Control Systems and Optimization Letters
Control Systems and Optimization Letters is an open-access journal offering authors the opportunity to publish in all fundamental and interdisciplinary areas of control and optimization, rapidly enabling a safe and sustainable interconnected human society. Control Systems and Optimization Letters accept scientifically sound and technically correct papers and provide valuable new knowledge to the mathematics and engineering communities. Theoretical work, experimental work, or case studies are all welcome. The journal also publishes survey papers. However, survey papers will be considered only with prior approval from the editor-in-chief and should provide additional insights into the topic surveyed rather than a mere compilation of known results. Topics on well-studied modern control and optimization methods, such as linear quadratic regulators, are within the scope of the journal. The Control Systems and Optimization Letters focus on control system development and solving problems using optimization algorithms to reach 17 Sustainable Development Goals (SDGs). The scope is linear control, nonlinear control, optimal control, adaptive control, robust control, geometry control, and intelligent control.
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<![CDATA[Ultimately Bounded TSK Fuzzy Management in Urban Traffic Stream Mechanism: Multi-Agent Modeling Approach ]]>
<![CDATA[Ghasemi, Reza]]>;
<![CDATA[Hazaveh, Negin Amiri]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.16
<![CDATA[In this paper, a novel control approach based on the selection of the type of traffic light and the period of the green phase to accomplish an optimum balance at intersections is proposed. This balance should be flexible to the static behavior of time, and randomness in a traffic situation, which the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control over the crash of cars. The proposed method was specifically investigated at the intersection through an appropriate timing of traffic lights by sampling a multi-agent system. It consists of a large numbers of intersections, each of which is considered as an independent agent that exchanges information with each other, and the stability of each agent is provided separately. The robustness against uncertainties, scalability, and stability of the closed-loop overall system are the main merits of the proposed methodology. The simulation results show that the fuzzy intelligent controller in this multi-factor system which is a TS fuzzy is more useful than scheduling in the fixed-time method and it reduces the lengths of vehicles queuing.]]>
<![CDATA[The Design of Rice Milling and Screening Systems Uses the DC Motor PID Method ]]>
<![CDATA[Cahya, Aulia Adi]]>;
<![CDATA[Puriyanto, Riky Dwi]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.2
<![CDATA[Rice is one of the staple foods of most Indonesian people, the processing of rice derived from rice plants goes through many stages, one of which is rice milling and sifting. This research aims to make it easier for farmers to do milling and screening, the system will utilize DC motor rotation which is suitable for application in milling and screening, this system also utilizes electrical energy obtained from sunlight so it is more efficient and environmentally friendly. The milling DC motor will use the PID method with a value of P=25, I=50 and D=5 with a setpoint of 250, while the winnowing motor will use a PWM setting of 200 with a voltage of 7.07 V and a motor RPM of 348. This study also has digital scales. which can easily find out the results in units of grams with a maximum capacity of 5,000 grams. The prototype of this rice grinder and sifter has a success rate of testing sensors and motors in the range of 50%, even though the milling results can be said to be less than optimal, the screening results can work according to function, as well as solar panels that can optimally provide power to move the actuators and sensors. sensors in this system.]]>
<![CDATA[Load Frequency Control of One and Two Areas Power System Using Grasshopper Optimization Based Fractional Order PID Controller ]]>
<![CDATA[Mohammed, A. S.]]>;
<![CDATA[Dodo, A.]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.12
