Earticle

본 논문에서는 새로운 실시간 적응형 PID 온도제어 기법을 제안한다. 제어대상을 표현하는 모델을 도입하여 오버슈트가 발생하지 않도록 하는 기법이다. 오버슈트의 원인이 되는 과도한 적분을 막기 위해 적분 제어량이 실시간 으로 모델의 열손실을 추종하도록 적분 이득을 조정한다. 기본적으로 비례 제어는 오버슈트를 유발하지 않는다. PID 제어에서 오버슈트의 발생 원인은 적분에서 기인한다. 기존의 PID 제어는 적분이 비례 제어에 종속되고 게인이 상수 로 고정되었다. 그 결과 서로에게 부정합되는 두 이득을 적용하면 과도한 오버슈트가 발생할 수 있었다. 그러나 제안 하는 적응형 제어는 적분 제어량이 항상 열손실을 초과하지 않도록 능동적으로 오버슈트를 제거한다. 따라서 제안하는 기법에 따라 튜닝 실험이 필요 없는 적응형 PID 제어를 실현할 수 있다.

In this paper, we propose a new real-time adaptive PID temperature control technique. This is a technique that prevents overshoot by introducing a model that represents the control object. To prevent excessive integration that causes overshoot, integral control adjusts the integral gain to track the heat loss of the model in real time. In the conventional PID control, the integration was dependent on proportional control and the gain was fixed to a constant. As a result, applying two gains that mismatch each other could cause excessive overshoot. However, the proposed adaptive control actively eliminates overshoot so that the integral control amount does not always exceed the heat loss. The cause of overshoot in PID control is integration. Basically, proportional control does not cause overshoot. Therefore, according to the proposed technique, adaptive PID control without the need for tuning experiments can be realized.

The parameters’ adjustment of Control System is very complicated. Such as, the adjustment of voltage, temperature and liquid level, they have the characteristic of non-linear and mutation. The traditional PID control algorithm has the defect of overstrike and the low accuracy of adjustment, in order to improve the control performance of Control System, we proposed an improved intelligent PID algorithm for Control System parameters’ adjustment. First, we encode the three parameters of PID to a firefly position vector; then, find the optimal PID parameters by simulating the firefly population's food forage and mating behavior; last, adjusted the parameters of PID to intelligent control the Control System. We also using MATLAB toolbox to simulate the proposed algorithm, and give a group of contrast experiments about two control systems, the voltage adjustment and liquid level adjustment. The experiments' results show that contrast to the traditional PID parameters’ optimization algorithm, our improved algorithm can quick adjust the Control System along with less overshoot, the response time is faster and the system is more robust.

To improve the accuracy and reduce the response time of traditional gas regulator, a Proportional Integral Derivative (PID) neural network controller of electric gas regulator is proposed by combining conventional digital PID with neural network. And the parallel architecture of the PID neural network is implemented by using Field Programmable Gate Array (FPGA). The neural network is demonstrated in a closed loop system of electric gas regulator and the ideal system output can be obtained by using this improved neural network algorithm. Theoretical analysis and simulation results show that the PID neural network pressure controller based on FPGA can achieve faster response speed and higher control accuracy compared with those based on software, and be obvious to improve the efficiency and security of the electric gas regulator.

This paper presents a method for optimum tuning of Fractional PID controllers using PSO algorithm which have fractional or integer order transfer functions. Particle swarm optimization (PSO) is a robust stochastic optimization technique based on the movement and intelligence of swarm, applies the concept of social interaction to problem solving. The best parameters of Fractional-Order PID controller consist of proportional gain integral gain , fractional-order of integrator λ, derivative gain and fractional-order of differentiator μ can be determinate by using this technique. The proposed approach with defined cost function has a very easy implementation and ability of fast tuning of optimum fractional-order PID controllers parameters. From the comparison this technique with the other methods, its influence and efficiency are illustrated.

