Development of PI controller for disc speed
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This paper discuss about the development of Proportional and Integral (PI) controller for disc speed by involving the disturbance at the feedback control. The effect of the disturbance to the disc speed system is eliminated by Proportional and Integral (PI) controller. The PI controller is tuned heuristically from the MATLAB/simulink at which integrated with the disc plant. The performance of the disc plant is analyzed in real-time. Based on the analysis in real-time, this paper shows that the performance of the PI controller with disturbance and without disturbance. The result with disturbance shows that the output response quite closes to the result without disturbance even though the overshoot is about 8 percent. By the way, the rise time and settling time of the disc speed with disturbance is reduced for the time less than 0.01 and 0.95 seconds each. From the results with and without disturbance, this paper concludes that the development of PI controller for this speed in simulation give less error about 0.02 compared to the real-time system.Keywords:
Overshoot (microwave communication)
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Electronic speed control
Rise time
Proportional control
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This paper uses the Ziegler-Nichols (Z-N) tuning method approach combined with adjustments of the Proportional-Integral-Derivative (PID) gain parameters to achieve satisfactory improvement in the open-loop Perturb-and-Observe (P&O) maximum power point tracking (MPPT) performance of a grid-connected solar photovoltaic (PV) system. Various modes of the PID control produced varied effects and improvements in performance compared to the open-loop response. The P-controller reduced the open-loop overshoot by 62.28 % and the settling time by 166 ms, but introduced ripples. The PI-controller also reduced the open-loop overshoot by 70.99 % and reduced settling time by 106 ms, but increased the rise time slightly over that of the P-controller. The PID-controller virtually eliminated the overshoot, reducing it from 35.06 % to 0.51 %, and also increased the system response time by 236 ms. The superiority of the PID controller is thus confirmed as it virtually eliminated the overshoots, connoting a significant reduction in losses. The settling times were also reduced, signifying a much faster system response.
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Optimal material level control in blending tank can be achieved through the use of a PID controller. However, the major challenges of PID controller are high overshoot and steady-state error, prolong settling time, and slow response which practically causes wastages and equipment downtime. Thus, in this work classical techniques were employed to tune PID controllers to achieve optimum performance of the blending tank level control. The mass balance principle was used to model level of the blending tank while Zigler-Nichols (ZN), Chien-Hrones-Reswick (CHR), and Cohen-Coon (CC) techniques were used to tune the PID controller for optimal performance. The performance of the simulated control schemes MATLAB/Simulink were evaluated using rise time, settling time, peak amplitude, and overshoot. The results revealed that the ZN-PID controller gave the lowest rise time of 2.11s, settling time of 14secs, and peak amplitude of 1.04 while the lowest overshoot of 0% was achieved by both CHR and CC-PID. It can be inferred that ZN-PID gives the best way of controlling the level of the blending tank.
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The purpose of this research is to design PID control on BLDC motors using 2 tuning methods, namely Cohen-Coon and Trial & Error. PID control of formula calculations with calculations in Simulink Matlab. From the simulation results shown in graphical form, the use of the PID control gives a better effect than the use of the P and PI controls. This can be seen in the comparison curve which shows the speed of the initial start process when using the PID control. In the Trial & Error method, the response value of the system to controller P is obtained, namely, rise time = 0.0151 s, settling time = 0.6 s, overshoot = 75.9%, peak time = 1.74 s, and time delay = 0.424 s. on the PI controller namely, rise time = 0.0148 s, settling time = 0.591 s, overshoot = 76.3%, peak time = 1.74 s, and time delay = 0.0416 s. on the PID controller namely, rise time = 0.0496 s, settling time = 0.55 s, overshoot = 44 %, peak time = 1.31 s, and time delay = 0.128 s. In the Cohen-Coon method, the response value of the system to controller P is obtained, namely, rise time = 0.0168 s, settling time = 0.575 s, overshoot = 73.3%, peak time = 1.71 s, and time delay = 0.0469 s. on the PI controller namely, rise time = 0.0573 s, settling time = 0.603 s, overshoot = 39.3%, peak time = 1.23 s, and time delay = 0.142 s. on the PID controller namely, rise time = 0.276 s, settling time = 0.658 s, overshoot = 2.42 %, peak time = 0.159 s, and time delay = 0.576 s. From the simulation results it is shown that the value for the Cohen-Coon tuning method is better than the Trial & Error method, perhaps because the input value for the Trial & Error method is larger.
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In this paper an optimized proportional plus integral plus derivative (PID) controller is designed to control the non-minimum phase systems (NMP) with delay. The problem associated with the NMP system is the undershoot behaviour of the system caused by zeros of the right half plane and it becomes trivial as delay increases. To improve the system performance the parameters of the PID controller are optimized using grey wolf optimizer (GWO). The GWO algorithm seeks to obtain the global optimal values of the PID controller in the region delineate by the conventional tuning criterion like Ziegler-Nichols (ZN) rule. The parameters are optimized on the basis of minimizing the integral absolute error (IAE) of the system. Simulation results prove that the proposed method advances the transient performance like settling time, rise time, peak time and overshoot of the system.