<![CDATA[In this paper, grasshopper optimization based fractional order PID controller for load frequency control of single and multi-area power system is presented. It is paramount to minimize large frequency deviation in power system control. Large frequency deviation occurs when the parameter values of the various generating units of the power system like generators, turbine and governors keeps changing due to numerous on/off witching in the load side. As such, for a more realistic study, nonlinearities and boiler dynamics has been introduced into the power system design and measures also put in place to mitigate large frequency deviation. This is because large frequency deviation can damage equipment at the generation level and the consumer devices at the distribution level. Anti-windup control will then be used to compensate the effects of the nonlinearities. The gain of the FOPID controller will be optimized using grasshopper optimization algorithm and objective function for minimization is the Integral Square Error (ISE). The Errors to be minimized are the summation of frequency deviation, tie-line power deviation and the area control errors. Simulations were carried out on the designed power system using MATLAB/Simulink and results obtained show a significant improvement in mitigating frequency deviation. However, the proposed method took a longer time to balance the generated power and load demand. This is because the proposed method considers boiler dynamics and nonlinearities in the power system designed and results were compared with other designed method for power system without nonlinearities.]]>
<![CDATA[DC Motor Controller Using Full State Feedback ]]>
<![CDATA[Setiawan, Naufal Rahmat]]>;
<![CDATA[Ma'arif, Alfian]]>;
<![CDATA[Widodo, Nuryono Satya]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.3
<![CDATA[This paper discusses the implementation of a full state feedback control system on DC motors to stabilize the speed of DC motors and fight the disturbances given to DC motors. Modern controls such as full state feedback use 2 sensor inputs, namely the Hall effect speed sensor OH42E and the INA219 current sensor and use 3 parameters namely K1 (Constant 1), K2 (Constant 2), and KI (Integral Constant) in designing the controller, the goal is to get a good system response according to the desired design specifications. The test was carried out with a hardware-in-the-Loop (HIL) scheme which uses an Arduino microcontroller as a DC motor plant control device in the form of a control mathematical model entered in the Arduino IDE software and by trial and error to find the desired response value. The test results showed that at the values of K1=1, K2=1, KI=0.9, a stable system response was obtained with tr(s)=3, ts(s)=4, and Os(%)=7% The addition of an integral constant () value affects a short rising time but is inversely proportional to a high overshoot value as well. Varying the values of K1 and K2 as multipliers on the sensor values has an impact on the stability of the system response or oscillations. The stability of this system response indicates that full state feedback can be relied upon as a control system.]]>
<![CDATA[Extended Kalman Filter Design to Estimate the Attitude of the Nanosatellite System Using Magnetometer ]]>
<![CDATA[Silva, Carlos]]>;
<![CDATA[McKell, George]]>;
<![CDATA[Parker, Linda]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.13
<![CDATA[The problem of estimating nonlinear systems is an important issue in many engineering applications. One of these applications is in the nanosatellite for Vehicle-to-everything (V2X) communications, which is used to replace sensors in the event of failure or error. Therefore, the accuracy of pre-filter estimation is of great importance. To control the orientation of a satellite, it is important to estimate the attitude accurately. Time-series estimation is especially important in micro and nanosatellites, whose sensors are usually low-cost and have higher noise levels than high-end sensors. Also, the algorithms should be able to run on systems with very restricted computer power. In this paper, an overview of the algorithms used to determine the attitude of nanosatellites, and especially using only the magnetometer sensor, will be discussed. This paper aims to simulate a nanosatellite system to estimate the magnetic field derivative vector using only the magnetometer data with the desired accuracy. The estimated vectors in the pre-filter, along with the magnetometer sensor data, are used to estimate the attitude of the satellite. The estimation of the state vector consisting of the vector part of quaternion and the angular velocity vector is used for the control calculation. To evaluate the accuracy of this pre-filter, a comparison of the magnetometer vector estimator with the body sensor data has been used.]]>
<![CDATA[System Control Holding Position on Quadcopter Using GPS with Waypoint ]]>
<![CDATA[Widhianto, Trisno]]>;
<![CDATA[Yudhana, Anton]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.4
<![CDATA[This study designs an autonomous quadcopter system that can work in outdoor areas using a waypoint and quadcopter system so that it can fly without being controlled to complete a given mission with accuracy that has a low offside value. The tests carried out were divided into 3 tests using 3 different missions using Post Hold flight mode and a height of 5 m, on each mission there were 3 waypoints with each waypoint distance of 10 m which later on each waypoint would perform a Holding Position. at each waypoint point and see the error value generated based on the waypoint point by calculating the Latitude and Longitude values between the vehicle and the waypoint point so as to get the error value between the vehicle and the waypoint point and then make a comparison with measurements using a measuring instrument at each waypoint point in carrying out missions.]]>