This paper presents a method of optimized PID parameter self-adapted ant colony algorithm with aberrance gene, based on ant colony algorithm. This method overcomes genetic algorithm’s defects of repeated iteration, slower solving efficiency, ordinary ant colony algorithm’s defects of slow convergence speed, easy to get stagnate, and low ability of full search. For a given system, the results of simulation experiments which compare to the result of Z-N optimization and evolution of genetic algorithm optimization and evolution of ant colony system optimization, it has more excellent performance in finding best solution and convergence, the PID parameters also have optimality, system possesses dynamic controlling and performance. The experiments show that this method has its practical value on controlling other objection and process.

This paper proposes a novel tuning approach for robust proportional-integral-derivative (PID) controller based on H∞ loop shaping synthesis in combination with gap metric and Particle Swarm Optimization (PSO) algorithm. Different from the traditional research, the controller is designed through the search region constrained by H∞ loop shaping synthesis and gap metric theorem. PSO algorithm is used for tuning the robust PID controller parameters based on the underlying constrained optimization problems without resolving complex arithmetical calculations. The control technique is applied for the robust controller design so as to get a low order structured controller and achieve robust performance and the ability of restraining disturbance. The simulation shows that the proposed method can character the set of all values of the controller parameters that guarantees the robust stability with any supposed accuracy and achieves favorable control performance for uncertain systems.

This article will mainly introduce the effective access to get the value of PID parameter, and the method of tuning PID parameters is studied from two aspects. To ensure the PID parameter value of the whole set is optimal, the controlled object must be given and the value of intelligent optimization algorithm also must be optimal. Then to compare and test the parameters, we can use the method of simulation and experiment. Research deep traditional Z-N method and PID structure control model, and preliminary parameter values of PID can be acquired by it. After that, an intelligent fusion optimization algorithm based on intelligent computation and simulation analysis is constructed, finally, we can use this method to tuning PID parameters’ value effectively.

In the process of freshwater fish farming in pond, the levels of dissolved oxygen must be monitored by creating a closed loop PID control system. But traditional PID controller has weak stability and slow response speed, because dissolved oxygen changes with delay. In this paper, a PID control algorithm with optimal Smith predictor is proposed, to eliminate negative effects caused by delay component. The result of experiment data indicates that the optimal algorithm can reduce settling time and overshoot, and has better robustness and disturbance rejection performance than traditional PID controller. Meanwhile, a hardware circuit design plan based on ARM Cortex-M3 embedded processor is supposed, which gets stronger performance than C51 MCU control system with traditional PID algorithm. The hardware selection and plan design realize high cost performance, it is valuable to small and medium freshwater aquaculture enterprises.

In the process of the rice germination, temperature control is the key. Due to the accelerating seed germination system belongs to a complex nonlinear, large time delay and multivariable, it is difficult to establish the exact mathematical relationship model. In order to solve this problem, in this paper, we established the model based on RBF neural network, and used genetic algorithm to optimize the parameters of the neural network. In order to realize the accurate control of temperature and ensure the quality of rice sprouting, Fuzzy-PID control method can adjusts the parameters of PID and effectively improve the uniform distribution of temperature in the germinating box. The 3D graphics of temperature distribution obtained by MATLAB can show effectiveness of the method. Finally, the control strategy and system model improving the rice budding rate and evenness of emergence, are verified by experimental verification.

본 논문에서는 PID 알고리즘을 이용하는 온도제어기의 가상적 튜닝 기법을 제안한다. 제어대상의 수학적 표현 을 이용하여 컴퓨터에서의 가상적 시뮬레이션을 활용하였다. 컴퓨터의 상세한 데이터 분석을 통하여 PID 알고리즘의 이득을 정확하게 구하는 기법을 도입하였고 기존의 실험적 튜닝 결과보다 우수한 성능을 검증하였다. 또한 실제의 제 어대상에서 실시하는 튜닝 실험을 대체하는 장점이 있어 시간적 공간적 제한이 전혀 없다. 제어대상을 실제 가동하는 튜닝 실험은 그 과정에서 나타나는 자세한 데이터를 확인할 수 없다. 실험의 정확성을 보장할 수 없으며 그 결과를 즉시 확인할 수도 없었다. 제안하는 기법을 통해 튜닝의 모든 과정을 컴퓨터에서 정확하게 확인할 수 있으며 발생하 는 문제의 원인도 분석할 수 있다.

