Showing papers by "Quoc Hung Nguyen published in 2017"
TL;DR: In this paper, a controller for active suspension system of train cars in the case that the sprung mass and model error are uncertainty parameters is presented. But this controller is not suitable for the case where the model error is unknown.
Abstract: This paper focuses on building a controller for active suspension system of train cars in the case that the sprung mass and model error are uncertainty parameters. The sprung mass is always varied ...
29 citations
01 Apr 2017
TL;DR: This paper forms and proves CDS-related necessary conditions for an approximation expressing an initial data space (IDS) convergent, and proposes a fuzzy system typed ANFIS associated with two solutions for establishing the CDS from the IDS, which focus on preventing, seeking and exterminating critical data samples in the C DS.
Abstract: Display Omitted Reflecting the relation between the convergent capability of ANFIS and especial features of the created cluster data space.Providing solutions for improving the convergent ability of ANFIS.Proposing an improved-configuration for ANFIS.Proposing a novel algorithm for building ANFIS.Establishing smart damper models based on ANFIS. For approximation of unknown mapping f: XY expressing a given database via an adaptive Neuro-Fuzzy inference system (ANFIS), ANFISs convergent capability is quite sensitive to the data features. In order to deal with this, this paper focus on ameliorating quality of cluster data space (CDS) used to establish the ANFIS. Firstly, we formulate and prove CDS-related necessary conditions for an approximation expressing an initial data space (IDS) convergent. Based on this theory basis, we propose a fuzzy system typed ANFIS associated with two solutions for establishing the CDS from the IDS, which focus on preventing, seeking and exterminating critical data samples in the CDS. In order to deploy these, we also present an improved structure of ANFIS. These aspects are described via a novel offline identification algorithm named ANFIS-JS for building ANFIS in a jointed input-output data space (JDS) deriving from the IDS. The results obtained via several surveys, including identifying smart dampers, magnetorheological damper (MRD) and electrorheological damper (ERD), show that the convergent stability and response accuracy are the main advantages of the ANFIS-JS.
18 citations
01 Jul 2017
TL;DR: An optimal fuzzy disturbance observer-enhanced sliding mode controller for magneto-rheological damper-based semi-active train-car suspensions subjected uncertainty and disturbance whose variability rate may be high but bounded is proposed.
Abstract: An optimal fuzzy disturbance observer-enhanced sliding mode controller (FDO-SMC) for magneto-rheological damper (MRD)-based semi-active train-car suspensions (MRD-TSs) subjected uncertainty and disturbance (UAD) whose variability rate may be high but bounded is proposed. The two main parts of the FDO-SMC are an adaptive sliding mode controller (aSMC) and an optimal fuzzy disturbance observer (oFDO). First, initial structures of the sliding mode controller (SMC) and disturbance observer (DO) are built. Adaptive update laws for the SMC and DO are then set up synchronously via Lyapunov stability analysis with a used parameter constraint mechanism. An optimal fuzzy system (oFS) is designed to implement fully the constraint mechanism so as to guarantee for the stable converging to the desired state even if the UAD variability rate increases in a given range. As a result, the aSMC and the oFDO are created from the SMC and DO. The compared simulation surveys reflected that the positive competence to stamp out and isolate vibration with the lower consumed power is the main advantage of the proposed controller.
1 citations