<![CDATA[Artificial Neural Network Optimized Load Forecasting of Smartgrid using MATLAB ]]>
<![CDATA[Ganthia, Bibhu Prasad]]>;
<![CDATA[Mohanty, Monalisa]]>;
<![CDATA[Mohapatra, Sushree Shataroopa]]>;
<![CDATA[Pradhan, Rosalin]]>;
<![CDATA[Satapathy, Subhasmita]]>;
<![CDATA[Patra, Shilpa]]>;
<![CDATA[Pahadasingh, Sunita Pahadasingh]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.14
<![CDATA[The motivation behind the research is the requirement of error-free load prediction for the power industries in India to assist the planners in making important decisions on unit commitments, energy trading, system security reliability, and optimal reserve capacity. The objective is to produce a desktop version of a personal computer-based complete expert system that can be used to forecast the future load of a smart grid. Using MATLAB, we can provide adequate user interfaces in graphical user interfaces. This paper devotes a study of load forecasting in smart grids, a detailed study of the architecture and configuration of Artificial Neural Network (ANN), Mathematical modeling and implementation of ANN using MATLAB, and a detailed study of load forecasting using the backpropagation algorithm.]]>
<![CDATA[Irrigation Sluice Control System Using Algorithm Based DC Motor PID And Omron PLC ]]>
<![CDATA[Prastiyo, Duwi]]>;
<![CDATA[Aji, Wahyu Sapto]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.5
<![CDATA[Automatic control system or control system (control system) is a system that aims to control a process so that the output produced can be controlled so that no errors occur. Automatic control in a system is very necessary because not all can be controlled by humans with precision, so it is necessary to have a control system that can monitor at the same time as the desired command execution. This research is to design a prototype irrigation sluice control system using a potentiometer, PID algorithm, PLC OMRON CP1E NA20DR-A and DC PG 28 motor as actuator. This research was conducted at the system design stage, both in hardware design and software design. The results of the tests that have been done show that the PID works well, this can be known from the state of the Output Word value "0" if the value "SP = PV" while the Output Word value will be greater than zero if "SP PV". Data collection is carried out with a water level condition of 12 cm then to raise the water condition, then add water slowly, from the data obtained that shows the increase in water level at the potentiometer voltage is 0.116 V / cm.]]>
<![CDATA[Power System Stabilizer Design using Genetic Algorithms and Particle Swarm Optimization ]]>
<![CDATA[Eddine, Ghouraf Djamel]]>;
<![CDATA[Abdellatif, Naceri]]>;
<![CDATA[Abdelkader, Sayeh]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.15
<![CDATA[in this paper, Meta-heuristic techniques using genetic algorithms GA and particle swarm optimization PSO to tuning optimal design of power system stabilizer PSS proposed. This latter have been used for many years to add damping to electromechanical oscillations of power system, Based on this idea we have proposed multiobjective function composed with tow function, first maximize stability margin by increasing the damping factors while minimizing the real parts of the eigenvalues. Simulation results to comparative study between genetic algorithms and particle swarm optimization obtained by our realized graphical user interface (GUI) proved the efficiency of PSS optimized by genetic algorithms in comparison with Particle Swarm Optimization, showing stable system responses almost insensitive to large parameter variations and under different operating regime (under-excited, nominal and over excited regime).]]>
<![CDATA[DC Motor Rotary Speed Control with Arduino UNO Based PID Control ]]>
<![CDATA[Rikwan, Rikwan]]>;
<![CDATA[Ma'arif, Alfian]]>
<![CDATA[ Control Systems and Optimization Letters Vol 1, No 1 (2023) ]]>
Publisher : <![CDATA[Peneliti Teknologi Teknik Indonesia ]]>
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DOI: 10.59247/csol.v1i1.6
<![CDATA[Along with the development of the times, DC motors are often used in industrial equipment or household appliances, but in DC motors they often experience a decrease due to the given load, it requires a controller. This research uses PID (Proportional Derivative) controller. In this study, the DC motor can be controlled despite the load using the trial and error method. This study uses Arduino UNO software for testing using parameters Kp=1.5, Ki=0.87, Kd=0.27. parameter y is the parameter value Kp, Ki, Kd obtained from the system response according to the software used. the value of rise time = 0.9925 Tested, Time = 2.7368, Overshoot = 1.3333 and Steady State Error = 0]]>
