It represents a universally applicable attitude and skill set everyone, not just computer scientists, would be eager to learn and use.

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Computational Thinking 計算論的思考

Design of tracking controller for quadrotor is an important issue for many engineering fields such as COVID-19 epidemic prevention, intelligent agriculture, military photography and rescue nowadays. This study applies the feedback linearized method and linear quadratic regulator (LQR) method using particle swarm optimization (PSO) to analysis and stabilize the highly nonlinear quadrotor system without applying any nonlinear function approximator that includes neural network approach and fuzzy approach. The article proposes a new method based on the firstly proposed convergence rate formula to achieve the optimal weighting matrices of LQR such that the composite controller can reduce the amplitudes of system control inputs. Determination of the LQR tuning parameters is conventionally achieved via trial and error approach. In addition to being very troublesome, it is difficult to find the globally best tuning matrices with LQR method. This article firstly uses the convergence rate formula of the nonlinear system as the fitness function of LQR approach by using PSO to take the place of the trial and error method. The generalities and implications of proposed approach are globally valid, whereas the Jacobian linearized approach is locally valid due to the Taylor expansion theorem. In addition to these two major achievements, the significant innovation of the proposed method is to possess “simultaneously” additional performances including the almost disturbance decoupling, input amplitude reduction, tuning parameter optimization and globally exponential stability performances. Comparative examples show that the convergence rate with our proposed optimal controller using the PSO algorithm is larger than the fuzzy method, and better than the singular perturbation method with high-gain feedback.

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Feedback Linearized Optimal Control Design for Quadrotor With Multi-Performances

Soft error hardening enhancement analysis of NBTI tolerant Schmitt trigger circuit

The point of this paper is to illustration a speed Controller of a DC motor by decision of a PID parameters using Genetic Algorithm (GAs), the DC motor is widely used as a part of various applications, for example, steel plants, electric trains, cranes and significantly more. DC could be spoken to by a nonlinear model when nonlinearities, for example, interesting dissemination is considered. To give successful control, nonlinearities and instabilities in the model must be considered in the control plan. The DC motor is considered as third request framework. Target of this paper a arrange of tuning strategies for PID parameters. In this paper a freely invigorated DC motor using MATLAB showing, has been sketched out whose speed may be analyzed using the Proportional, Integral, Derivative (KP, KI , KD) expansion of the PID controller. Subsequent to, built up controllers PID are fail to control the drive when weight parameters be in like manner changed The standard purpose of this paper is to analyze the execution of Optimization procedures viz. The Genetic Algorithm (GA) for improve PID controllers parameters for speed control of DC and rundown their purposes of enthusiasm over the customary tuning techniques.. The results got from GA figuring's were differentiated and that got from conventional system. It was establish that the Optimization systems thump pattern tuning practices of customary PID controllers.

Speed Control of DC Motor Using Optimization Techniques Based PID Controller

The inverted cart-pendulum (ICP) is a nonlinear underactuated system, which dynamics are representative of many applications. Therefore, the development of ICP control laws is important since these laws are suitable to other systems. Indeed, many nonlinear control strategies have emerged from the control of the ICP. For these reasons, the ICP remains a canonical and fundamental benchmark problem in control theory and robotics that is of interest to the scientific community. Till now, the trial-and-error method is still widely applied for ICP controller tuning as well as the sequential tuning referring to tune the swing-up controller and thereafter, the stabilization controller. Therefore, the aim of this paper is to automate and facilitate the ICP control in one step. Thus, this paper proposes to holistically optimize ICP controllers. The holistic optimization is performed by a simplified Ant Colony Optimization method with a constrained Nelder–Mead algorithm (ACO-NM). Holistic optimization refers to a simultaneous tuning of the swing-up, stabilization and switching mode parameters. A new cost function is designed to minimize swing-up time, achieve high stabilization performance and consider system constraints. The holistic approach optimizes four controller structures, which include controllers that have never been tuned by a specific method besides by the trial-and-error method. Simulation results on a ICP nonlinear model show that ACO-NM in the holistic approach is effective compared to other algorithms. In addition, contrary to the majority of work on the subject, all the optimized controllers are validated experimentally. The simulation and experimental results obtained confirm that the holistic approach is an efficient optimization tool and specifically responds to the need of optimization technique for the potential-well controller structure and for the Q [diagonal of the matrix and the full matrix] in the linear–quadratic regulator (LQR) technique. Moreover, ICP experimental response analysis demonstrates that using the full Q provides greater experimental stabilization performance than using its diagonal terms in the LQR technique.

