• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2001.10a
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• pp.122-127
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• 2001

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.10a
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• pp.256-261
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• 2002

In this paper, it is presented a new scheme of adaptive-neuro control system to implement real-time control of robot manipulator. Unlike the well-established theory for the adaptive control of linear systems, there exists relatively little general theory for the adaptive control of nonlinear systems. Adaptive control technique is essential for providing a stable and robust performance for application of robot control. The proposed neuro control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method. Through simulation, the proposed adaptive-neuro control scheme is proved to be a efficient control technique for real-time control of robot system using DSPs.

• Earthquakes and Structures
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• v.17 no.3
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• pp.307-315
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• 2019

Building prediction and control theory have been drawing the attention of many scientists over the past few years because design and control efficiency consumes the most financial and energy. In the literature, many methods have been proposed to achieve this goal by trying different control theorems, but all of these methods face some problems in correctly solving the problem. The Evolutionary Bat (EB) Algorithm is one of the recently introduced optimization methods and providing researchers to solve different types of optimization problems. This paper applies EB to the optimization of building control design. The optimized parameter is the input to the fuzzy controller, which gives the status response as an output, which in turn changes the state of the associated actuator. The novel control criterion for guarantee of the stability of the system is also derived for the demonstration in the analysis. This systematic and simplified controller design approach is the contribution for solving complex dynamic engineering system subjected to external disturbances. The experimental results show that the method achieves effective results in the design of closed-loop system. Therefore, by establishing the stability of the closed-loop system, the behavior of the closed-loop building system can be precisely predicted and stabilized.

• Journal of Power System Engineering
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• v.5 no.2
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• pp.87-92
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• 2001

Automotive suspension system is a mechanism for isolation of the vibration coming from the road inputs. Recently, the electronically controlled suspension systems which may improve ride and handling performance have been developed. Here, the continuously controlled semi-active suspension system is focused. As a mechanism to control damping forces continuously, a solenoid valve is used. The modeling for the solenoid valve is introduced briefly, a vehicle dynamics modeling is constructed, and then combined system model is completed. To design the efficient control algorithm for the semiactive suspension system the knowledge based fuzzy logic is applied and the technique how to apply the sky-hook theory to the fuzzy logic is developed. Finally, to confirm the improvement of performance the computer simulation is carried out.

• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.198-203
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• 2008

An Intelligent optimal control system design algorithm in active suspension equipment adopting linear matrix inequalities control system design theory with representing by descriptor system form is presented. The validity of the linear matrix inequalities intelligent decentralized control system design with representing by descriptor system form in active suspension system through the numerical examples is also investigated.

• Smart Structures and Systems
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• v.19 no.4
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• pp.351-360
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• 2017

Protection of structures against natural hazards such as earthquakes has always been a major concern. Semi-active control combines the reliability of passive control and versatility and adaptability of active control. So it has recently become a preferred control method. This paper proposes an algorithm based on Uniform Deformation Theory to mitigate vulnerable buildings using magneto-rheological (MR) damper. Due to the successful performance of fuzzy logic in control of systems and its simplicity and intrinsically robustness, it is used here to regulate MR dampers. The particle swarm optimization (PSO) algorithm is also used as an adaptive method to develop a fuzzy control algorithm that is able to create uniform inter-story drifts. Results show that the proposed algorithm exhibited a desirable performance in reducing both linear and nonlinear seismic responses of structures. Performance of the presented method is indicated in compare with passive-on and passive-off control algorithms.

• Transactions on Control, Automation and Systems Engineering
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• v.1 no.2
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• pp.94-98
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• 1999

Optical scanning systems use glavanometers to point the laser beam to the desired position on the workpiece. The angular speed of a galvanometer is typically controlled using Proportional+Integral+Derivative(PID) control algorithms. However, natural variations in the dynamics of different galvanometers due to manufacturing, aging, and environmental factors(i.e., process uncertainty) impose a hard limit on the bandwidth of the galvanometer control system. In general, the control bandwidth translates directly into efficiency of the system response. Since the optical scanning system must have rapid response, the higher control bandwidth is required. Auto-tuning PID algorithms have been accepted in this area since they could overcome some of the problems related to process uncertainty. However, when the galvanometer is attached to a larger mechanical system, the combined dynamics often exhibit resonances. It is well understood that PId algorithms may not have the capacity to increase the control bandwidth in the face of such resonances. This paper compares the achieable performance and robustness of a galvanometer control system using a PID controller tuned by the Ziegler-Nichols method and a controller designed by the Quantitative Feedback Theory(QFT) method. The results clearly indicate that-in contrast to PID designs-QFT can deliver a single, fixed controller which will supply high bandwidth design even when the dynamics is uncertain and includes mechanical resonances.

• Journal of the Korean Mathematical Society
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• v.50 no.1
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• pp.17-39
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• 2013

The study of nonlinear discrete-time control dynamical systems with disturbance is an important topic in control theory. In this paper, we concentrate our efforts to multiple valued iterative dynamical systems, which model the nonlinear discrete-time control dynamical systems with disturbance. After establishing the validity of such modeling, we study the invariant set theory of the multiple valued iterative dynamical systems, including the controllability/reachablity problems of the maximal invariant sets.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.3
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• pp.65-72
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• 2001

Generally, it is said that control of the inertia system is to track the reference input quickly while suppressing the vibration due to the system itself. In this case, the difficulty fur designing a controller is caused by modeling uncertainty and parameter variation. The purpose of this paper is to propose a design method to suppress the vibration of three-mass inertia system based on the LMI theory. That is, the generalized plant model by which we can cope with conservativeness of the existing H$_{*}$ theory is proposed and analyzed in terms of LMI. The results of simulation fur the three-mass inertia system show that the proposed design approach is quite effective under the given situations.

• The Journal of Korean Physical Therapy
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• v.11 no.3
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• pp.23-36
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• 1999

The very definitions of posture and balance have changed, as has our understanding of the underlying neural mechanisms, In rehabilitation science, there awe at least two different conceptual theories to describe the neural control of posture and balance : the reflex/hierarchical theory and system theory. A reflex/hierarchical theory suggests the posture and balance result from hierarchically organized reflex responses triggered by independent sensory systems. The systems approach suggests that action emerges from an interaction of the individual with the task and environment. That is to say, the systems approach implies that the ability to control our body's position in space emerges from a complex interaction of musculoskeletal and neural systems, collectively referred to as the postural control system. The specific organization of postural systems determined both by the functional task and the environment in which it is being performed, The postural control system is divided into three basic functional components for assessment : 1) musculoskeletal components, 2) motor coordination components, and 3) sensory organization components. It is proposed that a systemic functional understanding of human balance is critical to effective programs for balance rehabilitation. Thus, this article briefly reviews the basic functional components to consider in designing treatment plan and for the benefit of the balance assessment.