• Journal of Power Electronics
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• v.4 no.4
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• pp.217-227
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• 2004

A robust controller that combines the merits of the feed-back, feed-forward and model-following control for induction motor drives utilizing field orientation control is designed in this paper. The proposed controller is a two-degrees-of­freedom (2DOF) integral plus proportional & rate feedback (I-PD) speed controller combined with a model-following (2DOF I-PD MFC) speed controller. A systematic mathematical procedure is derived to find the parameters of the 2DOF I-PD MFC speed controller according to certain specifications for the drive system. Initially, we start with the I-PD feed­back controller design, then we add the feed-forward controller. These two controllers combine to form the 2DOF I-PD speed controller. To realize high dynamic performance for disturbance rejection and set point tracking characterisitics, a MFC controller is designed and added to the 2DOF I-PD controller. This combination is called a 2DOF I-PD MFC speed controller. We then study the effect of the 2DOF I-PD MFC speed controller on the performance of the drive system under different operating conditions. A computer simulation is also run to demonstrate the effectiveness of the proposed controller. The results verify that the proposed 2DOF I-PD MFC controller is more accurate and more reliable in the presence of load disturbance and motor parameter variations than a 2DOF I-PD controller without a MFC. Also, the proposed controller grants rapid and accurate responses to the reference model, regardless of whether a load disturbance is imposed or the induction machine parameters vary.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.3
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• pp.264-268
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• 2011

This paper presents a Takagi-Sugeno (T-S) type Fuzzy Logic Controller (FLC) with only 3 rules. The choice of parameters of FLC is very difficult job on design FLC. Therefore, the choice of appropriate linguistic variable is an important part of the design of fuzzy controller. However, since fuzzy controller is nonlinear, it is difficult to analyze mathematically the affection of the linguistic variable. So this choice is depend on the expert's experience and trial and error method. In this paper, we propose the method to choose the consequence linear equation's parameter of T-S type FLC. The parameters of consequence linear equations of FLC are tuned according to the system error that is the input of FLC. The full equation of T-S type FLC is presented and using this equation, the relation between output and parameters can represented. The parameters are tuned with gradient algorithm. The parameters are changed depending on output. The simulation results demonstrate the usefulness of this T-S type 3 rule fuzzy controller.

• International Journal of Naval Architecture and Ocean Engineering
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• v.11 no.1
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• pp.211-224
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• 2019

This paper deals with a nonlinear controller based on saturation functions with variable parameters for set-point regulation and trajectory tracking control of an Autonomous Underwater Vehicle (AUV). In many cases, saturation functions with constant parameters are used to limit the input signals generated by a classical PD (Proportional-Derivative) controller to avoid damaging the actuators; however this abrupt bounded harms the performance of the controller. We, therefore, propose to replace the conventional saturation function, with constant parameters, by a saturation function with variable parameters to limit the signals of a PD controller, which is the base of the nonlinear PD with gravitational/buoyancy compensation and the nonlinear PD + controllers that we propose in this paper. Consequently, the mathematical model is obtained, considering the featuring operation of the underwater vehicle LIRMIA 2, to do the stability analysis of the closed-loop system with the proposed nonlinear controllers using the Lyapunov arguments. The experimental results show the performance of an AUV (LIRMIA 2) for the depth control problems in the case of set-point regulation and trajectory tracking control.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.9
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• pp.839-845
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• 2013

A CSTR (Continuous Stirred Tank Reactor) is a highly nonlinear process with varying parameters during operation. Therefore, tuning of the controller and determining the transition policy of controller parameters are required to guarantee the best performance of the CSTR for overall operating regions. In this paper, a methodology employing the 2DOF (Two-Degree-of-Freedom) PID controller, the anti-windup technique and a fuzzy gain scheduler is presented for the temperature control of the CSTR. First, both a local model and an EA (Evolutionary Algorithm) are used to tune the optimal controller parameters at each operating region by minimizing the IAE (Integral of Absolute Error). Then, a set of controller parameters are expressed as functions of the gain scheduling variable. Those functions are implemented using a set of "if-then" fuzzy rules, which is of Sugeno's form. Simulation works for reference tracking, disturbance rejecting and noise rejecting performances show the feasibility of using the proposed method.

