Journal of Intelligent & Fuzzy Systems - Volume 29, issue 6

Authors: Yu, Yuan bin | Liu, Xiugang | Min, Haitao | Sun, Huanli | Xu, Lichao

Article Type: Research Article

Abstract: A hybrid energy storage system (HESS) composed of a battery and super-capacitor (SC) can make full use of advantages in energy and power density, which can further improve the performance of hybrid electric vehicles (HEV). Most studies have been limited to configuration and control to reduce the burden and prolong the life cycle of the battery, seldom focusing on the redesign of energy management strategies (EMS) for HEVs when passing from battery-only energy storage to HESS. In this paper, the equivalent fuel consumption during parallel-charging of a semi-active HESS in a series-parallel HEV under rule-based EMS was deduced, and a …fuzzy-logic based (FLB) CS for the HESS was established using the state of energy (SOE) of the battery and SC as inputs. This allows the requirement of energy balance for HESS to be clearly expressed. Furthermore, the regulated EMS for HEV, which could dynamically manage the high efficiency of the engine and maintain the real-time charging/discharging capability of HESS, was proposed and verified under hardware in a loop test (HIL). Quantitative comparison of results between HESS and battery-only indicated that velocity-based SC’SOE-adjustable EMS presented in this paper could make better use of SC in filtering than SOE-constant EMS, and improve the fuel economy of HEVs from 22.76 l/100 km (battery-only) to 21.18 l/100 km. In order to emphasize the advantages of management, the electric energy usage/loss and efficiency under city driving-cycle were also presented. Show more

Keywords: Hybrid electric vehicle (HEV), hybrid energy storage system (HESS), control strategy (EMS), fuzzy logic, state of energy (SOE)

DOI: 10.3233/IFS-151960

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2575-2584, 2015

Authors: Xia, Guoqing | Pang, Chengcheng | Xue, Jingjing

Article Type: Research Article

Abstract: This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural Network (DRFNN) with feedback loops is employed to approximate the unknown portion of the controller, which can greatly reduce the number of neural network inputs. A fuzzy logic dead-zone compensator is designed to cope with the unknown dead-zone characteristics of actuators. The upper bounds of the approximation errors …and disturbances of the network, which are often used in existing works, are not necessary in this paper due to the presentation of a special robust compensator. Stability analysis is conducted according to the Lyapunov theorem, and the tracking error is proved to converge to zero. Simulation results indicate that the proposed controller demonstrates good performance. Show more

Keywords: Dynamic recurrent fuzzy neural network, underwater vehicle, dynamic positioning, dead-zone, fuzzy compensator

DOI: 10.3233/IFS-151961

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2585-2595, 2015

Authors: Chang, En-Chih | Xu, Ziang | Su, Zhiyi | Wu, Rong-Ching

Article Type: Research Article

Abstract: In this paper, a fuzzy grey predictor (GP) compensated time-varying variable structure controller (TVVSC) is developed and applied to solar inverters. TVVSC can shorten the reaching phase and ensure the sliding mode occurrence from an arbitrary initial state. However, while loading is a severe nonlinear condition, the TVVSC may suffer from chattering and steady-state error problems, thus deteriorating solar inverter performance. A GP is thus devoted to alleviate the chattering when the system uncertainty bounds are overestimated, and to reduce the steady-state error when the system uncertainty bounds are underestimated. However, the GP with a fixed forecasting value causes long …rise time or large overshoot of the system response. Thus, fuzzy logic (FL) is applied to obtain flexible forecasting values to improve the system performance. With the proposed controller, the robustness of the solar inverter system can be enhanced, and a high-quality solar inverter sinusoidal output voltage with low voltage harmonics and fast dynamic response can be obtained, even under nonlinear loading. The theoretical analysis, design procedure, computer simulations, and digital signal processing (DSP)-based experimental implementation for solar inverters are presented to verify the efficacy of the proposed controller. Show more

Keywords: Grey predictor (GP), time-varying variable structure controller (TVVSC), fuzzy logic (FL), solar inverter, voltage harmonics

