Browsing by Author "Perng, Jau-Woei"

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Absolute Stability Analysis in Uncertain Static Fuzzy Control Systems with the Parametric Robust Popov Criterion
(2008)
Wu, Bing-Fei
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Ma, Li-Shan
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Perng, Jau-Woei
;
Chin, Hung-I
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電控工程研究所
This study analyzes the absolute stability in static fuzzy logic control systems with certain and uncertain parameters. For certain static fuzzy control systems, the absolute stability can be analyzed with Popov criterion. The uncertain parameters for absolute stability analysis include the reference input, actuator gain and interval linear plant. The parametric robust Popov criterion based on Lur'e systems is applied to stability analysis respect to uncertain parameters. In our work, the parametric robust Popov criterion is applied to analyze absolute stability in static fuzzy logic control systems first time. This study can provide a valuable reference in designing fuzzy control systems. Finally, numerical simulations are provided to verify the analytical results.
Adaptive synchronization for unknown chaotic systems with fuzzy-neural network observer
(2006)
Wu, Bing-Fei
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Ma, Li-Shan
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Perng, Jau-Woei
;
Chin, Hung-I
;
Lee, Tsu-Tian
This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In proposed approach, the receiver states can be reconstructed from one transmitted state using AFNO design. The adaptive fuzzy-niural network (INN) in AFNO is adopted to model the nonlinear term in the transmitter. Additionally, an observer is designed to estimate the other states of the master. Synchronization is achieved when all states are observed. The proposed scheme can adaptively estimated the transmitter states using AFNO, even if the transmitter changes into another chaotic system. Simulation results confirm that the proposed AFNO design is valid.
Exponentially stabilizing output tracking of fully autonomous passenger cars with an observer
(2006)
Kumarawadu, Sisil
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Perng, Jau-Woei
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Lee, Tsu-Tian
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電控工程研究所
;
Institute of Electrical and Control Engineering
This paper, inspired by resolved acceleration control techniques popular in robotics, presents an automated vehicle control algorithm for combined longitudinal and lateral motion control of highway vehicles with special emphasis on passenger cars. Key design features are: 1) inherent coupling effects will be taken into account as a result of combining of two control issues, viz., lateral and longitudinal control 2) rather ad hoc numerical approximations of lateral velocity will be avoided via a combined controller-observer design 3) closed-loop exponential stability issues of the overall system will be established. The algorithm is validated via formative mathematical analyzes and numerical simulations.
GPS navigation based autonomous driving system design for intelligent vehicles
(2007)
Wu, Bing-Fei
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Lee, Tsu-Tian
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Chang, Hsin-Han
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Jiang, Jhong-Jie
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Lien, Cheng-Nan
The main objective of this paper is to design and implement a real-time autonomous navigation system for intelligent vehicles by integrating a real-time kinematics differential global position system (RTK-DGPS) and a laser range finder. Firstly, a fuzzy logic algorithm for target position tracking is proposed to achieve the human driving concept. In addition, an actuator is equipped in the experimental vehicle TAIWAN iTS-1 so that the steering wheel can be controlled to let the vehicle follows a desired trajectory in digital maps. A laser range finder is used to detect obstacles in front of the vehicle for warning announcement and collision avoidance. A human machine interface is also built up to provide information from sensors. The performance and accuracy of the proposed system is verified by real-time experimental results.
Integrated headway adaptation with collision avoidance system for intelligent vehicles
(2007)
Chiang, Hsin-Han
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Wu, Bing-Fei
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Lee, Tsu-Tian
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Perng, Jau-Woei
;
電控工程研究所
In this paper, an integrated headway adaptation (HA) with collision avoidance (CA) system is proposed to be associated with a human factor aspect for driving assistance. The maneuver in the CA strategy is developed based on the idea that warning or potential crash information generally can be graded such that the driver need not react to a discrete on/off warning. The control law for the HA strategy is designed by using a modified sliding surface to achieve driving comfort requirement and also stability in car-following. To simulate the speed controlling of human drivers, the throttle and brake actuation is directed by the regulation control which is designed based on a human reasoning approach. A description of an experimental vehicle and real traffic testing in highways and urban-like tracks shows the potential and validness of the integrated system.
Limit cycle prediction of a neural vehicle control system with gain-phase margin tester
(2006)
Perng, Jau-Woei
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Wu, Bing-Fei
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Lee, Tsu-Tian
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電控工程研究所
;
Institute of Electrical and Control Engineering
Based on some useful frequency domain methods, this paper proposes a systematic procedure to address the limit cycle prediction of a neural vehicle control system with adjustable parameters. A simple neurocontroller can be linearized by using describing function method firstly. According to the classical method of parameter plane, the stability of linearized system with adjustable parameters is then considered. In addition, gain margin and phase margin for limit cycle generation are also analyzed by adding a gain-phase margin tester into open loop system. Computer simulations show the efficiency of this approach.
