• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.3
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• pp.171-180
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• 2014

In this paper, a multiple sliding surface (MSS) controller for a twin rotor multi-input-multioutput system (TRMS) with mismatched model uncertainties is proposed. The nonlinear terms in the model are regarded as model uncertainties, which do not satisfy the standard matching condition, and an MSS control technique is adopted to overcome them. In order to control the position of the TRMS, the system dynamics are pseudo-decomposed into horizontal and vertical subsystems, and two MSSs are separately designed for each subsystem. The stability of the TRMS with the proposed controller is guaranteed by the Lyapunov stability theory. Some simulation results are given to verify the proposed scheme, and the real time performances of the TRMS with the MSS controller show the effectiveness of the proposed controller.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.12
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• pp.782-790
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• 2011

Typical temperature control methods of a cooler for machine tools are hot-gas bypass and compressor variable speed control. The hot-gas bypass system has been widely used to control the cooler temperature in many general industrial fields. On the contrary, the compressor variable speed control is focused on special fields such as aerospace and high precision machine tools which need high precision control. The variable speed control system usually has two control variables such as target temperature and superheat. In other words, the variable speed control system is basically multi-input multi-output(MIMO) system. In spite of MIMO system, the proportional integral derivative(PID) feedback control methodology that based on single-input single-output (SISO) system is generally used for designing the variable speed control system. Therefore, it is inevitable to describe transfer functions for dynamic behaviors of every controlled variables and decide the PID gains with tremendous iteration process. Moreover, the designed PID gains do not provide optimum system performances. To solve these problems, high performance controller design method based on a state space model is suggested in this paper. An optimum controller is designed to minimize both control errors and energy inputs. This method was more simple to describe dynamic behaviors and easier to design the cooler controller which is MIMO system.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.12
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• pp.579-587
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• 2014

This paper deals with precise analytical state equation modeling of a variable speed refrigeration system (VSRS) for optimum control in state space. The VSRS is described as multi-input and multi-output (MIMO) system, which has two controlled variables and two control inputs. First, the Navier-Stokes equation and mass flow rate were applied to each component of the basic refrigeration cycle to build a dynamic model. The dynamic model, represented by a differential equation, was transformed into the state equation formula. Next, a full-order state observer was built to estimate all of the state variables to compose an optimum control system. Then, an optimum controller was designed to minimize an evaluation function that has input energy and control error. Finally, simulations and experiments were conducted to verify the validity of the proposed modeling and designed optimum controller to regulate target temperature and superheat in a 1RT oil cooler system. The results show that the proposed method, state equation modeling and optimum control, is efficient to ensure optimal control performance of the VSRS.