• Journal of Biosystems Engineering
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• v.42 no.1
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• pp.23-43
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• 2017

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.797-804
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• 2017

A social network is a typical social science environment with both network and iteration characteristics. This research presents a reaction analysis model of how each node responds to social networks when given input such as promotions or incentives. In addition, the setting value of a specific node is changed while examining the response of each node. And we try to understand the reactions of the nodes involved. The reaction analysis model is constructed by applying various techniques such as unidirectional, fuzzy set, weighting, and cyclic feedback, so it can accommodate the complicated environment of practice. Finally, the implementation model is implemented using Vensim rather than NetLogo because it requires repetitive input, change of setting value in real time, and analysis of association between nodes.

• Transactions on Electrical and Electronic Materials
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• v.15 no.6
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• pp.297-304
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• 2014

Due to the nonlinearity and complexity of the three-phase photovoltaic inverter, we propose an intelligent control based on fuzzy logic and the classical proportional-integral-derivative. The feedback linearization method is applied to cancel the nonlinearities, and transform the dynamic system into a simple and linear subsystem. The system is transformed from abc frame to dq0 synchronous frame, to simplify the state feedback linearization law, and make the close-loop dynamics in the equivalent linear model. The controls improve the dynamic response, efficiency and stability of the three-phase photovoltaic grid system, under variable temperature, solar intensity, and load. The intelligent control of the nonlinear characteristic of the photovoltaic automatically varies the coefficients $K_p$, $K_i$, and $K_d$ under variable temperature and irradiation, and eliminates the oscillation. The simulation results show the advantages of the proposed intelligent control in terms of the correctness, stability, and maintenance of its response, which from many aspects is better than that of the PID controller.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.37-39
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• 2000

This paper describes the application of Fuzzy Logic Controller (FLC) to Thyristor Controlled Series Capacitor (TCSC) which can have significant impact on Power system dynamics. The function of the FLC is to control the firing angle of the TCSC. We tuned the scaling factors of the FLC using Tabu Search. The proposed FLC is used for damping the low frequency oscillations caused by disturbances such as the sudden changes of small of large loads or the outages in the generators or transmission lines. To evaluate usefulness of the proposed FLC. we performed the computer simulation for single-machine infinite system. The response of FLC is compared with that of PD controller optimized using Tabu Search. Simulation results that the FLC shows the better control performance than PD controller.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.4
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• pp.481-486
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• 2004

The biped robot has the better mobility than the conventional wheeled robot. Since a biped robot tends to tip over easily, it is necessary to take stability into account when determining a walking pattern. To ensure the dynamic stability of the biped robot, we have to adapt the ground conditions with a foot motion and maintain motion, and ensure its stability through the kinematics and dynamics analysis. But its mathematic model is not too easy. In this paper, in order to ensure the dynamic stability of a biped robot, we design the fuzzy model and confirm the realization possibility of the proposed method through some simulations.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.438-442
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• 2003

For an efficient sliding mode control system stability and chattering avoidance should be guaranteed. A continuation method using boundary layer is well known as one solution for this. However since not only model uncertainties and disturbances but also control task itself is variable. it is practically impossible to set controller parameters - control discontinuity, control bandwidth, boundary layer thickness - in advance. In this paper first an adaptation law of control discontinuity is introduced to assure system stability and then fuzzy logic based tuning algorithm of design parameters is applied based on monitored performance indices of tracking error, control chattering, and model precision. In the end maximum control bandwidth not exciting unmodeled dynamics and minimum control discontinuity, boundary layer thickness making system stable and free of chattering are found respectively. This eliminates control chattering and enhances control accuracy as much as possible under given control situation. In order to demonstrate the validity of the proposed algorithm safe headway maintenance control for autonomous transportation system is simulated. The control results show that the proposed algorithm guarantees system stability all the time and tunes control parameters consistently and in consequence implements an efficient control in terms of both accuracy and actuator chattering.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.50-55
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• 2016

This paper discusses a sampled-data controller design problem for nonlinear systems including singular perturbation. The concerned system is assumed to be modeled in Takagi--Sugeno (T--S) form. By introducing a novel Lyapunov function and an identity equation, the stability of the sampled-data closed-loop dynamics of the singularly perturbed T--S fuzzy system is analyzed. The design condition is represented in terms of linear matrix inequalities. A few discussions on the development are made that propose future research topics. Numerical simulation shows the effectiveness of the proposed method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.428-433
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• 1997

This paper presents a new control strategy for the position and force control of flexible manipulators. The governing equation of motion of a two-link flexible manipulator which features piezoceramic actuators bonded on each flexible beam is derived via Hamilton's principle. The control torque of the motor to command desired position and force is determined by a sliding mode controller on the basis of the rigid-mode dynamics. In the controller formulation, the sliding mode controller with perturbation estimation(SMCPE) is adopted to determine appropriate control gains. The SMCPE is then incorporated with the fuzzy technique to mitigate inherent chattering problem while maintaining the stability of the system. A set of fuzzy parameters and control rules are obtained from a relation between estimated perturbation and actual perturbation. During the commanded motion, undesirable oscillation is actively suppressed by applying feedback control voltages to the piezoceramic actuators. These feedback voltages are also determined by the SMCPE. Consequently, accurate force and position control of a two-link flexible manipulator are achieved. Computer simulations are undertaken in order to demonstrate the effectiveness of the proposed control methodology.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2192-2195
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• 2002

Even though, tanks are used at the many industry plants, it is very difficult to control the tank level without any overflow and shortage; moreover, cause of its complication of dynamics and nonlinearity, it's impossible to realize the accurate control using the mathematical model which can be applied to the various operation modes. However, the sliding mode controller(SMC) is known as having the robust variable structures for the nonlinear control systems with the parametric perturbations and with the sudden disturbances. It's difficult to find SMC's parameters, and SMC is bring chattering which injures actuator and increases error. In this paper, Genetic Aloglism based Fuzzy Sliding Mode Controller(GA-FSMC) for the precise control of the coupled tank level was proposed. Genetic Algolism and Fuzzy logic are adapted to find SMC's parameters and reduce the chattering. The simulation result is shown that the tank level could be satisfactorily controlled with less overshoot and steady-state error by the proposed GA-FSMC.

• Proceedings of the KIEE Conference
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• 2006.07b
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• pp.743-744
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• 2006

This paper is proposed an efficiency optimization control algorithm for a synchronous reluctance motor which minimizes the copper and iron losses. The design of the speed controller based on adaptive fuzzy-neural networks(AFNN) controller that is implemented using fuzzy control and neural networks. The proposed algorithm allows the electromagnetic losses in variable speed and torque drives to be reduced while keeping good torque control dynamics. The control performance of the hybrid artificial intelligent(HAI) controller is evaluated by analysis for various operating conditions. Analysis results are presented to show the validity of the proposed algorithm