Browsing by Author "Perng, JW"

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An intelligent vision-based real-time integration system on autonomous vehicles
(2004)
Wu, BF
;
Chiu, CC
;
Chen, CJ
;
Wu, WC
;
Perng, JW
In this paper, an intelligent real-time system on autonomous vehicles is presented. A wireless-based remote control scheme is developed. A vision-based obstacle detection system and a radar sensor are integrated into the on-vehicle controller to automatically brake the vehicle under emergency. Finally, a successfully on-road demonstration is also completed with our experimental car. TAIWAN iTS-1.(1)
Gain-phase margin analysis of dynamic fuzzy control systems
(2004-10-01)
Perng, JW
;
Wu, BF
;
Chin, HI
;
Lee, TT
;
電控工程研究所
In this paper, we apply some effective methods, including the gain-phase margin tester, describing function and parameter plane, to predict the limit cycles of dynamic fuzzy control systems with adjustable parameters. Both continuous-time and sampled-data fuzzy control systems are considered. In general, fuzzy control systems are nonlinear. By use of the classical method of describing functions, the dynamic fuzzy controller may be linearized first. According to the stability equations and parameter plane methods, the stability of the equivalent linearized system with adjustable parameters is then analyzed. In addition, a simple approach is also proposed to determine the gain margin and phase margin which limit cycles can occur for robustness. Two examples of continuous-time fuzzy control systems with and without nonlinearity are presented to demonstrate the design procedure. Finally, this approach is also extended to a sampled-data fuzzy control system.
Gain-phase margin analysis of fuzzy control systems
(2003)
Perng, JW
;
Wu, BF
;
Lee, TT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
In this paper, we extend some effective methods, including the gain-phase margin tester method, the describing function method and the parameter plane method, to predict the limit cycles of fuzzy control systems. In general, fuzzy control systems are nonlinear. By use of the classical method of describing functions, a fizzy controller may be linearized first. The stability of the equivalent linearized system with adjustable parameters is then analyzed due to the stability equations and parameter plane methods. For the robust design, a novel way is proposed to determine the gain margin and phase margin which limit cycles can occur. Two examples are offered to illustrate the design procedure. First, the fuzzy control system with a third-order linear plant is considered. In addition, this approach is also extended to the fuzzy control system with nonlinearity. The results of computer simulation can verify its validity.
Gain-phase margin analysis of pilot-induced oscillations for limit-cycle prediction
(2004-01-01)
Wu, BF
;
Perng, JW
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This investigation attempts to forecast the limit cycles of pilot-induced oscillations (PIOs) by combining the gain-phase margin tester, the M-locus, and the parameter plane methods. First, one position- or rate-limited nonlinear element is linearized by the conventional means of describing functions. The stability of an equivalent linearized system with adjustable parameters is then analyzed using stability equations and the parameter plane method. Additionally, the minimum gain-phase margin of the PIO system at which a limit cycle can occur is determined by inserting the gain-phase margin tester into the forward open-loop system. Moreover, a simple method is developed to identify the intersections of the M locus and the constant gain and phase boundaries in the parameter plane. In so doing the exact relationship between the gain-phase margin and the characteristics of the limit cycle can be clearly determined. The results of this study demonstrate that. these procedures can enhance. the analysis of PIO over analysis by other methods in the literature. This approach is extended to PIO analysis with multiple nonlinearities.
H(infinity) tracking-based sliding mode longitudinal control of a platoon of vehicles
(2004)
Wu, BF
;
Ma, LS
;
Perng, JW
;
Lee, TT
;
電控工程研究所
In this paper, the H, tracking-based sliding mode design is applied into the longitudinal control of a platoon of vehicles. Due to this approach, the robustness for the external disturbance and the suppression of the chattering control input are both provided. In provided scheme, the upper bound of the external disturbance should not be known previously and designed control law can still work to reduce the effect of the external disturbance.
