Common Noninteracting Control with Simultaneous Common Partial Zeroing with Application to a Tracked UGV

In several MIMO system applications, the deviations of some output performance variables from their nominal values are required to be controlled independently, while the other performance variables are required to remain at their nominal value. This problem, named noninteracting control with simultaneous partial output zeroing, is important in the case of the common design of multi-model systems. To this end, the problem of a common noninteracting control with simultaneous common partial output zeroing is formulated. The present paper aims to develop a solution to the problem of multi-model normal linear time-invariant systems via regular and static measurement output feedback. The present approach follows the method developed for the solution of the common I/O decoupling problem. The main results of the paper are the introduction and the formulation of the problem at hand, the establishment of the necessary and sufficient conditions for its solvability, and the derivation of the respective general solution of the controller matrices. For the resulting closed-loop system, the additional design requirement of approximate command following a simultaneous I/O stabilizability is studied using a composite norm 2 type cost function and a metaheuristic algorithm for the derivation of the free parameters of the controller. The present results are illustrated through a numerical example of a nonlinear process with two operating points. Moreover, all the above results are successfully applied to the two-model description of a robot-tracked UGV, using a common controller feeding back measurements of the motor currents and the orientation of the vehicle

A Distributed Supervisor Architecture for a General Wafer Production System

The current trend in the wafer production industry is to expand the production chain with more production stations, more buffers, and robots. The goal of the present paper is to develop a distributed control architecture to face this challenge by controlling wafer industrial units in a general production chain, with a parametric number of production stations, one robot per two stations where each robot serves its two adjacent production stations, and one additional robot serving a parametric number of stations. The control architecture is analyzed for individual control units, one per robot, monitoring appropriate event signals from the control units of the adjacent robots. Each control unit is further analyzed to individual supervisors. In the present paper, a modular parametric discrete event model with respect to the number of production stations, the number of buffers, and the number of robotic manipulators is developed. A set of specifications for the total system is proposed in the form of rules. The specifications are translated and decomposed to a set of local regular languages for each robotic manipulator. The distributed supervisory control architecture is developed based on the local regular languages, where a set of local supervisors are designed for each robotic manipulator. The desired performance of the total manufacturing system, the realizability, and the nonblocking property of the proposed architecture is guaranteed. Finally, implementation issues are tackled, and the complexity of the distributed architecture is determined in a parametric formula. Overall, the contribution of the present paper is the development of a parametric model of the wafer manufacturing systems and the development of a parametric distributed supervisory control architecture. The present results provide a ready-to-hand solution for the continuously expanding wafer production industry

A Two Stage Nonlinear I/O Decoupling and Partially Wireless Controller for Differential Drive Mobile Robots

Differential drive mobile robots, being widely used in several industrial and domestic applications, are increasingly demanding when concerning precision and satisfactory maneuverability. In the present paper, the problem of independently controlling the velocity and orientation angle of a differential drive mobile robot is investigated by developing an appropriate two stage nonlinear controller embedded on board and also by using the measurements of the speed and accelerator of the two wheels, as well as taking remote measurements of the orientation angle and its rate. The model of the system is presented in a nonlinear state space form that includes unknown additive terms arising from external disturbances and actuator faults. Based on the nonlinear model of the system, the respective I/O relation is derived, and a two-stage nonlinear measurable output feedback controller, analyzed into an internal and an external controller, is designed. The internal controller aims to produce a decoupled inner closed-loop system of linear form, regulating the linear velocity and angular velocity of the mobile robot independently. The internal controller is of the nonlinear PD type and uses real time measurements of the angular velocities of the active wheels of the vehicle, as well as the respective accelerations. The external controller aims toward the regulation of the orientation angle of the vehicle. It is of a linear, delayed PD feedback form, offering feedback from the remote measurements of the orientation angle and angular velocity of the vehicle, which are transmitted to the controller through a wireless network. Analytic formulae are derived for the parameters of the external controller to ensure the stability of the closed-loop system, even in the presence of the wireless transmission delays, as well as asymptotic command following for the orientation angle. To compensate for measurement noise, external disturbances, and actuator faults, a metaheuristic algorithm is proposed to evaluate the remaining free controller parameters. The performance of the proposed control scheme is evaluated through a series of computational experiments, demonstrating satisfactory behavior

Supervisor Design for a Pressurized Reactor Unit in the Presence of Sensor and Actuator Faults