Limit cycle prediction of a neurocontrol vehicle system based on gain-phase margin analysis
(2010-06-01)
Perng, Jau-Woei
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Ma, Li-Shan
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Wu, Bing-Fei
;
電控工程研究所
;
Institute of Electrical and Control Engineering
Based on some useful frequency domain methods, this paper proposes a systematic procedure to address the limit cycle prediction of a neural vehicle control system with adjustable parameters. A simple neurocontroller can be linearized by using describing function method firstly. According to the classical method of parameter plane, the stability of linearized system with adjustable parameters is then considered. In addition, gain margin and phase margin for limit cycle generation are also analyzed by adding a gain-phase margin tester into open loop system. Computer simulations show the efficiency of this approach.
Multi-sensor Information Integration on DSP Platform for Vehicle Navigation Safety and Driving Aid
(2009)
Lee, Tsu-Tian
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Chiang, Hsin-Han
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Perng, Jau-Woei
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Jiang, Jhong-Jie
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Wu, Bing-Fei
Intelligent transportation systems (ITS) are the mainstream of the development of next-generation technologies. The project of Human-centered technology (HT)-ITS in Taiwan has launched R&D researches in driver assistance and safety warning systems. This paper demonstrates a part result that a multi-sensors integrated system to achieve the purpose of the vehicle navigation and safety warning assistance. Multi-sensors including a global position system (GPS), a laser range finder, and an inertia measurement unit (IMU), are equipped on the vehicle to realize the manipulation of collision warning (CW), dead-reckoning (DR), and the operation of comfort-meter. The maneuver of CW is developed based on the idea that warning or potential crash information generally can be graded such that the driver need not react to a discrete on/off alarm. DR is responsible to estimate the vehicle location and trajectory when GPS floats. The purpose of the comfort-meter is to examine whether the vehicle driving does conform to the comfortable standard or not. The current states of the vehicle will also be transmitted to the far-end monitoring center, and shown in the graphical user interface through wireless transmission in order to monitor the vehicle driving status. The processing unit is realized on an embedded platform, as well as these functions are verified on real-road testing.
Observer-based synchronization for a class of unknown chaos systems with adaptive fuzzy-neural network
(2008-07-01)
Wu, Bing-Fei
;
Ma, Li-Shan
;
Perng, Jau-Woei
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This investigation applies the adaptive fuzzy-neural observer (AFNO) to synchronize a class of unknown chaotic systems via scalar transmitting signal only. The proposed method can be used in synchronization if nonlinear chaotic systems can be transformed into the canonical form of Lur'e system type by the differential geometric method. In this approach, the adaptive fuzzy-neural network (FNN) in AFNO is adopted on line to model the nonlinear term in the transmitter. Additionally, the master's unknown states can be reconstructed from one transmitted state using observer design in the slave end. Synchronization is achieved when all states are observed. The utilized scheme can adaptively estimate the transmitter states on line, even if the transmitter is changed into another chaos system. On the other hand, the robustness of AFNO can be guaranteed with respect to the modeling error, and external bounded disturbance. Simulation results confirm that the AFNO design is valid for the application of chaos synchronization.
Optimal signgle-input PID type fuzzy logic controller design with genetic algorithm
(2007)
Wu, Bing-Fei
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Ma, Li-Shan
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Perng, Jau-Woei
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Lee, Tsu-Tian
;
電控工程研究所
In this paper, the PID type single-input fuzzy logic controller (SFLC) is proposed by modified from PD type SFLC. By proposed structure, the steady error from PD type SFLC can be improved. Furthermore, the optimal control performance can be achieved by tuning membership function and gain parameter with genetic algorithm (GA). The simulation results show the proposed structure has better performance by comparing with GA PID and Ziegler-Nichols PID approaches.
Robust control design for perturbed systems by frequency domain approach
(2007-09-01)
Wu, Bing-Fei
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Chin, Hung-I
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Perng, Jau-Woei
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Lee, Tsu-Tian
;
電控工程研究所
This paper is concentrated on a perturbed vehicle control system whose gain margin (GM) and phase margin (PM) are analyzed and for which a novel controller design method satisfying the given specifications on GM, PM, and sensitivity is developed. The approach is applied to the plants with uncertain parameters that vary in intervals. Based on the parameter space method and robust stability criteria, gain and phase boundary curves are generated from the characteristic polynomial of the system with which a gain-phase tester is included in series to perform system stability analysis and controller design. The main concern in the controller design is to find a region in the controller coefficient plane so that the performance of the uncertain system satisfies given specifications. The proposed method is applied to an example of a bus system. Simulation results are given for illustration to show the system performances on GM and PM, and the desired controller meeting the specified conditions in frequency domain for the perturbed system is derived.