In this paper, we propose a virtual tuning technique for a temperature controller using the PID algorithm. Virtual simulation on a computer was used using the mathematical expression of the control object. A technique for accurately calculating the gain of the PID algorithm was introduced through detailed computer data analysis, and superior performance compared to conventional experimental tuning results was verified. In addition, it has the advantage of replacing tuning experiments conducted on actual control subjects, so there are no temporal or spatial limitations. Tuning experiments that actually operate the control object do not show detailed data that appears during the process. The accuracy of the experiment could not be guaranteed, and the results could not be confirmed immediately. Through the proposed technique, the entire tuning process can be accurately checked on a computer and the cause of problems that occur can also be analyzed.

In this paper, we propose an adaptive PID controller using a cell-mediated immune response to improve a PID control performance. The proposed controller is based on the specific immune response of the biological immune system that is cell-mediated immunity. The immune system of organisms in the real body regulates the antibody and the T-cells to protect an attack from the foreign materials like virus, germ cells, and other antigens. It has similar characteristics that are the adaptation and robustness to overcome disturbances and to control the plant of engineering application. We first build a model of the T-cell regulated immune response mechanism and then designed an I-PID controller focusing on the T-cell regulated immune response of the biological immune system. We apply the proposed methodology to building structures to mitigate vibrations due to strong winds for evaluation of control performances. Through computer simulations, system responses are illustrated and additionally compared to traditional control approaches.

Based on the conventional PID algorithm and the adaptive PID (AD-PID) algorithm, a separate sampling adaptive PID (SSA-PID) algorithm is proposed to improve the transient response of digitally controlled DC-DC converters. The SSA-PID algorithm, which can be divided into an oversampled adaptive P (AD-P) control and an adaptive ID (AD-ID) control, adopts a higher sampling frequency for AD-P control and a conventional sampling frequency for AD-ID control. In addition, it can also adaptively adjust the PID parameters (i.e. $K_p$, $K_i$ and $K_d$) based on the system state. Simulation results show that the proposed algorithm has better line transient and load transient responses than the conventional PID and AD-PID algorithms. Compared with the conventional PID and AD-PID algorithms, the experimental results based on a FPGA indicate that the recovery time of the SSA-PID algorithm is reduced by 80% and 67% separately, and that overshoot is decreased by 33% and 12% for a 700mA load step. Moreover, the SSA-PID algorithm can achieve zero overshoot during startup.

선형 플랜트의 극한 이득과 주기를 찾기 위해 포화함수를 이용하여 자기 진동을 발생 시켰다. 포화함수 사용으로 극한이득과 주기의 정확성을 높였다. 발견한 극한 이득과 극한 주기는 PID 제어기 값을 구하는데 사용하였다. 정적인 부하 왜란 등이 있는 경우 비대칭 진동이 발생할 수 있다. 발생하는 비대칭 자기 진동을 분석하였고 분석결과로부터 극한 이득과 주기를 찾는 방법을 제안하였다.

We use the saturation nonlinear feedback element to generate self-oscillation in order to find an ultimate gain and period of linear plant. The use of saturation nonlinear feedback element can improve accuracy of an ultimate gain and period of unknown linear plant. An ultimate gain and period of linear plant can be used to tune a PID controller parameters. It is possible that an asymmetric oscillation can be occurred under the special circumstances such as with static load disturbance. We analyze an asymmetric self-oscillation. As the results of an analysis, we propose a method to find an ultimate gain and period of linear Plant under the asymmetric self-oscillation.