Limit cycle analysis of nonlinear sampled-data systems by gain-phase margin approach
(2004)
Wu, BF
;
Perng, JW
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The main purpose of this work is to analyze the limit cycle phenomena of nonlinear sampled-data systems by applying the methods of gain-phase margin tester, the M-locus and the parameter plane. First, a sampled-data control system with nonlinear elements is linearized by the classical method of describing functions. According to stability equations and the parameter plane method, we can then analyze the stability of the equivalent linearized system with adjustable parameters. After adding the gain-phase margin tester in the forward open loop system, the relationship between the gain-phase margin and the characteristics of the limit cycle may be elucidated by finding the intersections of the M-locus and the constant gain and phase boundaries. A concise method is presented to solve this problem. In doing so, the minimum gain-phase margin of nonlinear sampled-data system at which a limit cycle can occur is conferred. This paper manifests that the procedure can be easily extended to analyze the limit cycles of a sampled-data system as compared with the continuous-data system cases in the literatures. Computer simulation results can verify its validity.
Limit cycle analysis of nonlinear sampled-data systems by gain-phase margin approach
(2005-03-01)
Wu, BF
;
Perng, JW
;
Chin, HI
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This work analyzes the limit cycle phenomena of nonlinear sampled-data systems by applying the methods of gain-phase margin testing, the M-locus and the parameter plane. First, a sampled-data control system with nonlinear elements is linearized by the classical method of describing functions. The stability of the equivalent linearized system is then analyzed using the stability equations and the parameter plane method, with adjustable parameters. After the gain-phase margin tester has been added to the forward open-loop system, exactly how the gain-phase margin and the characteristics of the limit cycle are related can be elicited by determining the intersections of the M-locus and the constant gain and phase boundaries. A concise method is presented to solve this problem. The minimum gain-phase margin of the nonlinear sampled-data system at which a limit cycle can occur is investigated. This work indicates that the procedure can be easily extended to analyze the limit cycles of a sampled-data system from a continuous-data system cases considered in the literature. Finally, a sampled-data system with multiple nonlinearities is illustrated to verify the validity of the procedure. (C) 2004 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
Limit cycle analysis of PID controller design
(2003)
Wu, BF
;
Perng, JW
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The main purpose of this paper is to predict limit cycles of nonlinear PID control systems with adjustable parameters by the approaches of stability equation, describing function and parameter plane. First, nonlinear elements are linearized by the classical describing function method. The stability of equivalent linearized system with adjustable parameters is then analyzed by using the stability equations and the parameter plane method. According to our study, the characteristics of limit cycles with PID control design in current literature can be improved. Finally, this approach is also extended to a sampled-data control system with broken line nonlinearity.
Limit cycle analysis of uncertain fuzzy vehicle control systems
(2005)
Perng, JW
;
Wu, BF
;
Chin, HI
;
Lee, TT
;
電控工程研究所
In this paper, some useful frequency domain methods including describing function, parameter space and Kharitonov approach are applied to analyze the stability of a fuzzy vehicle control system for limit cycle prediction. A systematic procedure is proposed to solve this problem. In general, fuzzy control systems are nonlinear systems. The fuzzy controller can be linearized by the use of classical describing function firstly. By doing so, it is feasible to treat the stability problem of fuzzy control systems as linear one. In order to consider the robustness of the fuzzy vehicle control system, parameter space method and Kharitonov approach are then employed for plotting the stability boundaries. Furthermore, the effect of transport delay is also addressed. Much information of limit cycles can be obtained by this approach. Our work shows that the limit cycles caused by a fuzzy controller can be easily suppressed if the system parameters are chosen carefully.
Neural control for a perturbed vehicle steering system using parameter plane method
(2005)
Perng, JW
;
Wu, BF
;
Lee, TT
;
電控工程研究所
;
Institute of Electrical and Control Engineering
The robust stability analysis of a neural control based vehicle steering system is considered in this paper. The neural controller can be linearized by the use of describing function first. Since the perturbed parameters including velocity and friction are existed in the vehicle steering system, the stability of equivalent linearized system is then analyzed by using the parameter plane method. According to this procedure, the amplitude and frequency of limit cycles caused by the neural controller can be figured out clearly in the parameter plane. Moreover, the limit cycles may be suppressed by adjusting the control factors carefully. Computer simulation shows the efficiency of this approach.
