• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.212-217
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• 2007

A new method of designing multi-loop PID controllers is presented in this paper. By using the generalized IMC-PID method for multi-loop systems, the optimization problem involved in finding the PID parameters is efficiently simplified to find the optimum closed-loop time constant in a reduced search space. A weighted sum Mp criterion is proposed as a performance cost function to cope with both the performance and robustness of a multi-loop control system. Several illustrative examples are included to demonstrate the improved performance of the multi-loop PID controllers obtained by the proposed design method.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.1
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• pp.77-82
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• 2010

An analytical method for robust design of the multi-loop proportional-integral (PI) controller is proposed for various types of multi-delay processes. On the basis of the direct synthesis and generalized IMC-PID approach, the analytical tuning rules of the multi-loop PI controller are firstly derived for achieving the desired closed-loop response, and the structured singular value synthesis is then utilized for the tradeoffs between the robust stability and performance by adjusting only one design parameter (i.e., the closed-loop time constant). To verify the superiority of the proposed method, the simulation studies have been conducted on a wide variety of multivariable processes. The multi-loop PI controller designed by the proposed method shows a fast, well-balanced and robust response with the minimum integral absolute error (IAE) in compared with other renowned methods.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.10
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• pp.1031-1036
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• 2015

Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.

• Journal of Electrical Engineering and Technology
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• v.12 no.1
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• pp.72-77
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• 2017

This paper proposes the explicit tuning rule of multi-loop PID controller for brushless direct current motors to predict the system behaviors in time and frequency domains, using properties of the convex combination method. The convex set of the proposed controllers formulates the envelope to satisfy the performances in time and frequency domains. The final control parameters are determined by solving the convex optimization problem subject to the constraints which are represented as convex set of time domain performances. The effectiveness of the proposed control method is shown in the numerical simulation, in which controller tuning algorithm and dynamics of brushless DC motor are well taken into account.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.3
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• pp.196-200
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• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used fur on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.2
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• pp.136-139
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• 2000

A neural controller for process control is proposed that combines a conventional multi-loop PID controller with a neural network. The concept of target signal based on feedback error is used for on-line learning of the neural network. This controller is applied to distillation column control to illustrate its effectiveness. The result shows that the proposed neural controller can cope well with disturbance, strong interactions, time delays without any prior knowledge of the process.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.478-484
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• 1990

An automatic tuning method of a PID controller which is used for single input single output processes is proposed. In the proposed tuning method, the frequency response data model is adopted along with the performance index which is an integral of time weighted square error between reference model and process frequency response data model for tuning. This method is easier to retune when either the process dynamics is changed or the reference model is changed. Finally, an example is provided to show the usefulness of the method.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.46-51
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• 2004

The problem of reducing the effect of an unknown disturbance on a dynamical system is one of the most fundamental issues in control design. We propose a robust PID (Proportional Integral Derivative) control method with neural network for improving the performance due to the rejection of an unknown disturbance. The proposed system consists of a model of the plant, a conventional PID controller and a multi-layer neural network, and is composed of two loop; the first loop enables the system to achieve stability of system, the second loop rejects an unknown disturbance. Simulation and experiment results show that the proposed method improves considerably on the performance of the conventional PID control method and the typical IMC method using neural network.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.584-589
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• 1994

A time-varying nonlinear mathematical model was derived to consider the effect of change in roll radius on tension varation during winding and unwinding. A variable-gain PID controller was designed for tension control at start and stop in a multi-span continuous process system. The controller gains are updated at every control loop as roll radii continuously change. Computer simulation was carried out by using the mathematical model and the controller developed for a typical operating condition including acceleration and deceleration. When the variable-gain PID controller was used, the tension control performance was improved compared with that of existing control method during start-up and stop.

• Journal of Navigation and Port Research
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• v.31 no.5 s.121
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• pp.325-332
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• 2007

This study develops a control algorithm on berthing/unberthing system using a joystick for ships with thrusters and a rudder. A nonlinear mathematical model for low speed maneuvering of typical container ships is used to develop a MIMO(multi-input multi-output) nonlinear control algorithm for velocity feedback joystick control. Also a virtual HILS(hardware in the loop simulation) software program for berthing/unberthing is developed to test the performance of the nonlinear and a PID control algorithm. The program is developed using LabWindow/CVI, and a user can see current position and desired trajectory of ship in a monitor, then he can control forward and yaw velocities of a ship using a joystick. The simulation results show that the nonlinear mfd the PID controller have superior performance over a simple open loop joystick control algorithm.