Design and simulation linear quadratic gaussian (LQG) for pan-tilt face tracking camera servos

Ramelan, Agus; Saputro, Joko Slamet; Apribowo, Chico Hermanu Brillianto; Ibrahim, Muhammad Hamka; Pramono, Subuh

doi:10.1063/5.0000614

Cited by 7 publications

(5 citation statements)

References 8 publications

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“…Some researchers use the first method (mathematically based) to get the system model such as in [17]- [20]. On the other hand, [15] and [10] use the second method by taking data from the input-output of the system to find the system model. In the first method, system parameters are required; therefore, it is not suitable for hardware implementation where no parameters of the system are ready.…”

Section: Materials and Methods A Mini Conveyor Modelmentioning

confidence: 99%

“…Kalman Filter is a state estimation model that can estimate state variables from the measurement which has noise. If the noise is of Gaussian type, then the error variation can be optimally minimized [15]. The process estimation is conducted by using a form of feedback control that can be in the form of noise measurement.…”

Section: B Lqg Control Designmentioning

confidence: 99%

“…One of them is LQG. According to [15] this method can minimize estimation errors and produce optimal control signals. The LQG control is the combination of LQR control with the Kalman Filter which works as an optimal estimation so that new measurements can be directly processed and reduce the estimated mean square error.…”

Section: Introductionmentioning

confidence: 99%

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Integral State Feedback Control Using Linear Quadratic Gaussian in DC-drive System

Praptodiyono¹,

Maghfiroh

Saputro

et al. 2021

J. Elektron. dan Telekomun.

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The electric motor is one of the technological developments which can support the production process. DC motor has some advantages compared to AC motor especially on the easier way to control its speed or position as well as its widely adjustable range. The main issue in the DC motor is controlling the angular speed with uncertainty and disturbance. The alternative solution of a control method with simple, easy to design, and implementable in a multi-input multi-output system is integral state feedback such as linear quadratic Gaussian (LQG). It is a combination between linear quadratic regulator and Kalman filter. One of the advantages of this method is the usage of fewer sensors compared with the original linear quadratic regulator method which uses sensors as many as the state in the system model. The design, simulation, and experimental study of the application of LQG as state feedback control in a DC-drive system have been done. Both performance and energy were analyzed and compared with conventional proportional integral derivative (PID). The gain of LQG was determined by trial whereas the PID gain is determined from MATLAB autotuning without fine-tuning. The load test and tracking test were carried out in the experiment. Both simulation and hardware tests showed the same result which LQG is superior in integral absolute error (IAE) by up to 74.37 % in loading test compared to PID. On the other side, LQG needs more energy, it consumes higher energy by 6.34 % in the load test.

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Section: Materials and Methods A Mini Conveyor Modelmentioning

confidence: 99%

Section: B Lqg Control Designmentioning

confidence: 99%

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Integral State Feedback Control Using Linear Quadratic Gaussian in DC-drive System

Praptodiyono¹,

Maghfiroh

Saputro

et al. 2021

J. Elektron. dan Telekomun.

Self Cite

View full text Add to dashboard Cite

show abstract

“…Some researchers used the first method (mathematically based), such as in [37], [38], [39]. Meanwhile, researchers in [16] and [40] used black-box modeling by analyzing input-output experimental data to find the system model.…”

Section: A Hardware System Designmentioning

confidence: 99%

Improved LQR Control Using PSO Optimization and Kalman Filter Estimator

et al. 2022

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The electric motor is a device that converts electrical power into mechanical power. The DC motor has some advantages compared to the AC motor on its easier way to control the speed or position and wide adjustable range. The alternative solution for a control method with simple, easy to design, and can be implemented in a multi-input multi-output system is the integral state feedback such as LQR. The weakness of LQR control is that there is no exact method to determine the best value of matrix Q and R used to calculate the state feedback gain. Therefore, it was chosen by trial (manually tuned). This paper proposed an improved LQR control using PSO optimization and the Kalman filter estimator. The PSO is used to find optimal Q and R value while the Kalman filter is used to reduce the number of sensors used to measure the system state. Both performance and energy consumption were compared by using IAE and total energy consumption. The simulation results showed that the proposed method is superior in performance and energy compared to manually tuned LQR. The hardware implementation proves that the proposed method has the smallest IAE, whereas the smallest energy is manually tuned LQR. The proposed method can reduce the IAE by 11.28% with 1% higher energy compared to manually tuned LQR.

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“…Some researchers use the first method to get the system model such as [28][29][30]. On the other hand, [31] and [32], use the second method by taking data from the input-output of the system to find the system model. In the first method, system parameters are required; therefore, it not suitable for hardware implementation where no parameters of the system are ready.…”

Section: B Lqg Designmentioning

confidence: 99%

Speed Control of Induction Motor using LQG

Maghfiroh

Iftadi

Sujono

2021

jrc

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The electric motor is one of the technological developments which can support the production process. Not only in the manufacturing, but also in the transportation sector. The AC motor is divided into the synchronous and asynchronous motor. One type of asynchronous motor which widely used is the induction motor. In this study, the application of the IFOC control method and the LQG speed control method will be used to control the speed of an induction motor. The PID algorithm is also used as a comparison. Tests were carried out using MATLAB software. The speed variation and load variation are tested to validate the controller performance. PID is superior in terms of settling time and IAE. On the other hand, LQG is better in energy consumption. In terms of IAE, LQG has a higher value compared to PID by up to 56.67%. On the other hand, LQG is superior in terms of energy, which is 8.38% more efficient.

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Design and simulation linear quadratic gaussian (LQG) for pan-tilt face tracking camera servos

Cited by 7 publications

References 8 publications

Integral State Feedback Control Using Linear Quadratic Gaussian in DC-drive System

Integral State Feedback Control Using Linear Quadratic Gaussian in DC-drive System

Improved LQR Control Using PSO Optimization and Kalman Filter Estimator

Speed Control of Induction Motor using LQG

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