International Journal of Robotics and Control Systems
International Journal of Robotics and Control Systems is open access and peer-reviewed international journal that invited academicians (students and lecturers), researchers, scientists, and engineers to exchange and disseminate their work, development, and contribution in the area of robotics and control technology systems experts. Its scope includes Industrial Robots, Humanoid Robot, Flying Robot, Mobile Robot, Proportional-Integral-Derivative (PID) Controller, Feedback Control, Linear Control (Compensator, State Feedback, Servo State Feedback, Observer, etc.), Nonlinear Control (Feedback Linearization, Sliding Mode Controller, Backstepping, etc.), Robust Control, Adaptive Control (Model Reference Adaptive Control, etc.), Geometry Control, Intelligent Control (Fuzzy Logic Controller (FLC), Neural Network Control), Power Electronic Control, Artificial Intelligence, Embedded Systems, Internet of Things (IoT) in Control and Robot, Network Control System, Controller Optimization (Linear Quadratic Regulator (LQR), Coefficient Diagram Method, Metaheuristic Algorithm, etc.), Modelling and Identification System.
Articles
361 Documents
<![CDATA[SDRE and LQR Controls Comparison Applied in High-Performance Aircraft in a Longitudinal Flight ]]>
<![CDATA[Guilherme P. Dos Santos]]>;
<![CDATA[Adriano Kossoski]]>;
<![CDATA[Jose M. Balthazar]]>;
<![CDATA[Angelo Marcelo Tusset]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 2 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i2.329
<![CDATA[This paper presents the design of the LQR (Linear Quadratic Regulator) and SDRE (State-Dependent Riccati Equation) controllers for the flight control of the F-8 Crusader aircraft considering the nonlinear model of longitudinal movement of the aircraft. Numerical results and analysis demonstrate that the designed controllers can lead to significant improvements in the aircraft's performance, ensuring stability in a large range of attack angle situations. When applied in flight conditions with an angle of attack above the stall situation and influenced by the gust model, it was demonstrated that the LQR and SDRE controllers were able to smooth the flight response maintaining conditions in balance for an angle of attack up to 56% above stall angle. However, for even more difficult situations, with angles of attack up to 76% above the stall angle, only the SDRE controller proved to be efficient and reliable in recovering the aircraft to its stable flight configuration.]]>
<![CDATA[The Path Direction Control System for Lanange Jagad Dance Robot Using the MPU6050 Gyroscope Sensor ]]>
<![CDATA[Ibnu Rifajar]]>;
<![CDATA[Abdul Fadlil]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 1 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i1.225
<![CDATA[The ability to walk straight on a dance robot is very important considering that in competitions, dance robots are required to be able to walk through several zones starting from the starting zone and ending with the closed zone. Therefore, a control system is needed in the Lanange Jagad dance robot so that the robot can control the direction of its walking motion and reduce errors in dance motion while walking on the dance robot. This control system uses a reading value based on the orientation of the rotating motion on the yaw angle axis on the MPU6050 gyroscope sensor which will later be used as a corrector for dance robots when performing various dance movements while walking in the competition arena. From the results of the overall test of the Lanange Jagad dance robot after adding the road direction control system, the percentage of the success rate in the battery power supply condition is 12 volts to 12.6 volts by 100% with the greater the battery power supply, the error in the robot's final angle average to The starting angle of the robot is getting smaller and the percentage of the success rate at the slope of the 0o to 4o race arena is 93.3%. With the tilted race arena, the error in the mean error of the robot's final angle to the starting angle of the robot is also greater, so it can be concluded that the robot can be controlled direction of walking and can walk straight to the finish in the closed zone.]]>
<![CDATA[An Adaptive Sliding Mode Control for Single Machine Infinite Bus System under Unknown Uncertainties ]]>
<![CDATA[Magdi Sadek Mahmoud]]>;
<![CDATA[Ali Alameer]]>;
<![CDATA[Mutaz M. Hamdan]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 3 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i3.351
<![CDATA[The inherent uncertainties in a Single Machine Infinite Bus System (SMIBS) are governed by unmodeled dynamics or large disturbances such as the system's faults. The existence of these uncertainties demands robust controllers to guarantee the system's asymptotic stability under such exacting conditions. In this work, we propose an Adaptive Sliding Mode Control (ASMC) design implemented on a fifth-order nonlinear SMIBS to handle those uncertainties without prior knowledge about its upper bounds. We develop the ASMC with gains of two nested adaptive layers to asymptotically stabilize the system's internal states, the machine's terminal voltage, and power angle within a region of unknown bounded uncertainties while mitigating the chattering phenomena associated with conventional Sliding Mode Control (SMC). To verify the design's effectiveness and prove the conducted Lyapunov theoretical stability analysis, we simulate the occurrence of a large disturbance represented by a 3-phase fault at the system's universal bus. The results show that the ASMC can successfully achieve asymptotic stable output errors and stabilizing the SMIBS internal states after the clearance of the fault. Moreover, the ASMC noticeably outperforms the SMC in chattering mitigation, where the ASMC's signal is significantly smoother than that of the SMC.]]>
