between Primary Users (licensed) and Secondary Users (unlicensed) for significant improvement in the spectrum efficiency. The coexistence of users for data communications in a band-limited channel calls for a robust congestion controller to maximize throughput. This work presents the design of a robust nonlinear congestion controller based on event-triggered sliding mode for Cognitive Radio Networks. The goal is to maintain desired Quality of Service of the network with optimum bandwidth and resource utilization. The controller has been designed on the notions of sliding mode, better known for its inherent robustness and disturbance rejection capabilities. An event-triggering scheme has been incorporated with the sliding mode for optimum utilization of the available resources. The signal is sampled and control is updated only when a predefined condition gets violated while ensuring acceptable closed-loop behavior of the system. The efficiency of the proposed controllers has been validated using simulations.     

采用滑模观测器的机载激光通信视轴精度控制

为了提高机载激光通信系统在机体振动和机械摩擦等扰动下的视轴对准精度,提出了一种基于滑模观测器的反步滑模控制方法。首先建立了机载激光通信系统的数学模型,然后通过设计的滑模观测器对扰动值进行估计,同时针对指令转换模块、激光通信模块和电机模块逐步设计了反步滑模控制律,实现对机载激光通信系统视轴的高精度控制。实验结果表明:提出的方法与分数阶PID控制方法相比突出了更优的快速性和准确性,响应时间仅为0.4 s,最大空间对准误差仅为0.3 m,设计的滑模观测器能够快速、准确地估计出扰动值,响应时间仅为0.3 s,最大估计误差分别仅为0.1 m/s、0.06 (°)/s2 和0.07 A/s,大幅提高了机载激光通信系统中视轴的对准精度。     

Adaptive sliding controller with self-tuning fuzzy compensation for vehicle suspension control

Since the hydraulic actuating suspension system has nonlinear and time-varying behavior, it is difficult to establish an accurate dynamic model for a model-based sliding mode control design. Here, a novel model-free adaptive sliding controller is proposed to suppress the position oscillation of the sprung mass in response to road surface variation. This control strategy employs the functional approximation technique to establish the unknown function for releasing the model-based requirement. In addition, a fuzzy scheme with online learning ability is introduced to compensate the functional approximation error for improving the control performance and reducing the implementation difficulty. The important advantages of this approach are to achieve the sliding mode controller design without the system dynamic model requirement and release the trial-and-error work of selecting approximation function. The update laws for the coefficients of the Fourier series functions and the fuzzy tuning parameters are derived from a Lyapunov function to guarantee the control system stability. The experimental results show that the proposed control scheme effectively suppresses the oscillation amplitude of the vehicle sprung mass corresponding to the road surface variation and external uncertainties, and the control performance is better than that of a traditional model-based sliding mode controller.     

Robust fuzzy neural network sliding mode control scheme for IPMSM drives

This article proposes a robust fuzzy neural network sliding mode control (FNNSMC) law for interior permanent magnet synchronous motor (IPMSM) drives. The proposed control strategy not only guarantees accurate and fast command speed tracking but also it ensures the robustness to system uncertainties and sudden speed and load changes. The proposed speed controller encompasses three control terms: a decoupling control term which compensates for nonlinear coupling factors using nominal parameters, a fuzzy neural network (FNN) control term which approximates the ideal control components and a sliding mode control (SMC) term which is proposed to compensate for the errors of that approximation. Next, an online FNN training methodology, which is developed using the Lyapunov stability theorem and the gradient descent method, is proposed to enhance the learning capability of the FNN. Moreover, the maximum torque per ampere (MTPA) control is incorporated to maximise the torque generation in the constant torque region and increase the efficiency of the IPMSM drives. To verify the effectiveness of the proposed robust FNNSMC, simulations and experiments are performed by using MATLAB/Simulink platform and a TI TMS320F28335 DSP on a prototype IPMSM drive setup, respectively. Finally, the simulated and experimental results indicate that the proposed design scheme can achieve much better control performances (e.g. more rapid transient response and smaller steady-state error) when compared to the conventional SMC method, especially in the case that there exist system uncertainties.     

Adaptive Iterative Learning Control for a Class of Uncertain Nonlinear Systems with Second-Order Sliding Mode Technique

This paper addresses the problem of robust adaptive iterative learning control for a chain of uncertain integral nonlinear systems, whose aim is to stabilize the tracking error of the system and improve convergence speed in the presence of uncertainties. In response to unknown bounded disturbances, a continuous second-order sliding mode adaptive iterative learning control scheme is proposed, in which an integral term is to attenuate the effects of the disturbances and achieve fast convergence performance. By designing a suitable controller and composite energy function, it is proved that the tracking error along iterative learning horizon will converge to a small neighborhood of zero. Numerical examples are provided to validate the efficacy of the proposed method.     

Robust Adaptive Sliding Mode Control for Nonlinear Uncertain Neutral Markovian Jump Systems

This paper investigates the robust adaptive sliding mode control problem for a class of nonlinear uncertain neutral Markovian jump systems. In this study, the system state is unmeasurable and the upper norm bounds of the nonlinear functions are unavailable. An observer-based adaptive sliding mode controller is synthesized to render the resulting error system stochastically stable with a prescribed disturbance attenuation level. Finally, a numerical example is exploited to demonstrate the effectiveness of the control scheme.     

