• Journal of Institute of Control, Robotics and Systems
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• v.18 no.10
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• pp.902-911
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• 2012

This paper proposes a robust adaptive fuzzy backstepping control scheme for trajectory tracking of an electrically driven nonholonomic mobile robot with uncertainties and actuator dynamics. A complete model of an electrically driven nonholonomic mobile robot described in this work includes all models of the uncertain robot kinematics with a nonholonomic constraint, the uncertain robot body dynamics with uncertain frictions and unmodeled disturbances, and the uncertain actuator dynamics with disturbances. The proposed control scheme uses the backstepping control approach through a kinematic controller and a robust adaptive fuzzy velocity tracking controller. The presented control scheme has a voltage control input with an auxiliary current control input rather than a torque control input. It has two FBFNs(Fuzzy Basis Function Networks) to approximate two unknown nonlinear robot dynamic functions and a robust adaptive control input with the proposed adaptive laws to overcome the uncertainties such as parameter uncertainties and external disturbances. The proposed control scheme does not a priori require the accurate knowledge of all parameters in the robot kinematics, robot dynamics and actuator dynamics. It can also alleviate the chattering of the control input. Using the Lyapunov stability theory, the stability of the closed-loop robot control system is guaranteed. Simulation results show the validity and robustness of the proposed control scheme.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.845-846
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• 2006

In this paper, we describe a capacitive position sensing and motion control scheme of a MEMS scanner used for laser display application. The laser displays can be made by scanning laser beams much the same way a CRT scans electron beams. So the accuracy of the scanner motion determines the quality of the displayed image. The MEMS scanner under consideration is composed of electrostatic comb electrodes with initial gap and requires large driving voltage. Due to the under-damping and nonlinear driving characteristics, the scanner motion is subject to be an unwanted oscillation. For the linear scanner motion, we devise a differential charge amplifier and phase compensator. The experimental results show that the implemented feedback control system provides sufficient electrical damping and improves the dynamic performance of the scanner.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.10 no.1
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• pp.12-18
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• 2010

This paper proposes an adaptive robust fuzzy control scheme for path tracking of a wheeled mobile robot with uncertainties. The robot dynamics including the actuator dynamics is considered in this work. The presented controller is composed of a fuzzy basis function network (FBFN) to approximate an unknown nonlinear function of the robot complete dynamics, an adaptive robust input to overcome the uncertainties, and a stabilizing control input. Genetic algorithms are employed to optimize the fuzzy rules of FBFN. The stability and the convergence of the tracking errors are guaranteed using the Lyapunov stability theory. When the controller is designed, the different parameters for two actuator models in the dynamic equation are taken into account. The proposed control scheme does not require the accurate parameter values for the actuator parameters as well as the robot parameters. The validity and robustness of the proposed control scheme are demonstrated through computer simulations.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.623-625
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• 2000

For the finite element analysis of highly saturated rotating machines involving rotation of a rotor such as dynamic analysis. cogging torque analysis and etc, so much time is needed because a new system matrix equation should be solved for each iteration and time step. It is proved in this paper that. in linear systems. the computational time can be greatly reduced by using the domain decomposition method (DDM). In nonlinear systems. however. this advantage vanishes because the stiffness matrix changes at each iteration especially when using the Newton-Raphson (NR) method. The transmission line modeling (TLM) method resolves this problem because in TLM method the stiffness matrix does not change throughout the entire analysis. In this paper, a new technique for FEA of rotating machines including rotation of rotor and non-linearity is proposed. This method is applied to a test problem. and compared with the conventional method.

• Wind and Structures
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• v.13 no.5
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• pp.451-469
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• 2010

The majority of weather-related failures of transmission line structures that have occurred in the past have been attributed to high intensity localized wind events, in the form of tornadoes and downbursts. A numerical scheme is developed in the current study to assess the performance of transmission lines under tornado wind load events. The tornado wind field is based on a model scale Computational Fluid Dynamic (CFD) analysis that was conducted and validated in a previous study. Using field measurements and code specifications, the CFD model data is used to estimate the wind fields for F4 and F2 full scale tornadoes. The wind forces associated with these tornado fields are evaluated and later incorporated into a nonlinear finite element three-dimensional model for the transmission line system, which includes a simulation for the towers and the conductors. A comparison is carried between the forces in the members resulting from the tornadoes, and those obtained using the conventional design wind loads. The study reveals the importance of considering tornadoes when designing transmission line structures.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.1
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• pp.43-50
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• 2001