Parameter plane analysis of fuzzy control systems for limit cycle prediction
(2003)
Perng, JW
;
Wu, BF
;
Lee, TT
;
Wu, WC
;
電控工程研究所
The main purpose of this paper is to predict the limit cycles of fuzzy control system by combining the approaches of stability equation, describing function and parameter plane. The fuzzy controller is first linearized by using the describing function method. The stability of equivalent linearized system is. then analyzed by using stability equations and the parameter plane method. According to this procedure, the amplitude and frequency of limit cycles generated by the fuzzy controller can be figured out clearly in the parameter plane. In addition, both the continuous and sampled-data systems are considered. Finally, a fuzzy control system with multiple nonlinearities is also illustrated to verify its validity.
Parameter plane analysis of neurocontrol vehicle systems for limit cycle prediction
(2003)
Wu, BF
;
Perng, JW
;
Lee, TT
;
電機學院
;
College of Electrical and Computer Engineering
The main purpose of this paper is to predict the limit cycles, of neurocontrol system with perturbed parameters by combining the approaches of stability equation, describing function and parameter plane. The neurocontroller is first linearized by using the describing function method. The stability of equivalent linearized system is then analyzed by using stability equations and the parameter plane method. According to this procedure, the amplitude and frequency of limit cycles can be figured out clearly in the parameter plane. Moreover, the limit cycle may be suppressed by adjusting the control parameters carefully. Finally, a vehicle model is illustrated to demonstrate its validity.
Robust control design of front-wheel-steering system by LMI approach
(2004)
Wu, BF
;
Chang, SM
;
Perng, JW
;
電控工程研究所
;
Institute of Electrical and Control Engineering
This paper presents an application of H-infinity robust control theory to a Front-Wheel-Steering (FWS) mechanical model (complex model) substituted for the linearized dynamics model. The input signal of the structure can be determined by a given steering angle, and then a Linear Matrix Inequality (LMI) based on H, method is proposed to solve the uncertainty problem under the conditions of the mass and velocity. Finally the simulation results show that the remainder velocities and masses are located inside the assignment boundary.
Robust PI controller design for vehicle steering systems
(2005)
Perng, JW
;
Ma, LS
;
Wu, BF
;
Lee, TT
;
電控工程研究所
In this paper, the robust analysis and design of vehicle steering control systems with uncertainties are considered by the use of parameter plane method and gain-phase margin tester method. A systematic design procedure is proposed to solve this problem. First, a single tracked vehicle model is given for the design and the suitable operating range of vehicle system is also defined. Based on the parameter plane method and gain-phase margin tester method, a simple PI controller is developed to have desirable values of gain margins and phase margins in our work. Furthermore, limit cycles generated from a saturation element of vehicle system are also discussed. Computer simulation results show the efficiency of our approach.
Sliding mode tracking control for Chua's circuit
(2004)
Wu, BF
;
Ma, LS
;
Perng, JW
;
Lee, TT
;
電控工程研究所
In this paper, H(infinity) sliding mode control is applied to enhance the robust tracking of Chua's circuit systems. Chua's circuit is transformed into standard control canonical form firstly. Furthermore, the error dynamics can be formulated from the master and slave Chua's circuits. In so doing, the tracking problem can be viewed as regular one. Then, H(infinity) sliding mode controller is presented to achieve the robust stability under the effect of external disturbance. The simulation results can demonstrate the feasibility of this approach.
Stability analysis of a robust fuzzy vehicle steering control system
(2005)
Perng, JW
;
Chin, HI
;
Wu, BF
;
Lee, TT
;
電控工程研究所
The main purpose of this paper is to analyze the stability for a fuzzy vehicle steering control system. In general, fuzzy control system is a nonlinear control system. Therefore, the fuzzy controller may be linearized by the use of describing function first; After then, the traditional frequency domain method i.e. parameter plane, is then applied to determine the condition of stability when the system has perturbed or adjustable parameters. A systematic procedure is proposed to solve this problem. The stability problem under the effects of plant parameters and control factors are both considered here. Furthermore, the effect of transport delay is also addressed. The limit cycles provided by a static fuzzy controller can be easily suppressed if the system parameters are chosen properly. Simulation results show the efficiency of our approach.