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.     

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.     

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.     

一种基于布谷鸟算法的质子交换膜燃料电池湿度辨识方法

为了提高燃料电池内部交换膜湿度的测量精度,本文基于区间二型模糊逻辑计算理论,结合Cuckoo Search 算法,建立了一种辨识方法,对其湿度特性进行非线性拟合逼近。通过对非线性拟合结果进行验证,所设计的辨识方法在对燃料电池进行湿度拟合的过程较为精确。计算模型的输出结果较为稳定,测试稳定性较高,此类测量技术能够广泛应用于各类离线测量系统中。     

Fuzzy logic–based distributed clustering protocol to improve energy efficiency and stability of wireless smart sensor networks for farmland monitoring systems

Wireless smart sensor networks (WSSNs) are emerging as the physical backbone of the internet of things (IoT) technology. On the basis of the IoT platform, web‐based systems and services are been developing such as e‐surveillance, industrial‐IoT, and precision agriculture. For farmland monitoring systems, WSSNs need to be scalable in terms of coverage area. Sensor nodes are energy‐constrained devices, and hence, many energy‐efficient clustering protocols are developed in the literature. But these methods overload the cluster leaders (CLs) with cluster computation and data communication costs. An improper CL selection may lead to the early death of such nodes and hence does not prolong the network lifetime stability. We propose a fuzzy logic (FL)–based distributed clustering protocol to enhance the energy efficiency of WSSN while maximizing the coverage area. The load of CLs is shared by originators and super‐CLs (SCLs) selected in the network. The wireless link and received signal strength (RSS) are greatly affected by environmental conditions and thus cannot be considered as ideal network parameters. We use FL systems to tackle the uncertainty of such network parameters. The proposed protocol is simulated for different scalable WSSNs. The results indicate that the proposed protocol provides better lifetime stability than the recent conventional protocols. The functionalities of the protocol are proposed considering the recent wireless standards. Hence, the proposed protocol can be suitably implemented for farmland monitoring systems.     

Observer-based Fault Detection and Isolation for 2D State-space Models

In this paper, the fault detection and isolation problems for two-dimensional (2D) state-space models are investigated, both when no disturbances affect the system and when they actually do. Basing on some old results about dead-beat observers [Bisiacco, M. (1986) IEEE Transactions on Automatic Control, AC-31, 676–680] and on some recent results about dead-beat unknown input observers (UIOs) (for 2D systems affected by disturbances) [Bisiacco, M. & Valcher, M. E. (2004) International Journal of Control 77(9), 861–876], we develop a complete theory of dead-beat (possibly unknown input) observer-based fault detectors and isolators (FDIs). Necessary and sufficient conditions for the existence of a dead-beat observer-based FDI or for the existence of a dead-beat UIO-based FDI are derived, and constructive procedures for obtaining such FDIs are described in detail. Published online: April 2006