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[Enhanced Sliding Mode Control for a Nonlinear Active Suspension Full Car Model ]]>
<![CDATA[Erliana Samsuria]]>;
<![CDATA[Yahaya M. Sam]]>;
<![CDATA[Fazilah Hassan]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 4 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i4.473
<![CDATA[This paper delivers findings on optimal robust control studies of nonlinear full car models. A nonlinear active suspension full car model is used, which considers the dynamic of a hydraulic actuator. The investigation on the benefit of using Sliding Mode Control (SMC) structure for the effective trade-off between road handling. The design of SMC in the chassis/internal subsystem is enhanced by modifying a sliding surface based on Proportional-Integral-Derivatives (PID) with the utilization of particle swarm optimization (PSO) algorithm in obtaining the best optimum value of control parameters. The switching control is designed through the Lyapunov function, which includes the boundedness of uncertainties in sprung masses that can guarantee the stability of the control design. The responses of the proposed controller have improved the disturbance rejection up to 60% as compared to the conventional SMC controller design and shown the high robustness to resist the effect of varying the parameter with minimal output deviations. The study proved that the proposed SMC scheme offers an overall effective performance in full car active suspension control to perform a better ride comfort as well as the road handling ability while maintaining a restriction of suspension travel. An intensive computer simulation (MATLAB Simulink) has been carried out to evaluate the effectiveness of the proposed control algorithm under various road surface conditions.]]>
<![CDATA[Turning Point and Free Segments Strategies for Navigation of Wheeled Mobile Robot ]]>
<![CDATA[Imen Hassani]]>;
<![CDATA[Islem Ergui]]>;
<![CDATA[Chokri Rekik]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 1 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i1.586
<![CDATA[The basic idea of the developed work is to solve the problem of mobile robot navigation with obstacle avoidance and the trajectory tracking problem in simple and complex environments. The research contribution aims to develop a strategy of navigation based on the turning point and the free segments algorithms. Indeed, a turning point method is developed in order to solve the problem of navigation in a simple environment. Then, the free segments approach is applied in order to solve the problem of obstacle avoidance in a complex environment. The second part of this paper aims to solve the problem of trajectory tracking. For this reason, a sliding mode controller is proposed as a solution to control the stability of the mobile robot. Finally, some simulation results which are developed using Matlab software are given to prove the validity of the developed work.]]>
<![CDATA[Chaotic Particle Swarm Optimization for Solving Reactive Power Optimization Problem ]]>
<![CDATA[Omar Muhammed Neda]]>;
<![CDATA[Alfian Ma'arif]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 1, No 4 (2021) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v1i4.539
<![CDATA[The losses in electrical power systems are a great problem. Multiple methods have been utilized to decrease power losses in transmission lines. The proper adjusting of reactive power resources is one way to minimize the losses in any power system. Reactive Power Optimization (RPO) problem is a nonlinear and complex optimization problem and contains equality and inequality constraints. The RPO is highly essential in the operation and control of power systems. Therefore, the study concentrates on the Optimal Load Flow calculation in solving RPO problems. The Simple Particle Swarm Optimization (PSO) often falls into the local optima solution. To prevent this limitation and speed up the convergence for the Simple PSO algorithm, this study employed an improved hybrid algorithm based on Chaotic theory with PSO, called Chaotic PSO (CPSO) algorithm. Undeniably, this merging of chaotic theory in PSO algorithm can be an efficient method to slip very easily from local optima compared to Simple PSO algorithm due to remarkable behavior and high ability of the chaos. In this study, the CPSO algorithm was utilized as an optimization tool for solving the RPO problem; the main objective in this study is to decrease the power loss and enhance the voltage profile in the power system. The presented algorithm was tested on IEEE Node-14 system. The simulation implications for this system reveal that the CPSO algorithm provides the best results. It had a high ability to minimize transmission line losses and improve the system's voltage profile compared to the Simple PSO and other approaches in the literature.]]>
<![CDATA[Effect of Joints’ Configuration Change on the Effective Mass of the Robot ]]>
<![CDATA[Abdel-Nasser Sharkawy]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 1 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i1.564