DOI: 10.3233/IFS-151962

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2597-2602, 2015

Authors: Wang, Quanhui | Huang, Jianjun | Huang, Jingxiong

Article Type: Research Article

Abstract: A fuzzy logic-based multi-factor aided multiple-model filter (FLMAMMF) for General aviation (GA) maneuvering target tracking (MTT) is presented. The target category and meteorological information are introduced into the interacting multiple model (IMM) filter to perform GA target tracking. Fuzzy logic inference is employed in the proposed algorithm to reflect the complicated relationship between these two factors and the transition probability matrix (TPM). Both the number of models in model set and the transition probabilities between models are adjusted through fuzzy inference. Simulation results show that the proposed method is efficient and effective.

Keywords: General aviation target tracking, multi-factor Aided, IMM algorithm, model transition probability matrix, fuzzy inference

DOI: 10.3233/IFS-151963

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2603-2609, 2015

Authors: Wen, Chen | Hui, Zhao | Tao, Li | Yuling, Liu

Article Type: Research Article

Abstract: Intelligent traffic signal control (TSC) system is important for the alleviation of traffic congestion. Usually, most of the researches about TSC focused on single intersection based on type-1 fuzzy set. Compared with type-1 fuzzy logic controller (FLC), type-2 FLC can deal with more uncertainties in the road traffic control system. Therefore, a type-2 FLC optimized by NSGAII (T2-NSGAII) is designed for TSC in a complex road network, in which the intersection’s traffic signal time is dynamically adjusted by its own and adjacent intersections’ traffic volumes to reduce global delay time and traffic congestion. In T2-NSGAII, the expert rule set and …the parameters of the fuzzy membership functions are simultaneously optimized by NSGAII to achieve less time delay and traffic congestion. In the simulations of a six-intersection traffic network with different vehicular arrival rates, it is demonstrated that T2-NSGAII has better performance compared with vehicle actuated controller based on fixed-time control (FTC), type-1 FLC, type-2 FLC and isolatedly optimized Type-2 FLC and the total delay time could be reduced by 76.3% , 65.1% , 58.3% and 35.4% respectively. Show more

Keywords: Type-2 logical fuzzy, traffic signal control, NSGAII, phase sequence, multi objects optimization

DOI: 10.3233/IFS-151964

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2611-2618, 2015

Authors: Wu, Hua | Wu, Yan-Xiong | Meng, Ling-Zhi | Liu, Chang-An | Yang, Guo-Tian

Article Type: Research Article

Abstract: This paper describes a hybrid anti-swing control scheme of an inspection robot in tunnels for power transmission cables. The hybrid control scheme consists of velocity switching and fuzzy logic control, so that the robot can be operated smoothly without causing excessive swings in acceleration or deceleration motion. In order to ensure control system robustness for greatest movement in the tunnel, fuzzy logic control is used for horizontal anti-swing control. Velocity switching is adopted for incline anti-swing control, in order to obtain sufficient damping as well as a fast response. The stability of the hybrid system has been analyzed. The experimental …results present the practicability and effectiveness of the proposed method. Show more

Keywords: Tunnel inspection robot, anti-swing, hybrid control, fuzzy logic, velocity switching

DOI: 10.3233/IFS-151965

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2619-2627, 2015

Authors: Hu, Shushan | Liu, Feng | Tang, Cunchen | Wang, Xiaojun | Zhou, Huaibei

Article Type: Research Article

Abstract: Buildings were responsible for over 30% of total Chinese energy consumption in 2010. With a wild range of climate conditions and a separate air conditioning structure in campus buildings, it is significant but difficult to assess the energy performance of campus buildings in China. This paper proposes a novel mechanism to assess energy performance of campus buildings, using a fuzzy analytic network process (FANP). Six criteria are used as key performance indicators based on climate conditions in China and the air conditioning device deployment structure in campus buildings: 1) building envelope; 2) renewable energy; 3) illumination; 4) thermal comfort; 5) …window and door; and 6) occupation status. A simulation is presented to illustrate the effectiveness of the proposed approach, analyzing three different rooms in the International School of Software, at Wuhan University. Assessment results are discussed in terms of optimizing future energy performance of campus buildings. Show more