A holistic optimization approach for inverted cart-pendulum control tuning

This work proposes design and implementation of an optimal inverted pendulum controller using linear quadratic regulator (LQR) based on particle swarm optimization (PSO). The LQR feedback module is implemented on the Mitsubishi Q series-UDV programmable logic controller (PLC). In this paper, the optimum gains of the PSO based LQR are predefined offline by MATLAB and subsequently, evaluated in our experimental inverted pendulum. The results show that our proposed PSO based LQR technique provides the maximum swing with as low as 4 times of that from the traditional LQR approach when applied to the real plant.

Design and implementation of PSO based LQR control for inverted pendulum through PLC

In recent years, engineering education has become one of the challenging issues in Thailand education. By teaching and learning subjects independently, students are limited to subject-oriented problems, which are not in reality. To address these flaws, integrating knowledge across disciplines becomes significantly necessary. In the past years, STEM has been accepted as one of the effective strategies to bridge the difference in nature of each field to construct more practical projects and innovations. Moreover, the educational robot can be employed as a learning tool in that strategy since it not only provides challenging learning missions but also promotes computational thinking for the students. Therefore, this research study proposed STEM learning activities on three-day workshop to lay out the foundation to the high-school science-and-technology students who are becoming the engineering students. The workshop comprises of eight phases to facilitate their learning inquiry process with hands-on experience; moreover, the activities were designed in consideration of promoting computational thinking with challenging learning missions. The findings of this study showed that the proposed workshop activities are beneficial for the students who outperformed on robotics with higher computational thinking; meanwhile, they could provide more relevant responses regarding the proposed learning activities.

Enhancing High-School Students' Computational Thinking with Educational Robotics Learning

This work focuses on use of particle swarm optimization (PSO) to identify the optimal PID controller gains in speed control of a conveyor system. The proposed method is implemented on Mitsubishi Q series-UDV PLC with a number of encoder sensors and a built-in Ethernet module to monitor the feedback. To verify the performance of the proposed technique, we apply the optimal gains, which are determined offline by PSO, to the simulator and actual model. The experimental results show that the proposed PSO based PID controller provides lower transient fluctuation and smaller steady-state error compared to other previous approaches.

Speed control technique for conveyor using PSO based PID with programmable logic controller

Pre-service teachers play a crucial role in educational system as they are required to be well-prepared for their future teaching to students. Hence, they should be able to construct their own teaching materials effectively. Presently, Augmented Reality has widely been adopted to make learning and teaching environments more engaging and interesting. Therefore, this study employs the advantages of AR technology to motivate the pre-service teachers in constructing the teaching materials. Project-based learning approach has been used in this proposal by requiring the pre-service teachers developing their materials in a structural manner with higher-order thinking process. By analyzing the motivation questionnaires, it has found that the proposed approach has motivated them both males and females to construct their teaching materials. This novel approach could help enhance the preparation of educational system.

Motivating Pre-service Teachers with Augmented Reality to Developing Instructional Materials through Project-Based Learning Approach

In this work, we use PSO to adaptively adjust gains of PID and LQR controllers to regulate speed and position of a DC motor with load variation. The proposed framework is implemented on programmable logic controller (PLC) with encoder sensors and Ethernet port to monitor the feedback via SCADA application. Experimental results show that the proposed PSO based PID and LQR techniques provide relatively fast response and small steady-state error in the system under load variation.

Warin Sootkaneung

Papers

Design and implementation of PSO based LQR control for inverted pendulum through PLC

Enhancing High-School Students' Computational Thinking with Educational Robotics Learning

Speed control technique for conveyor using PSO based PID with programmable logic controller

Motivating Pre-service Teachers with Augmented Reality to Developing Instructional Materials through Project-Based Learning Approach

Implementation of PSO Based Gain-Scheduled PID and LQR for DC Motor Control Using PLC and SCADA