• Journal of Power Electronics
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• v.15 no.3
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• pp.763-774
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• 2015

This study investigates the inherent influence of a DC-link voltage controller on both DC-link voltage control and the compensation performance of a three-phase, four-wire shunt active power filter (APF). A nonlinear variable-parameter DC-link voltage controller is proposed to satisfy both the dynamic characteristic of DC-link voltage control and steady-state compensation performance. Unlike in the conventional fixed-parameter controller, the parameters in the proposed controller vary according to the difference between the actual and the reference DC-link voltages. The design procedures for the nonlinear voltage controller with variable parameters are determined and analyzed so that the proposed voltage controller can be designed accordingly. Representative simulation and experimental results for the three-phase, four-wire, center-spilt shunt APF verify the analysis findings, as well as the feasibility and effectiveness of the proposed DC-link voltage controller.

• Journal of Power Electronics
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• v.8 no.3
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• pp.210-216
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• 2008

This paper presents a classical speed controller (CSC) for vector controlled induction motors. The controller explores the use of a Fuzzy Logic controller in a classical form. The controller combines the advantages of the classical controller and the properties of intelligent controllers. The Fuzzy Logic controller idea is used to obtain the CSC output equation, whereby the CSC equation is based on the speed error and its change. The CSC parameters are calculated based on the motor mechanical equation and a predefined system performance. Once the CSC parameters are obtained, the defined speed performance can be achieved at all operating conditions. The application of the CSC to control the speed of a vector controlled induction motor is presented. Different induction motor ratings are used. Simulation results in all possible olperating conditions are presented. Results show that the CSC behaves as an expert controller to provide the predefined speed performance in all possible operating conditions. Based on the results obtained in this paper, the CSC is expected to become the ultimate solution for high-performance drives of the next generation.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.228-228
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• 2000

To deal with non-linearities and time-varying characteristics of hydraulic systems, in this paper, the neuro-fuzzy controller has been introduced. This controller does not require an accurate mathematical model for the nonlinear factor. In order to solve general fuzzy inference problems, the input membership function and fuzzy reasoning rules are used for determining the controller Parameters. These parameters are determined by using the learning algorithm. The control performance of the neuro-fuzzy controller is obtained through a series of experiments for the various types of input while applying disturbances to the cylinder. .and performance of this controller was compared with that of PID, PD controller. As a experimental result, it can be proven that the position tracking performance of the neuro-fuzzy is better than that of PID and PD controller.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.1
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• pp.22-30
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• 2001

This paper describes a neural network based fuzzy PID control scheme. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriated PID gains in nonlinear systems and systems with long time delay and so on. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based self tuning fuzzy PID controller of which output gains were adjusted automatically. The tuning parameters of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods. Then they were adjusted by using proposed neural network learning algorithm. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The experiment on the magnetic levitation system, which is known to be heavily nonlinear, showed the proposed controller's excellent performance.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.700-702
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• 2000

The new design methodology of a hybrid fuzzy controller by means of the genetic algorithms is presented. In fuzzy controller which has been widely applied and used. in order to construct the best fuzzy rules that include adjustment of fuzzy sets, a highly skilled techniques using trial and error are required. To deal with such a problem, first, a hybrid fuzzy controller(HFC) related to the optimal estimation of control parameters is proposed. The HFC combined a PID controller with a fuzzy controller concurrently produces the better output performance than any other controller from each control output in steady state and transient state. Second, a auto-tuning algorithms is presented to automatically improve the performance of hybrid fuzzy controller, utilizing the simplified reasoning method and genetic algorithms. In addition, to obtain scaling factors and PID Parameters of HFC using GA, three kinds of estimation modes such as basic, contraction, and expansion mode are effectively utilized. The HFCs are applied to the first-order second-order process with time-delay and DC motor Computer simulations are conducted at step input and the performances of systems are evaluated and also discussed from performance indices.

• Journal of Electrical Engineering and Technology
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• v.3 no.1
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• pp.135-142
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• 2008

This paper deals with the design of a robust PI controller for a vehicle suspension system. A method, which is related to computation of all stabilizing PI controllers, is applied to the vehicle suspension system in order to obtain optimum control between passenger comfort and driving performance. The PI controller parameters are calculated by plotting the stability boundary locus in the $(k_p,\;k_i)$-plane and illustrative results are presented. In reality, like all physical systems, the vehicle suspension system parameters contain uncertainty. Thus, the proposed method is also used to compute all the parameters of a PI controller that stabilize a vehicle suspension system with uncertain parameters.