릴레이 대신 포화함수를 이용하여 선형 플랜트의 극한 이득과 주기를 결정하였다. 포화함수를 사용함으로서 플랜트의 고주파 성분을 감소 시켜 묘사함수 사용에 의한 극한이득과 주기 결정의 정확도를 증가시켰다. 또한 적절한 포화함수를 사용할 수 있는 간단한 절차를 기술하였으며 진동이 발생하지 않는 플랜트에 대해서 지연요소를 이용한 자동동조 방법을 제시하였다.

We use the slope bounded saturation nonlinear feedback element instead of relay to find ultimate gain and period of linear plant. Saturation nonlinear element reduces the high harmonics of plant output. The reduction of high harmonics improve the accuracy of describing function method used to find ultimate gain and period. We give a simple procedure to find ultimate gain and period with saturation nonlinear element. A PID controller design method with known time delay element is also given, which is very useful when oscillation is not occurred with nonlinear element.

In this paper, a control algorithm for a servo manipulator is focused on. A servo manipulator system has been developed for remotely handling radioactive materials in a hot cell. It is driven by servo motors. The torque from a servo motor is transferred through a reducer to the corresponding axis. The PID control algorithm is a simple and effective algorithm for such application. However, since friction degrades the algorithm's performance, friction has to be considered and compensated. The major aberrations are the positional tracking errors and the limit cycle. The authors have considered a switching term to a conventional PID algorithm to reduce the friction's effect. It has been tested by a hardware test.

In recent years, the remarkable development of communication network technology with the increasing demand of B-ISDN service helps the higg-speed ATM network to be applied a fully integrated global network. The considerable issue of high-speed communication network is a performance of service-link and stability of network queue. In this paper, we propose a feedback control algorithm and PID control method to improve the performance of service-link and stability of network queue and confirm upgraded traffic performance of the high-speed ATM network.

$\textbullet$ Abstract $\textbullet$ Introduction $\textbullet$ Liquid Level Control System $\textbullet$ Flow Ratio Control System $\textbullet$ Application of Lookup Table Technique $\textbullet$ Experimental Results $\textbullet$ Conclusion

An immune algorithm is a kind of evolutional computation strategies, which is developed in the basis of a real immune mechanism in the human body. Recently, scientific or engineering applications using this scheme are remarkably increased due to its significant ability in terms of adaptation and robustness for external disturbances. Particularly, this algorithm is efficient to search optimal parameters against complicated dynamic systems with uncertainty and perturbation. In this paper, we investigate an immune algorithm embedded Proportional Integral Derivate (called I-PID) control, in which an optimal parameter vector of the controller is determined offline by using a cell-mediated immune response of the immunized mechanism. For evaluation, we apply the proposed control to mitigation of vibrations for nonlinear structural systems, cased by external environment load such as winds and earthquakes. Comparing to traditional controls under same simulation scenarios, we demonstrate the innovation control is superior especially in robustness aspect.

This paper proposes a new method for tuning a linear quadratic - proportional integral derivative controller for second order systems to simultaneously meet the time and frequency domain design specifications. The suitable loop-shape of the controlled system and the desired step response are considered as specifications in the time and frequency domains, respectively. The weighting factors, Q and R of the LQ controller are determined by the algebraic Riccati equation with respect to the limiting behavior and target function matching. Numerical examples show the effectiveness of the proposed LQ-PID tuning method

This paper is concerned with the design of a predictive PID controller, which has similar features to the model-based predictive controller. A PID type control structure is defined which includes prediction of the outputs and the recalculation of new set points using the future set point data. The optimal values of the PID gains are pre-calculated using the values of gains calculated from an unconstrained generalized predictive control algorithm. Simulation studies demonstrate the performance of the proposed controller and the results are compared with generalized predictive controller and the results are compared with generalized predictive control solutions.