Improving the strategies employed to control robotic arms is of great importance because of the increase in their use in advanced supervisory control strategies, such as digital twins. The inverse kinematic (IK) control of manipulators requires an IK solution and an awareness of the singular configurations. This work presents a complete IK calculation system with singularity analysis for the UR5 robotic arm created by Universal Robots. For a specific robot pose, different angle solution sets are obtained, and one of these solution sets has to be selected to achieve movement continuity and avoid singularities. Two methods for this double purpose are proposed: one calculates all the solution possibilities, and the other obtains only one solution set by following a sequence of decisions and calculations clearly stated by a finite state machine (FSM). Both methods are effective in managing singularities. The FSM-based method complements the IK solution procedure with advantages in the number of computations and performance by producing results that would not lead the joints to move abruptly. The results prove that the presented methods select an IK solution that does not result in a singular configuration, and that most of the time, they lead to the same valid IK solution.

Virtual remote laboratories have already been successfully implemented in educational centers for practical learning of mechatronics and robotic systems. This article presents the development of a virtual articulated UR-type robot, designed as an educational tool that is suitable for programming and evaluating both the inverse kinematics control of the robot and the independent control of the robot joints. The 3D model of the virtual robot was developed in the Blender V2.79 software and uses the Modbus TCP industrial communication protocol for the communication to an external controller implemented in CoDeSys V3.5 software. The developed system allows the students to generate and test their own control algorithm for the robot joints with the visualization of the achieved performance in 3D and real time. Tailored control systems can be compared on the virtual robot. In this study, a novel technique for the joint position control based on an FSM is proposed and verified with the virtual UR5 robots to prove that the developed system is a suitable platform to teach and learn the inverse kinematics control and independent joint control of the UR5 robotic arm.

The peak demand or demand limit control is an important part of the actions that industries carry out to optimize their energy consumption and reduce the costs related to their electricity billing. Prioritized switching of multiple appliances is often needed in order to reduce demand and energy consumption during peak load periods. The present article describes a peak load limitation algorithm that estimates the optimal disconnection time for one or more electrical loads before the electric demand exceeds a preset limit. This algorithm uses parametric and variable load factors that vary dynamically depending on what loads are present at a given time. For its validation, a software-in-the-loop testbed was designed and developed, in which multiple electrical loads were simulated via LabVIEW software and connected to a PLC controller emulated through CODESYS software. In this environment, several test configurations were executed and evaluated to study the influence of variables such as the nominal power and the disconnection priority of loads in the algorithm output. The results showed that the control algorithm is effective for peak load limitation, the maximum demand value reached during simulations tests did not exceed the preset demand limit at any time interval. The performance of the algorithm could be improved when prioritizing the shutdown of loads with higher nominal power or when increasing the anticipation time used for the disconnection of the controllable loads.

Cyber–physical systems use digital twins to provide advanced monitoring and control functions, including self-diagnosis. The digital twin is often conceptualized as a 3D model, but mathematical models implemented in numerical simulations are required to reproduce the dynamical and functional characteristics of physical systems. In this work, a cyber–physical system scheme is proposed to monitor and diagnose failures. The virtual system, embedded at the supervisory control level, combines concepts from complex networks and hybrid automata to detect failures in the hardware components and in the execution of the sequential logic control. An automated storage and retrieval system is presented as a case study to show the applicability of the proposed scheme. The functional test and the obtained results validate the implemented system that is shown to be capable of fault diagnosis and location in real time. The online execution of the digital twin present several advantages for diagnosing multiple concurrent failures in sensors, actuators, and the control unit. This approach can be incorporate into diverse manufacturing systems.

This study explores the direct current (DC) motor load torquecalculation using an effective discretization of the motor dynamicsand the proper choice of sample time.

Power demand control is required at steelmaking plants and other energy intensive industrial plants where the electrical bills include high demand charges and are subject to demand limit contracts. This paper introduces a novel and simplified algorithm for the implementation of a power demand controller. The presented algorithm does not require a model of the electrical load since it is based on a geometrical approach for the estimation of the disconnection time of the controllable load and only requires the nominal power values and the load factors of both the total (full) load and the noncontrollable (base) load as parameters. The power demand control method presented is verified with a computational simulation, and precise control of the demand limit is achieved under random variations of the base and full loads. The proposed control algorithm is simpler than commercial methods and achieves a competitive performance. Simulation results show a better performance by calculating the disconnection times based on load parameters specified as mean values between the average and nominal powers of the full and base loads. Some considerations to tune‐up the load factor parameters are also discussed. The presented control method has been successfully implemented on industrial controllers in two steelmaking facilities in Mexico, having an electric arc furnace as controllable load in both cases. This novel demand control is adequate for industrial plants with electrical loads that can be disconnected without affecting the quality of the product and with minor impact on productivity.