Robust longitudinal controller and observer design for vehicles with a riccati equation approach
(2006)
Wu, Bing-Fei
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Ma, Li-Shan
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Perng, Jau-Woei
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Chin, Hung-I
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Lee, Tsu-Tian
In this paper, the robust stabilizer with Riccati equations is applied to vehicle longitudinal system design. In our design, even if the uncertainties exist in vehicle systems, the designed observer and state feedback controller can stabilize the systems for any given initial conditions. In this method, Riccati equations are solved for finding positive-definite symmetry matrices to construct the observer and state feedback gain matrices. After the inter loop is stable, the PI controller is designed in outer loop for improving the ability of tracking performance. Finally, the simulation shows the feasibility of our design.
Robust stability analysis of a fuzzy vehicle lateral control system using describing function method
(2007)
Perng, Jau-Woei
;
Wu, Bing-Fei
;
Liao, Tien-Yu
;
Lee, Tsu-Tian
;
電控工程研究所
In this paper, the robust stability analysis of a fuzzy vehicle lateral system with perturbed parameters is presented. Firstly, the fuzzy controller can be linearized by utilizing the describing function method with experiments. After the describing function is obtained, the stability analysis of the vehicle lateral control system with the variations of velocity and friction is then carried out by the use of parameter plane method. Afterward some limit cycle loci caused by the fuzzy controller can be easily pointed out in the parameter plane. Computer simulation shows the efficiency of this approach.
Robust stability analysis of a fuzzy vehicle lateral control system using describing function method
(2007-01-01)
Perng, Jau-Woei
;
Wu, Bing-Fei
;
Liao, Tien-Yu
;
Lee, Tsu-Tian
;
電控工程研究所
In this paper, the robust stability analysis of a fuzzy vehicle lateral system with perturbed parameters is presented. Firstly, the fuzzy controller can be linearized by utilizing the describing function method with experiments. After the describing function is obtained, the stability analysis of the vehicle lateral control system with the variations of velocity and friction is then carried out by the use of parameter plane method. Afterward some limit cycle loci caused by the fuzzy controller can be easily pointed out in the parameter plane. Computer simulation shows the efficiency of this approach.
Robust stability analysis of a fuzzy vehicle lateral control system using describing function method
(2007)
Perng, Jau-Woei
;
Wu, Bing-Fei
;
Liao, Tien-Yu
;
Lee, Tsu-Tian
;
電控工程研究所
In this paper, the robust stability analysis of a fuzzy vehicle lateral system with perturbed parameters is presented. Firstly, the fuzzy controller can be linearized by utilizing the describing function method with experiments. After the describing function is obtained, the stability analysis of the vehicle lateral control system with the variations of velocity and friction is then carried out by the use of parameter plane method. Afterward some limit cycle loci caused by the fuzzy controller can be easily pointed out in the parameter plane. Computer simulation shows the efficiency of this approach.
Stability analysis of equilibrium points in static fuzzy control systems with reference inputs and adjustable parameters
(2006)
Wu, Bing-Fei
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Ma, Li-Shan
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Perng, Jau-Woei
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Chin, Hung-I
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Lee, Tsu-Tian
In this paper, the stability in static fuzzy control systems for linear systems with different fixed reference inputs and adjustable parameters are analyzed. Under certain conditions, the unique equilibriums of error in fuzzy control systems can be solved with fixed reference. Furthermore, when the unique equilibrium is stable, the steady state error can be obtained from this stable equilibrium. Under the adjustable parameters and reference inputs, the equilibriums may have stable and unstable transformations each other respect to absolutely stability. Additionally, the insight mechanism for oscillation of equilibrium is also given with a numerical example.