<![CDATA[Multibody Modeling and Balance Control of a Reaction Wheel Inverted Pendulum Using LQR Controller ]]>
<![CDATA[Ümit Önen]]>;
<![CDATA[Abdullah Çakan]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 1 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i1.296
<![CDATA[In this study, modeling and LQR control of a reaction wheel inverted pendulum system is described. The reaction wheel inverted pendulum model is created by using a 3D CAD platform and exported to Simscape Multibody. The multibody model is linearized to derive a state-space representation. A LQR (Linear-quadratic regulator) controller is designed and applied for balance control of the pendulum. The results show that deriving a state-space representation from multibody is an easy and effective way to model dynamic systems and balance control of the reaction wheel inverted pendulum is successfully achieved by LQR controller. Results are given in the form of graphics.]]>
<![CDATA[Interval Type-2 Fuzzy Observers Applied in Biodegradation ]]>
<![CDATA[Marco Antonio Márquez-Vera]]>;
<![CDATA[Andrea Rodríguez-Romero]]>;
<![CDATA[Carlos Antonio Márquez-Vera]]>;
<![CDATA[Karla Refugio Ramos-Téllez]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 2 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i2.344
<![CDATA[There exist processes difficult to control because of the lack of inline sensors, as occurs in biotechnology engineering. Commonly the sensor is expensive, damaged, or even they do not exist. It is important to build an observer to have an approximation of the process output to have a closed-loop control. The biotechnological processes are nonlinear, thus in this work is proposed a fuzzy observer to endure nonlinearities. To improve the results reported in the literature, type-2 fuzzy logic was used to justify the membership functions used. The observer's gains were computed via LMIs to guarantee the observer's stability. To facilitate the fuzzy inference computation, interval type-2 fuzzy sets were implemented. The results obtained with the interval type-2 fuzzy observer were compared with a similar technique that uses a fuzzy sliding mode observer; this new approach gives better results obtaining an error 60% lower than the obtained with the other technique. They were designed three observers that work ensemble via a fuzzy relation. The best approximation was to estimate the intermediate concentration. It is important to know this variable because this sub-product was also toxic. It was concluding that by using the oxygen concentration and the liquid volume inside the reactor, the other concentrations were estimated. Finally, this result helps to design a fuzzy controller by using the estimated state. Using this approach, the estimation errors for the phenol and biomass concentrations were 49.26% and 21.27% lower than by using sliding modes.]]>
<![CDATA[Robot Operating System (ROS) in Quadcopter Flying Robot Using Telemetry System ]]>
<![CDATA[Mohammad Iqbalul Faiq Hatta]]>;
<![CDATA[Nuryono Satya Widodo]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 1 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i1.247
<![CDATA[In this study implementing odometry using RVIZ on a quadcopter flying robot that uses the Pixhawk Cube firmware version 3.6.8 as the sub-controller. Then the Lenovo G400 laptop as the main-controller as well as the Ground Control Station using the ubuntu 16.04 Linux operating system. The ROS platform uses the Kinetic and MAVROS versions as a quadcopter platform package using MAVlink communication with the telemetry module. The odometry system was tested using Rviz as navigation for Quadcopter movements in carrying out movements that follow movement patterns in certain shapes and perform basic robot movements. Data were collected using a standard measuring instrument inclinometer as a measurement of the slope of the robot and visualization RVIZ as a visual display of the odometric robot. The results of the research obtained are that the flying robot can maneuver according to the shape on the RVIZ according to the movements carried out directly at the airport, as well as the effect of the roll angle on the quadcopter (negative left roll, positive right) and the pitch angle on the quadcopter (negative forward pitch, the pitch returns positive).]]>
<![CDATA[Microcontroller Implementation, Chaos Control, Synchronization and Antisynchronization of Josephson Junction Model ]]>
<![CDATA[Rolande Tsapla Fotsa]]>;
<![CDATA[André Rodrigue Tchamda]]>;
<![CDATA[Alex Stephane Kemnang Tsafack]]>;
<![CDATA[Sifeu Takougang Kingni]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 2 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i2.354