<![CDATA[Effective mass of robot is considered of great significance in enhancing the safety of human-robot collaboration. In this paper, the effective mass of the robot is investigated using different joint configurations. This investigation is executed in two steps. In the first step, the position of each joint of the robot is changing alone, whereas the positions of the other joints of the robot are fixed and then the effective mass is determined. In the second step, the positions of all joints of the robot are changing together, and the effective mass of the robot is determined. From this process, the relation between the effective mass of the robot and the joint configurations can be presented. This analysis is implemented in MATLAB and using two collaborative robots; the first one is UR10e robot which is a 6-DOF robot and the second one is KUKA LBR iiwa 7 R800 robot which is a 7-DOF robot. The results from this simulation prove that the change in any joint position of the robot except the first and the last joint affect the effective mass of the robot. In addition, the change in all joints’ positions of the robot affect the effective mass. Effective mass can thus be considered as one of the criteria in optimizing the robot kinematics and configuration.]]>
<![CDATA[A Comparative Study of Nonlinear Control Schemes for Induction Motor Operation Improvement ]]>
<![CDATA[Yassine Zahraoui]]>;
<![CDATA[Mohamed Akherraz]]>;
<![CDATA[Alfian Ma’arif]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 1 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i1.521
<![CDATA[In the objective of improving the performance of induction motor operation and ensuring a robust control against different uncertainties and external disturbances, especially at low-speed regions, this research highlights the main features of two nonlinear control techniques. First, the control design is based on the backstepping approach (BSA) with integral action, and then the sliding mode control (SMC) theory. The BSA principle is to define successive causal relations in order to construct the control law in a recursive and systematic way. This allows overcoming the obstacle of the higher-order system's dimension. SMC is designed to drive and then constrain the system state to lie within a neighborhood of the switching surface, this provides very strong and inherent robustness to the resulting controllers. The main reason behind developing the nonlinear control techniques is to ensure a decoupled control of the machine. Besides, it guarantees the stability of the overall system by tracking the speed reference with the fewest static error. Moreover, as the sensorless control increases the reliability and decreases the cost of the control system, an extended Kalman filter is implemented to improve speed and flux observation. The simulations of all the discussed results have been obtained by MATLAB/Simulink.]]>
<![CDATA[Syngas Generation Process Simulation: A Comparative Study ]]>
<![CDATA[Reyner P. P. de Oliveira]]>;
<![CDATA[Maria E. K. Fuziki]]>;
<![CDATA[Priscila M. L. Z. Costa]]>;
<![CDATA[Angelo Marcelo Tusset]]>;
<![CDATA[Giane G. Lenzi]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 1 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i1.584
<![CDATA[Methane reforming processes are of great importance for both the reduction of this greenhouse gas concentration in the atmosphere and for hydrogen production for energetic or chemical synthesis purposes. The use of Biogas in substitution for methane in reforming processes still provides a solution for the recovery of organic waste capable of producing Biogas. However, an in-depth analysis of the advantages of this substitution from the point of view of process yield is still lacking. Thus, the main contribution of the present research is the focus given to the comparison between methane and biogas as a reactant for the dry and steam reforming processes. In this work, a computational comparison of syngas production processes was performed, considering the system within the open-loop control. The software Aspen Hysys was used based on the minimization of Gibbs free energy in equilibrium. The parameters studied were: molar ratio of reagents (1-5), temperature (600-1000 °C), and pressure (1-5 bar). Dry methane reforming and steam methane reforming units were simulated, as well as both units using Biogas as a methane source. The plant was built in the simulator, and the results obtained indicated that high values in the molar ratio of CO2/CH4, CO2/Biogas, H2O/CH4, and H2O/Biogas, high temperatures, and low pressures favor the maximum conversion of methane. The use of Biogas in replacement of pure methane in the reform process proved to be advantageous for favoring the synthesis gas production reaction, besides adding value to a residue.]]>
<![CDATA[MRAC Adaptive Control Design for an F15 Aircraft Pitch Angular Motion Using Dynamics Inversion and Fractional-Order Filtering ]]>
<![CDATA[Amani R. Ynineb]]>;
<![CDATA[Samir Ladaci]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 2 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i2.574
<![CDATA[This study proposes a fractional adaptive control scheme design for a longitudinal pitch angular motion control of a military F15 aircraft. The aircraft behavior will be forced to follow a chosen model reference in an MRAC (Model Reference Adaptive Control) configuration combined with dynamics inversion technique such that the transient response becomes invariant even in the presence of uncertainties or variations for a reference input by introducing a fractional-order transfer function pre-filter. Based on Lyapunov theory, the updating control law minimizes the error between the plant output and the model reference one. This controller is set in a cascade with a linear dynamic compensator. Simulation results on a military aircraft model with comparison to preceding results illustrate the effectiveness and the superiority of the proposed control strategy.]]>