The Absolute Stability Analysis in Fuzzy Control Systems with Parametric Uncertainties and Reference Inputs
(2009-08-01)
Wu, Bing-Fei
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Ma, Li-Shan
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Perng, Jau-Woei
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電控工程研究所
;
Institute of Electrical and Control Engineering
This study analyzes the absolute stability in P and PD type fuzzy logic control systems with both certain and uncertain linear plants. Stability analysis includes the reference input, actuator gain and interval plant parameters. For certain linear plants, the stability (i.e. the stable equilibriums of error) in P and PD types is analyzed with the Popov or linearization methods under various reference inputs and actuator gains. The steady state errors of fuzzy control systems are also addressed in the parameter plane. The parametric robust Popov criterion for parametric absolute stability based on Lur'e systems is also applied to the stability analysis of P type fuzzy control systems with uncertain plants. The PD type fuzzy logic controller in our approach is a single-input fuzzy logic controller and is transformed into the P type for analysis. In our work, the absolute stability analysis of fuzzy control systems is given with respect to a non-zero reference input and an uncertain linear plant with the parametric robust Popov criterion unlike previous works. Moreover, a fuzzy current controlled RC circuit is designed with PSPICE models. Both numerical and PSPICE simulations are provided to verify the analytical results. Furthermore, the oscillation mechanism in fuzzy control systems is specified with various equilibrium points of view in the simulation example. Finally, the comparisons are also given to show the effectiveness of the analysis method.
The design of an intelligent real-time autonomous vehicle, Taiwan iTS-1
(2007-07-01)
Wu, Bing-Fei
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Chen, Chao-Jung
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Chiang, Hsin-Han
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Peng, Hsin-Yuan
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Perng, Jau-Woei
Developed at National Chiao Tung University, TAIWAN iTS-1 is the first smart car with active safety systems and comfortable autonomous driving in Taiwan. An adaptive vision-based lane detection algorithm was proposed to help the lateral control unit to keep the car in its lane safely. It also carries a DSP system to generate warning, signals for unintentional roadway departures. A laser radar measures the distance between the preceding car and TAIWAN iTS-1. With this information, the longitudinal control unit performs intelligent cruise control and stop-and-go functions. The remote control function is realized on TAIWAN iTS-1 for safety testing and military applications. Unlike most smart car studies, this paper considers not only driving safety demands but also non-driving security. An active mobile surveillance system will inform the car owner when the car is illegally broken into, anytime and anywhere. For drivers and passengers, the perception of comfort is achieved by intelligent vehicle dynamic control. All functions integrated into TAIWAN iTS-1 have been tested repeatedly on National Highway 3 and Expressway 68 in the Hsinchu area and the system's robustness has been successfully demonstrated in these real-road experiments.
The Embedded Driving-assistance System on Taiwan iTS-1
(2008)
Wu, Bing-Fei
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Chiang, Hsin-Han
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Lee, Tsu-Tian
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Perng, Jau-Woei
;
電控工程研究所
Vehicle automation is an important research topic of advanced vehicle systems (AVS). Taiwan iTS-1 is the first smart car with autonomous driving in Taiwan. In this paper, an embedded driving-assistance system is presented. The definition of hierarchical-control structure is necessary in the system to deal with sensorial inputs and environmental and procedural knowledge to manage vehicle actuators in order to accomplish various driving tasks. Upper-level control perceives road environment and determines the proper and safe operation modes including lane-keeping, lane-change, cruise control, adaptive cruise control, and stop-and-go. Wench mode, the desired-velocity and reference-trajectory are primarily determined, and then are forwarded to vehicle-body control. To incorporate well driver behavior into our system, vehicle-body control utilizes the fuzzy control technique to manage the fundamental actuators of vehicle, steering wheel, throttle, and brake, to adapt to the desired command (velocity and trajectory). The core controller is built-in on a DSP-based embedded computing platform. The aim of our system is to provide the driving-assistance in the same way human drivers do.
The heterogeneous systems integration design and implementation for lane keeping on a vehicle
(2008-06-01)
Wu, Shinq-Jen
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Chiang, Hsin-Han
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Perng, Jau-Woei
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Chen, Chao-Jung
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Wu, Bing-Fei
In this paper, an intelligent automated lane-keeping system is proposed and implemented on our vehicle platform, i.e., TAIWAN iTS-1. This system challenges the online integrating heterogeneous systems such as a real-time vision system, a lateral controller, in-vehicle sensors, and a steering wheel actuating motor. The implemented vision system detects the lane markings ahead of the vehicle, regardless of the varieties in road appearance, and determines the desired trajectory based on the relative positions of the vehicle with respect to the center of the road. To achieve more humanlike driving behavior such as smooth turning, particularly at high levels of speed, a fuzzy gain scheduling (FGS) strategy is introduced to compensate for the feedback controller for appropriately adapting to the SW command. Instead of manual tuning by trial and error, the methodology of FGS is designed to ensure that the closed-loop system can satisfy the crossover model principle. The proposed integrated system is examined on the standard testing road at the Automotive Research and Testing Center (ARTC)(1) and extraurban highways.