<![CDATA[The microcontroller implementation, chaos control, synchronization, and antisynchronization of the nonlinear resistive-capacitive-inductive shunted Josephson junction (NRCISJJ) model are reported in this paper. The dynamical behavior of the NRCISJJ model is performed using phase portraits, and time series. The numerical simulation results reveal that the NRCISJJ model exhibits different shapes of hidden chaotic attractors by varying the parameters. The existence of different shapes of hidden chaotic attractors is confirmed by microcontroller results obtained from the microcontroller implementation of the NRCISJJ model. It is theoretically demonstrated that the two designed single controllers can suppress the hidden chaotic attractors found in the NRCISJJ model. Finally, the synchronization and antisynchronization of unidirectional coupled NRCISJJ models are studied by using the feedback control method. Thanks to the Routh Hurwitz stability criterion, the controllers are designed in order to control chaos in JJ models and achieved synchronization and antisynchronization between coupled NRCISJJ models. Numerical simulations are shown to clarify and confirm the control, synchronization, and antisynchronization.]]>
<![CDATA[Autonomous Fuzzy Heading Control for a Multi-Wheeled Combat Vehicle ]]>
<![CDATA[A. N. Ouda]]>;
<![CDATA[Amr Mohamed]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 1 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i1.286
<![CDATA[This paper introduces the design and the implementation of a heading angle tracking controller using fuzzy logic for a scaled Autonomous Multi-Wheeled Combat Vehicle (AMWCV) to navigate in outdoor environments. The challenge of designing this control system is to control the steering of the front four wheels individually to obtain the correct heading angle of the vehicle. The main contribution of the paper can be summarized in the fact that it is designing four fuzzy controllers for navigation and tracking the desired heading angle while at the same time while controlling the steering of the front four wheels individually. The AMWCV is capable of forwarding and backward movement where all eight wheels are powered individually. The different heading angles are used and simulated using MATLAB software to evaluate the performances of the developed algorithms. In addition, the performance of the developed controllers is validated in the presence of noise and disturbance in order to evaluate the robustness of the controller's Simulation results show the performances and demonstrate that the developed controllers are effective in predicting the desired heading angle changes.]]>
<![CDATA[An Adaptive Control for the Path Tracking of an Active Leg Prosthesis ]]>
<![CDATA[Rahma Boucetta]]>;
<![CDATA[Wiem Abdallah]]>;
<![CDATA[Saloua Bel Hadj Ali]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 2 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i2.350
<![CDATA[This paper presents an adaptive fuzzy-PID control strategy applied to an active lower limb prosthesis for trajectories tracking in normal walking, stairs climbing, and stairs descent. Trying to imitate a natural human limb, the prosthesis design challenges rehabilitating amputees to resume normal activities. A dynamic model of an ankle-knee active prosthesis is developed without ground reaction in a first case and introduces ground effect in a second one to ameliorate prothesis performances. The obtained models are used to synthesize a control strategy based on TS fuzzy concepts and PID control to reproduce human lower limb behavior in a normal gait and climb and descent of stairs. The RSME errors are calculated to evaluate and compare the various results performances and eventually show the capacity of the proposed control with ground reaction impact on trajectory tracking. The RMSE values obtained for the four outputs of the fuzzy controller are very small for the different modes of locomotion. Moreover, they become weaker when the ground reaction forces are added to the model to show the role of these forces for the body equilibrium maintaining during the gait cycle. The developed approach ensured good trajectories tracking compared to a healthy leg even in presence of disturbances.]]>
<![CDATA[Tuning of PID Controller Parameters with Genetic Algorithm Method on DC Motor ]]>
<![CDATA[Eka Widya Suseno]]>;
<![CDATA[Alfian Ma'arif]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 1 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i1.249
<![CDATA[Proportional Integral Derivative (PID) controllers are used in general to control a system, for example a DC motor system. The difficulty of using the controller is parameter tuning, because the tuning parameters still use the trial and error method to find the PID parameter constants, namely Proportional Gain (KP), Integral Gain (KI) and Derivative Gain (KD). In this case, the genetic algorithm method is used which can give better results in each iteration. Genetic algorithms are one of the smart methods inspired by the process of natural selection, the process that causes biological evolution, this concept is applied to tuning PID parameters. This research uses the Matlab simulation method and applies the simulation results to the DC motor hardware using the Arduino Uno. The genetic algorithm method gives a system that has a better steady time and a smaller maximum spike than the Trial and Error method. The test process produced the two best data with an overshoot value = 2, settling time = 13.5 and rise time of 2.7872 and the PID parameter value for mutation of 1 was KP = 3.7500; KI = 1.3184 and KD = 0.2051. Then the value of the best PID parameter on Crossover is 0.4, which is KP = 4.2090; KI = 1.2012 and KD = 0.2539 with an overshoot value = 2, settling time = 18 and rise time = 2.6462.]]>