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The main purpose of this paper is to control the speed of a DC motor using two techniques, via PID Controller and Fuzzy Logic Controller (FLC). A system model is implemented for PID and FLC controllers along with a model for a DC motor using MATLAB Simulink. The performance of the two techniques is evaluated and compared in terms of the settling time (Ts) and maximum overshoot under different load conditions. PID controller is shown to give a good response and small rise time, but higher overshoot and settling time. Fuzzy Logic Controller is found to provide better performance as compared to PID controller in terms of settling time and percentage overshoot and a better control of the DC motor due to the fact that FLC required no tuning and human manipulations are reduced.
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Abstract In this paper, a simple design method is presented to adjust the parameters of a proportional-integral derivative PID controller to be applied to different systems. In this method, PID controller is designed based on setting the optimal proportional gain according to the desired performance (settling time, overshoot). Determining the other parameters of the PID controller by adjusting the optimum ratio gain (k p ) in a stable loop that minimizes the settling time (t s ) and the error rate of the overshoot (M p ) constitutes the basis of the method. The Routh Rurwitz criterion is used to guarantee stability. The performance of the controller designed with the proposed method has been evaluated on three different transfer functions. With this method, the PID controller works successfully without destroying parameters and without complex mathematical formulation. It has been observed that the proposed method provides better closed loop performance compared to the methods reported recently.
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In this paper an optimized fractional order proportional, integral and derivative (FOPID) controller is designed to control the non-minimum phase (NMP) systems with time delay. The NMP system shows the undershoot behavior because of having zeros in the right half plane and the response becomes sluggish as the time delay increases. For improving the performance of the NMP system an optimized FOPID controller is designed. The parameters of FOPID are optimized using Nelder's and Mead (NM) optimization Algorithm. NM-optimization seeks to obtain the best optimal values of the FOPID controller in the region. The parameters are optimized on the basis of minimizing the integral absolute error (IAE) of the system. Simulation results verify that the proposed controller improves the transient performance like rise time, settling time and overshoot of the system.
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Controlling the temperature of the glycerin purification process system was not an easy task, as an increase in operating temperature would significantly reduce the quality of the purified glycerin. This is because an unlimited increase in temperature beyond the set point and an excessive prolongation of the heating process would result in the formation of an excessive secondary oxidation product in the final purified glycerin. This paper discusses the transient response characteristics of the glycerin heating process using a parallel PID controller. The glycerin heating process behavior was determined experimentally using step input test and modelled as the First Order plus Delay Time. The controller parameters wereadjusted using Ziegler-Nichols, Cohen-Coon and Wang tuning methods, each of which was analyzed on the basis of the corresponding integral error criterion value. The Integral Square Error, Integral Absolute Error and Integral Time-weighted Absolute Error criteria value were used to evaluate the efficiency of the glycerin heating process. The transient response performances in terms of overshoot, rise time and settling time were also evaluated. Simulation work has shown that the process has experienced high overshoots for Ziegler-Nichols and Cohen-Coon, and has taken longer time to settle. Wang method exhibits with no overshoot but slow response. The lower gain PID controller was found to improve the process response in terms of overshoot but increase in the rise time and settling time. The results indicate that the desired process performance were more or less influenced by the interaction between the tuning parameters. The Ziegler-Nichols PID controller is not recommended for controlling glycerin heating process due to process response oscillations that are difficult to eliminate without prolonging the heating cycle.
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The purpose of this research is to design a PID control on a DC motor using 2 tuning methods, namely Trial & Error and Ziegler-Nichols. The results showed that the Pittman DC Motor system response from the Pittman DC motor was very unstable, in which there were still many oscillations and a very high overshoot value. In the Trial & Error method, the system response value was obtained on the P controller, namely, rise time = 0.000551 s, settling time = 0.00468 s, overshoot = 37.1 %, peak time = 0.972 s, and time delay = 0.00134 s. on the PI controller namely, rise time = 0.000396 s, settling time = 0.00534 s, overshoot = 47.7%, peak time = 1.23 s, and time delay = 0.00102 s. on the PID controller namely, rise time = 0.000223 s, settling time = 0.00502 s, overshoot = 64.6%, peak time = 1.54 s, and time delay = 0.000601 s. In the Ziegler-NIchols method, the response value of the system to the P controller is obtained, namely, rise time = 0.00118 s, settling time = 0.00564 s, overshoot = 15.4%, peak time = 0.178 s, and time delay = 0.00262 s. on the PI controller namely, rise time = 0.000275 s, settling time = 0.00531 s, overshoot = 58.3%, peak time = 1.44 s, and time delay = 0.000767 s. on the PID controller, namely, rise time = 0.00133 s, settling time = 0.00446 s, overshoot = 12.6 %, peak time = 0.0237 s, and time delay = 0.00288 s. The simulation results show that the value for the Ziegler-Nichols tuning method is better than the Trial & Error method, perhaps because the input value for the Trial & Error method is larger.
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