The preservation of the efficient functionality of a pressurized reactor unit in the presence of faults is the aim of the present paper. To satisfy this aim, a distributed supervisory control scheme, considering the possibility of system faults, was designed. Towards this aim, the models of the subsystems of the total pressurized reactor unit in the presence of sensor and actuator faults are developed, using finite deterministic automata. This is the first contribution of the paper. The desired performance of the unit was formulated in the form of rules guaranteeing the desired behavior of a pressurize–depressurize cycle and safety specifications. The rules were translated to six desired regular languages. The realization of these languages, in the form of supervisor automata, was accomplished. This is the second contribution of the paper. A modular supervisory design scheme, towards safety and tolerance in the presence of faults, was proposed and realized, and the properties of the proposed supervisors and the controlled automaton were proven. This is the third contribution of the paper. The complexity of each supervisor was computed. The efficiency of the supervisory design scheme was illustrated through simulations. A PLC implementation of the derived supervisors was proposed. The derived supervisors are suitable for implementation as function blocks

Robust PID Controller for a Pneumatic Actuator

In this paper the position control pneumatic actuator using a robust PID controller is presented. The parameters of the PID controller are computed using a Hurwitz invariability technique enriched with a Simulated Annealing Algorithm. The nonlinear model involves uncertain parameters due to linearization of the servo valve, variations of the initial volume of the cylinder and variation of the external load. The problem is proven to be solvable and the controller parameters are chosen to provide a suboptimal solution for tracking error minimization. Simulation results are presented for the nonlinear model

Robust PID Controller for a Pneumatic Actuator

In this paper the position control pneumatic actuator using a robust PID controller is presented. The parameters of the PID controller are computed using a Hurwitz invariability technique enriched with a Simulated Annealing Algorithm. The nonlinear model involves uncertain parameters due to linearization of the servo valve, variations of the initial volume of the cylinder and variation of the external load. The problem is proven to be solvable and the controller parameters are chosen to provide a suboptimal solution for tracking error minimization. Simulation results are presented for the nonlinear model

Modular Supervisory Control for the Coordination of a Manufacturing Cell with Observable Faults

In the present paper, a manufacturing cell in the presence of faults, coming from the devices of the process, is considered. The modular modeling of the subsystems of the cell is accomplished using of appropriate finite deterministic automata. The desired functionality of the cell as well as appropriate safety specifications are formulated as eleven desired languages. The desired languages are expressed as regular expressions in analytic forms. The languages are realized in the form of appropriate general type supervisor forms. Using these forms, a modular supervisory design scheme is accomplished providing satisfactory performance in the presence of faults as well guaranteeing the safety requirements. The aim of the present supervisor control scheme is to achieve tolerance of basic characteristics of the process coordination to upper-level faults, despite the presence of low-level faults in the devices of the process. The complexity of the supervisor scheme is computed

Metaheuristic Procedures for the Determination of a Bank of Switching Observers toward Soft Sensor Design with Application to an Alcoholic Fermentation Process

The present work focused on the development of soft sensors for single-input single-output (SISO) nonlinear dynamic systems with unknown physical parameters using a switching observer design. Toward the development of more accurate soft sensors, as compared with hard sensors, an extended design methodology for the determination of a bank of operating points satisfying the dense web principle was proposed, where for the determination of the bank of operating points and the observer parameters, a metaheuristic procedure was developed. To validate the results of the metaheuristic algorithm, the case of an alcoholic fermentation process was studied as a special case of the present approach. For the nonlinear model of the process, an observer-based soft sensor was developed using the metaheuristic procedure. First, the accuracy of the linear approximant of the process with respect to the original nonlinear model was investigated. Second, the I/O reconstructability of the linear approximant was verified. Third, based on the linear approximant, an observer was designed for the estimation of the non-measurable variable. Fourth, considering that the observer is designed upon the linear approximant, the linear approximant model parameters are derived through identification, for different operating points, upon the nonlinear model. Fifth, the observers corresponding to the different operating points, constitute a bank of observers. The design was completed using a data-driven rule-based system, performing stepwise switching between the observers of the bank. The efficiency of the proposed metaheuristic algorithm and the performance of the switching scheme were demonstrated through a series of computational experiments, where it was observed that the herein-proposed approach was more than two orders of magnitude more accurate than traditional single-step approaches of transition from one operating point to another

Power Supply Technologies for Drones and Machine Vision Applications: A Comparative Analysis and Future Trends

The field of Unmanned Aerial Vehicles (UAVs), or drones, is encountering quick development in the areas of air transportation and computerization. Progress in innovation has prompted more noteworthy capacities and highlights in UAVs, which are currently broadly involved by the military and flying industry for an assortment of high-end generally safe errands. Highly advanced UAVs that can be controlled remotely via a controller, mobile phone, or ground station cockpit have been developed through the integration of automation technology and machine vision, which includes thermal imaging, cameras, sensors, and other sensors. The three primary characteristics of UAVs will be investigated in this study, namely power-source technology, deep-learning neural networks for computer vision, and some of the applications that are used the most. The goal is to thoroughly examine these characteristics and offer suggestions for addressing some of the difficulties of optimizing UAV performance and also exploring potential future trends