不确定分数阶多驱动一响应混沌系统同步

针对一类新的多驱动一响应混沌系统同步方式,基于分数阶系统稳定性理论和Lyapunov稳定性理论,运用追踪控制和滑模自适应控制方法设计了同步控制律和参数自适应律.对象模型考虑了不确定因素的影响,首先选取一类稳定的分数阶滑模曲面,然后提出了一种鲁棒同步方案.最后数值仿真验证了方案的正确性和有效性.     

Sliding Mode Control of Uncertain Stochastic Hybrid Delay Systems with Average Dwell Time

This paper investigates the problem of sliding mode control (SMC) for uncertain switched stochastic system with time-varying delay. The system under consideration is concerned with the stochastic dynamics and deterministic switching laws. An integral sliding surface is constructed and the stable sliding mode is derived. A sufficient condition for mean-square exponential stability of the sliding mode is developed under a class of switching laws based on the average dwell time method. Variable structure controllers are designed to guarantee the existence of the sliding mode from the initial time. An illustrative example is used to demonstrate the effectiveness of the proposed scheme.     

D2D/蜂窝通信模式切换与联合功率控制方案

设备直连（Device-to-Device, D2D）通信技术通过复用蜂窝系统的频谱资源提高频谱利用率,但D2D的引入会给蜂窝系统带来干扰。如何合理地选择D2D/蜂窝通信模式并进行功率优化控制,成为减小D2D和蜂窝系统间干扰、提升网络性能的关键。本文考虑D2D用户复用蜂窝上行链路场景,提出了一种基于距离和联合功率控制的通信模式选择方案。在该方案中,D2D用户和蜂窝用户与基站距离的比值决定了D2D用户是否采用Underlay模式进行通信,进而在约束蜂窝用户和D2D用户发射功率的条件下实现D2D链路和蜂窝链路的联合功率控制,最终推导出能够最大化系统总吞吐量的最优用户功率分配方案。根据仿真结果,本文提出的联合功率控制方案能够在降低系统间干扰的同时有效提高D2D和蜂窝系统的总吞吐量,进而提高了系统的性能。      

Precise friction control for the nonlinear friction system using the friction state observer and sliding mode control with recurrent fuzzy neural networks

This paper deals with a tracking control problem of a mechanical servo system with nonlinear dynamic friction which contains a directly immeasurable friction state variable and an uncertainty caused by incomplete parameter modeling and its variations. In order to provide an efficient solution to these control problems, we propose a composite control scheme, which consists of a friction state observer, a RFNN approximator and an approximation error compensator with sliding mode control. In first, a sliding mode controller and friction state observer are designed to estimate the unknown internal state of the LuGre friction model. Next, a RFNN is developed to approximate an unknown lumped friction uncertainty. Finally, an adaptive error compensator is designed to compensate an approximation error of RFNN. Some simulations and experiments on the mechanical servo system composed of ball-screw and DC servo motor are executed. Their results give a satisfactory performance of the proposed control scheme.     

Output tracking of uncertain fractional-order nonlinear systems via a novel fractional-order sliding mode approach

In this paper, a board class of uncertain fractional-order nonlinear systems is considered. A novel fractional-order sliding mode controller for output tracking of a time-varying reference signal is designed which can conquer the uncertainties and guarantees the asymptotic convergence of the system output toward the desired time-varying reference signal. For this purpose, an appropriate sliding surface is designed where maintaining the system’s states on this surface leads to asymptotic vanishing of error signal. Moreover, by tacking the fractional derivative of order α from the sliding surface, the convergence of system’s trajectories into the sliding surface in a finite time is proven. Finally, in order to verify the theoretical results, the proposed method is applied to a fractional-order gyroscope model and computer simulations show the efficiency of the proposed method in output tracking.     

Quantized Observer-Based Sliding Mode Control for Networked Control Systems Via the Time-Delay Approach

This paper investigates the sliding mode control problem for networked control systems, which are influenced by the non-ideal network environment, such as network-induced delays, packet dropouts and quantization errors. The states of the system are assumed to be unavailable, and an observer is designed to estimate the state of the system, based on which a sliding mode controller is given to guarantee the closed-loop system to be stable. Furthermore, it is shown that the proposed control scheme ensures the reachability of the sliding surfaces in both the state estimate space and the estimation error space. Finally, a numerical example is given to illustrated the effectiveness of the proposed methodology.     

Leader‐Following Formation Control of Multiple Robots with Uncertainties through Sliding Mode and Nonlinear Disturbance Observer

This paper presents a control scheme for the leader‐following formation of multiple robots. The control scheme combines the sliding mode control (SMC) method with the nonlinear disturbance observer (NDOB) technique. The formation dynamics suffer from uncertainties because the individual robots are uncertain. Concerning such formation uncertainties, the leader‐following formation dynamics are modeled. Assuming that the formation uncertainties have an unknown boundary, an NDOB‐based observer was designed to estimate the formation uncertainties. A sliding surface containing the observer outputs has been defined. Regarding the sliding surface, an SMC‐based controller was investigated to form uncertain robots. A sufficient condition in the sense of the Lyapunov theory was proven such that the formation system is asymptotically stable. Herein, some comparison results between the sole SMC method and the second‐order SMC method are presented to demonstrate the effectiveness and feasibility of the control scheme for multiple robots in the presence of uncertainties.