Keywords: Fuzzy, analytic network process, building energy performance, performance indicator, Chinese campus building

DOI: 10.3233/IFS-151966

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2629-2638, 2015

Authors: Zhang, Nannan | Zhou, Kefa

Article Type: Research Article

Abstract: Knowledge-and data-driven approaches are two major methods used to integrate various evidential maps for mineral prospectivity mapping (MPM). Geological maps, geochemical samples and data from known gold deposits were collected in the western Junggar area, Xinjiang Province. The geological and a spatial database for geological and mineral occurrences were constructed for the studied region. A weights-of-evidence model and a fuzzy logic model were employed for MPM, and the results were compared. Results indicate that favorable sedimentary rocks, fault density, fault distance and concentration of Au were the primary factors affecting Au mineralization. Arsenic (AS), Stibium (Sb), fault direction, quartz veins …and intrusive rocks were secondary factors affecting Au mineralization. Conditional independence exerted a major influence on the weights-of-evidence model. However, posterior probability would be very high if the conditional independence was disregarded, which impaired results. Combining the quantification results provided by weights-of-evidence and the fuzzy membership values determined by expert knowledge, the mineral prospectivity mapping according to the fuzzy logic method was proved to be valid. For the study area, which had a large number of deposits, data-driven approaches for MPM are generally considered to be appropriate. However, if sufficient data are not collected, the knowledge-driven approaches, for example, the fuzzy logic method used in the present study, usually achieves a better result. Show more

Keywords: Mineral prospectivity mapping, weights-of-evidence, fuzzy logic

DOI: 10.3233/IFS-151967

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2639-2651, 2015

Authors: Hu, Chunchun | Zhao, Qiansheng | Luo, Nianxue

Article Type: Research Article

Abstract: Spatio-temporal trajectory clustering can extract behavior and moving pattern of object with the change of time and space by exploring similar trajectories. Most of trajectory clustering method can be achieved by expanding the traditional clustering algorithms. Considering the limitations of fitness and optimization of most clustering algorithms, especially for spatio-temporal trajectory data sets, this paper proposes a trajectory fuzzy clustering method based on multi-objective mixed function, which can simultaneously optimize multiple objective function such as FCM and XB when perform particle swarm optimization method. And we also propose a new coarse-grained DTW based on interpolation point for generalization trajectory data …and improvement the performance of measure the similarity between trajectories. The experimental results, which implement on the synthetized trajectory data and real vehicle history data by employing the new clustering algorithm, and clustering validity evaluation and hot spots analysis show that the proposed method, which combines different objective functions with different optimization criteria and particle swarm algorithm, can effectively solve the clustering problem and produce better clustering results than the traditional clustering method. Show more

Keywords: Trajectory clustering, multi-objective function, PSO, FCM, hot spot

DOI: 10.3233/IFS-151968

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2653-2660, 2015

Authors: Zhou, Tao | Zhou, Yulin

Article Type: Research Article

Abstract: Urban regeneration decision-making is a complicated system, which requires that stakeholder interests balance in aspects of the economy, society and environment. It is necessary to identify the key factors affecting urban regeneration and then construct an urban regeneration decision-making evaluation system to provide a basis for objective and comprehensive judgment for urban regeneration decision-making. Through constructing a fuzzy comprehensive evaluation model based on the entropy weight method, this paper attempts to provide a scientific evaluation method for the suitability of urban regeneration. An urban regeneration scheduling method by sorting the appropriate degree of the update of different areas in the …large region, is proposed to achieve urban regeneration implementation in the sequence of time and space optimization. Show more

Keywords: Urban regeneration decision-making, stakeholder, fuzzy comprehensive evaluation, entropy weight method

DOI: 10.3233/IFS-151969

Citation: Journal of Intelligent & Fuzzy Systems, vol. 29, no. 6, pp. 2661-2668, 2015