In this paper, we propose the design procedure of advance Polynomial Neural Networks(PNN) architecture for optimal model identification of complex and nonlinear system. The proposed PNN architecture is presented as the generic and advanced type. The essence of the design procedure dwells on the Group Method of Data Handling(GMDH). PNN is a flexible neural architecture whose structure is developed through learning. In particular, the number of layers of the PNN is not fixed in advance but is generated in a dynamic way. In this sense, PNN is a self-organizing network. With the aid of three representative numerical examples, compari-sons show that the proposed advanced PNN algorithm can produce the model with higher accuracy than previous other works. And performance index related to approximation and generalization capabilities of model is evaluated and also discussed.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.1
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• pp.66-72
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• 2000

As the demand for the design of modular manipulators or special purpose manipulators has increased, task based design to design an optimal manipulator for a given task become more and more important. However, the complexity with a large number of design parameters, and highly nonlinear and implicit functions are characteristics of a general manipulator design. To achieve the goal of task based design, it is necessary to develop a methodology to solve the complexity. This paper addresses how to determine the kinematic parameters of a two-degrees of freedom manipulator with parallelogram five-bar link mechanism from a given task, namely, how to map a given task into the kinematic parameters. With simplified example of designing a manipulator with five-bar link mechanism, the methodology for task based design is presented. And it introduces formulations of a given task and manipulator specifications, and presents a new dexterity measure for manipulator design. Also the optimization problem with constraints is solved by using a genetic algorithm that provides robust search in complex spaces.

• Journal of Ocean Engineering and Technology
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• v.19 no.1 s.62
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• pp.87-94
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• 2005

This paper investigates the constant-level luffing and time optimal control of jib cranes. The constant-level luffing, which is the sustainment of the load at a constant height during luffing, is achieved by analyzing the kinematic relationship between the angular displacement of a boom and that of the main hoist motor of a jib crane. Under the assumption that the main body of the crane does not rotate, the equations of motion of the boom are derived using Newton's Second Law. The dynamic equations for the crane system are highly nonlinear; therefore, they are linearized under the small angular motion of the load to apply linear control theory. This paper investigates the time optimal control from the perspective of no-sway at a target point. A stepped velocity pattern is used to design the moving path of the jib crane. Simulation results demonstrate the effectiveness of the time optimal control, in terms of anti-sway motion of the load, while luffing the crane.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1740-1751
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• 2018

This paper proposes a novel fault tolerant tracking control (FTTC) scheme for a class of nonlinear systems with actuator failures based on the policy iteration (PI) algorithm and the adaptive fault observer. The estimated actuator failure from an adaptive fault observer is utilized to construct an improved performance index function that reflects the failure, regulation and control simultaneously. With the help of the proper performance index function, the FTTC problem can be transformed into an optimal control problem. The fault tolerant tracking controller is composed of the desired controller and the approximated optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, and the approximated optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. By establishing a critic neural network, the PI algorithm is utilized to solve the Hamilton-Jacobi-Bellman equation, and then the approximated optimal feedback controller can be derived. Based on Lyapunov technique, the uniform ultimate boundedness of the closed-loop system is proven. The proposed FTTC scheme is applied to reconfigurable manipulators with two degree of freedoms in order to test the effectiveness via numerical simulation.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1079-1082
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• 1996

To automate an excavator the control issues resulting from environmental uncertainties must be solved. In particular the interactions between the excavation tool and the excavation environment are dynamic, unstructured and complex. In addition, operating modes of an excavator depend on working conditions, which makes it difficult to derive the exact mathematical model of excavator. Even after the exact mathematical model is established, it is difficult to design of a controller because the system equations are highly nonlinear and the state variable are coupled. The objective of this study is to design a fuzzy logic controller(FLC) which controls the position of excavator's attachment. This approach enables the transfer of human heuristics and expert knowledge to the controller. Excavation experiments are carried out to check the performance of the FLC.