<![CDATA[Using PV Fuzzy Tracking Algorithm to Charge Electric Vehicles ]]>
<![CDATA[Yao Lung Chuang]]>;
<![CDATA[Miguel Herrera]]>;
<![CDATA[Afshin Balal]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 2 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i2.636
<![CDATA[Due to the possible shortage of oil and gas, increasing the number of cars, global warming, air pollution, and outages, there is a special need for renewable energy sources and electric vehicles (EVs). The new battery-electric vehicles BEVs can be charged by the power grid. However, the existing fossil fuel power plant cannot provide enough power for this purpose, and the only choice is renewable energy sources (RECs). Comparing RECs, solar energy is abundant and accessible in any part of the world. Needless to state that a maximum power point tracking (MPPT) system is required in order to extract maximum power from solar modules. In this paper, a charging strategy is proposed via using a solar system, a boost converter, and a fuzzy tracking algorithm. The main research contribution of the presented paper is to charge an EV without putting stress on the power grid. The effectiveness of this approach is demonstrated by the MATLAB Simulink and LTSPICE results.]]>
<![CDATA[Coordinated Distributed Voltage Control Methods for Standalone Microgrids ]]>
<![CDATA[Awatef K. Ali]]>;
<![CDATA[MagdiSadek Mostafa Mahmoud]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 2 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i2.612
<![CDATA[A microgrid is a small-scale power grid comprising distributed generators (DGs), distributed storage systems, and loads. It will lose contribution from the main grid if it shifts to islanded mode due to pre-planned or unforeseen disturbances. To restore the terminal voltages of all the distributed generators to the reference value, this paper presents three coordinated secondary control strategies. First, motivated by the synchronization control theory of multiagent systems, a distributed control technique is developed where each of the DGs is considered an agent and they exchange information via a communication network. second, a two-level control technique is designed in which a global controller is employed to monitor the overall performance of the DGs by transmitting corrective signals to the local controllers of the agents. In this technique, all the communication is between the global controller and the local controllers without any direct communication between the agents. Third, decentralized control is provided in which each DG is separately controlled by its local controller that operates based on the local feedback measurements. Simulations are carried out on an islanded microgrid consisting of four DGs to illustrate our design approach.]]>
<![CDATA[Power Assist Rehabilitation Robot and Motion Intention Estimation ]]>
<![CDATA[Zulikha Ayomikun Adeola-Bello]]>;
<![CDATA[Norsinnira Zainul Azlan]]>
<![CDATA[ International Journal of Robotics and Control Systems Vol 2, No 2 (2022) ]]>
Publisher : <![CDATA[Association for Scientific Computing Electronics and Engineering (ASCEE) ]]>
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DOI: 10.31763/ijrcs.v2i2.650
<![CDATA[This article attempts to review papers on power assist rehabilitation robots, human motion intention, control laws, and estimation of power assist rehabilitation robots based on human motion intention in recent years. This paper presents the various ways in which human motion intention in rehabilitation can be estimated. This paper also elaborates on the control laws for the estimation of motion intention of the power assist rehabilitation robot. From the review, it has been found that the motion intention estimation method includes: Artificial Intelligence-based motion intention and Model-based motion intention estimation. The controllers include hybrid force/position control, EMG control, and adaptive control. Furthermore, Artificial Intelligence based motion intention estimation can be subdivided into Electromyography (EMG), Surface Electromyography (SEMG), Extreme Learning Machine (ELM), and Electromyography-based Admittance Control (EAC). Also, Model-based motion intention estimation can be subdivided into Impedance and Admittance control interaction. Having reviewed several papers, EAC and ELM are proposed for efficient motion intention estimation under artificial-based motion intention. In future works, Impedance and Admittance control methods are suggested under model-based motion intention for efficient estimation of motion intention of power assist rehabilitation robot. In addition, hybrid force/position control and adaptive control are suggested for the selection of control laws. The findings of this review paper can be used for developing an efficient power assist rehabilitation robot with motion intention to aid people with lower or upper limb impairment.]]>
