• Journal of Auto-vehicle Safety Association
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• v.12 no.4
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• pp.13-22
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• 2020

This paper presents an adaptive feedback based actuator fault detection and tolerant control algorithms for longitudinal functional safety of autonomous driving. In order to ensure the functional safety of autonomous vehicles, fault detection and tolerant control algorithms are needed for sensors and actuators used for autonomous driving. In this study, adaptive feedback control algorithm to compute the longitudinal acceleration for autonomous driving has been developed based on relationship function using states. The relationship function has been designed using feedback gains and error states for adaptation rule design. The coefficients in the relationship function have been estimated using recursive least square with multiple forgetting factors. The MIT rule has been adopted to design the adaptation rule for feedback gains online. The stability analysis has been conducted based on Lyapunov direct method. The longitudinal acceleration computed by adaptive control algorithm has been compared to the actual acceleration for fault detection of actuators used for longitudinal autonomous driving.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.10
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• pp.94-104
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• 1996

This paper presents a new approach to the design of adaptive control system using DSPs(TMS320C31) for robotic manpulators to achieve accurate trajectory tracking by the joint angles Digital signal processors are used in implementing real time adaptive control algorithms to provide an enhanced motion control for robotic manipulators. In the proposed contorl scheme, adaptation laws are derived from the improved Lyapunov second stability analysis method based on the adaptive model reference control theory. The adaptive controller consists of an adaptive feedforward controller, feedback controller, and PID type time varying auxillary control elements. The proposed adaptive control scheme is simple in structure, fast in computation, and suitable for implementation of real-time control. Morever, this scheme does not require an accurate dynamic modeling nor values of manpipulator parameters and payload. Performance of the adaptive controller is illustated by simulation and experimental results for a SCARA robot.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.2
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• pp.77-88
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• 2018

This paper proposes a RBFNN(Radial Basis Function Neural Network) based decentralized adaptive tracking control scheme using PSO(Particle Swarm Optimization) for an uncertain electrically driven robot system with input saturation. Practically, the magnitudes of input voltage and current signals are limited due to the saturation of actuators in robot systems. The proposed controller overcomes this input saturation and does not require any robot link and actuator model parameters. The fitness function used in the presented PSO scheme is expressed as a multi-objective function including the magnitudes of voltages and currents as well as the tracking errors. Using a PSO scheme, the control gains and the number of the RBFs are tuned automatically and thus the performance of the control system is improved. The stability of the total control system is guaranteed by the Lyapunov stability analysis. The validity and robustness of the proposed control scheme are verified through simulation results.

• Advances in concrete construction
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• v.13 no.5
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• pp.385-394
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• 2022

Recently, an increasing number of cutting-edged studies have shown that designing a smart active control for real-time implementation requires piles of hard-work criteria in the design process, including performance controllers to reduce the tracking errors and tolerance to external interference and measure system disturbed perturbations. This article proposes an effective artificial-intelligence method using these rigorous criteria, which can be translated into general control plants for the management of civil engineering installations. To facilitate the calculation, an efficient solution process based on linear matrix (LMI) inequality has been introduced to verify the relevance of the proposed method, and extensive simulators have been carried out for the numerical constructive model in the seismic stimulation of the active rigidity. Additionally, a fuzzy model of the neural network based system (NN) is developed using an interconnected method for LDI (linear differential) representation determined for arbitrary dynamics. This expression is constructed with a nonlinear sector which converts the nonlinear model into a multiple linear deformation of the linear model and a new state sufficient to guarantee the asymptomatic stability of the Lyapunov function of the linear matrix inequality. In the control design, we incorporated H Infinity optimized development algorithm and performance analysis stability. Finally, there is a numerical practical example with simulations to show the results. The implication results in the RMS response with as well as without tuned mass damper (TMD) of the benchmark building under the external excitation, the El-Centro Earthquake, in which it also showed the simulation using evolved bat algorithmic LMI fuzzy controllers in term of RMS in acceleration and displacement of the building.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.89-98
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• 2015

This paper provides a robust and non-fragile $H_{\infty}$ controller design algorithm for time-delayed systems with randomly occurring polytopic uncertainties and disturbances. First, we design time-delayed system considering randomly occurring uncertainties and disturbances. Next, The sufficient condition for the existence of robust and non-fragile $H_{\infty}$ controller is presented by LMI(linear matrix inequality) using Lyapunov stability analysis and $H_{\infty}$ performance measure. Since the obtained condition can be expressed as a PLMI(parameterized linear matrix inequality) by changes of variables and Schur complement, all solutions including controller gain, degrees of controller satisfying non-fragility, $H_{\infty}$ norm bound ${\gamma}$ can be calculated simultaneously. Finally, numerical examples are given to illustrate the performance and the effectiveness of the proposed robust and non-fragile $H_{\infty}$ controller compared with the deterministic uncertainty model even though there exists randomly occurring uncertainties, disturbances and time delays.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.41 no.3
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• pp.200-209
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• 2013

In this paper, the types of B-dot controller and the review results of B-dot controller stability are summarized. Also, it is confirmed that B-dot controller is very useful and essential tool when a dawn-dusk low earth orbit(LEO) large satellite has especially to capture the Sun for a required power supply in a reliable way after anomaly and that its algorithm is very simple for on-board implementation. New physical interpretation of B-dot controller is presented as a result of extensive theoretical investigation introducing the concept of transient control torque and steady state control torque. Also, the failure effect analysis results of magnetic torquers as well as a simulation verification are included. And the design recommendation for optimal design is provided to cope with the failure of magnetic torquer. Nonlinear simulation results are included to justify its capability as well as its performance for an application to a dawn-dusk LEO large satellite.