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Appl. Syst. Innov., Volume 2, Issue 2 (June 2019) – 7 articles

Cover Story (view full-size image): Producing domestic hot water efficiently from renewable energy sources is important to reduce anthropogenic carbon emissions. The efficiency of solar systems can be improved by adopting controllers to optimize their operations and adapt to changes in the environmental conditions. This paper presents a comparative analysis of several control methods, including a self-learning, coupled fuzzy control/Q-learning controller applied on a simulated domestic hot water system. Several 5-year simulations were performed to assess the performance of the controllers with respect to the energy harvesting process, the global system performance and the impact on the primary circulator durability. View this paper.
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17 pages, 301 KiB  
Article
Existence of Fractional Impulsive Functional Integro-Differential Equations in Banach Spaces
by Dimplekumar Chalishajar, Chokkalingam Ravichandran, Shanmugam Dhanalakshmi and Rangasamy Murugesu
Appl. Syst. Innov. 2019, 2(2), 18; https://doi.org/10.3390/asi2020018 - 14 Jun 2019
Cited by 13 | Viewed by 3190
Abstract
In this paper, we establish the existence of piece wise (PC)-mild solutions (defined in Section 2) for non local fractional impulsive functional integro-differential equations with finite delay. The proofs are obtained using techniques of fixed point theorems, semi-group theory and generalized Bellman inequality. [...] Read more.
In this paper, we establish the existence of piece wise (PC)-mild solutions (defined in Section 2) for non local fractional impulsive functional integro-differential equations with finite delay. The proofs are obtained using techniques of fixed point theorems, semi-group theory and generalized Bellman inequality. In this paper, we used the distributed characteristic operators to define a mild solution of the system. We also discussed the controversy related to the solution operator for the fractional order system using weak and strong Caputo derivatives. Examples are given to illustrate the theory. Full article
(This article belongs to the Special Issue Non-linear Devices, Systems, Networks and Their Applications)
24 pages, 1377 KiB  
Article
Ant Lion Optimized Fractional Order Fuzzy Pre-Compensated Intelligent Pid Controller for Frequency Stabilization of Interconnected Multi-Area Power Systems
by A. H. Gomaa Haroun and Yin-Ya Li
Appl. Syst. Innov. 2019, 2(2), 17; https://doi.org/10.3390/asi2020017 - 15 May 2019
Cited by 7 | Viewed by 2923
Abstract
Load frequency control (LFC) is considered to be the most important strategy in interconnected multi-area power systems for satisfactory operation and distribution. In order to transfer reliable power with acceptable quality, an LFC mechanism requires highly efficacy and intelligent techniques. In this paper, [...] Read more.
Load frequency control (LFC) is considered to be the most important strategy in interconnected multi-area power systems for satisfactory operation and distribution. In order to transfer reliable power with acceptable quality, an LFC mechanism requires highly efficacy and intelligent techniques. In this paper, a novel hybrid fractional order fuzzy pre-compensated intelligent proportional-integral-derivative (PID) (FOFP-iPID) controller is proposed for the LFC of a realistic interconnected two-area power system. The proposed FOFP-iPID controller is incorporated into the power system as a secondary controller. In doing so, the parameters of the suggested FOFP-iPID controller are optimized using a more recent evolutionary computational technique called the Ant lion optimizer (ALO) algorithm utilizing an Integral of Time multiplied Absolute Error (ITAE) index. Simulation results demonstrated that the proposed FOFP-iPID controller achieves better dynamics performance under a wide variation of load perturbations. The supremacy of the proposed FOFP-iPID controller is demonstrated by comparing the results with some existing controllers, such as fractional order PID (FOPID) and fractional order intelligent PID (FOiPID) controllers for the identical system. Finally, the sensitivity analysis of the plant is examined and the simulation results showed that the suggested FOFP-iPID controller is robust and performs satisfactorily despite the presence of uncertainties. Full article
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14 pages, 764 KiB  
Article
Continuous-Service M/M/1 Queuing Systems
by Song Chew
Appl. Syst. Innov. 2019, 2(2), 16; https://doi.org/10.3390/asi2020016 - 28 Apr 2019
Cited by 2 | Viewed by 3363
Abstract
In this paper, we look into a novel notion of the standard M/M/1 queueing system. In our study, we assume that there is a single server and that there are two types of customers: real and imaginary customers. Real customers are regular customers [...] Read more.
In this paper, we look into a novel notion of the standard M/M/1 queueing system. In our study, we assume that there is a single server and that there are two types of customers: real and imaginary customers. Real customers are regular customers arriving into our queueing system in accordance with a Poisson process. There exist infinitely many imaginary customers residing in the system. Real customers have service priority over imaginary customers. Thus, the server always serves real (regular) customers one by one if there are real customers present in the system. After serving all real customers, the server immediately serves, one at a time, imaginary customers residing in the system. A newly arriving real customer presumably does not preempt the service of an imaginary customer and hence must wait in the queue for their service. The server immediately serves a waiting real customer upon service completion of the imaginary customer currently under service. All service times are identically, independently, and exponentially distributed. Since our systems are characterized by continuous service by the server, we dub our systems continuous-service M/M/1 queueing systems. We conduct the steady-state analysis and determine common performance measures of our systems. In addition, we carry out simulation experiments to verify our results. We compare our results to that of the standard M/M/1 queueing system, and draw interesting conclusions. Full article
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25 pages, 9884 KiB  
Article
Analysis and Adaptation of Q-Learning Algorithm to Expert Controls of a Solar Domestic Hot Water System
by Davide Bettoni, Anton Soppelsa, Roberto Fedrizzi and Raul Mario del Toro Matamoros
Appl. Syst. Innov. 2019, 2(2), 15; https://doi.org/10.3390/asi2020015 - 25 Apr 2019
Cited by 6 | Viewed by 3191
Abstract
This paper discusses the development of a coupled Q-learning/fuzzy control algorithm to be applied to the control of solar domestic hot water systems. The controller brings the benefit of showing performance in line with the best reference controllers without the need for devoting [...] Read more.
This paper discusses the development of a coupled Q-learning/fuzzy control algorithm to be applied to the control of solar domestic hot water systems. The controller brings the benefit of showing performance in line with the best reference controllers without the need for devoting time to modelling and simulations to tune its parameters before deployment. The performance of the proposed control algorithm was analysed in detail concerning the input membership function defining the fuzzy controller. The algorithm was compared to four standard reference control cases using three performance figures: the seasonal performance factor of the solar collectors, the seasonal performance factor of the system and the number of on/off cycles of the primary circulator. The work shows that the reinforced learning controller can find the best performing fuzzy controller within a family of controllers. It also shows how to increase the speed of the learning process by loading the controller with partial pre-existing information. The new controller performed significantly better than the best reference case with regard to the collectors’ performance factor (between 15% and 115%), and at the same time, to the number of on/off cycles of the primary circulator (1.2 per day down from 30 per day). Regarding the domestic hot water performance factor, the new controller performed about 11% worse than the best reference controller but greatly improved its on/off cycle figure (425 from 11,046). The decrease in performance was due to the choice of reward function, which was not selected for that purpose and it was blind to some of the factors influencing the system performance factor. Full article
(This article belongs to the Special Issue Solar Thermal Systems)
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16 pages, 9157 KiB  
Article
Gaze-Guided Control of an Autonomous Mobile Robot Using Type-2 Fuzzy Logic
by Mahmut Dirik, Oscar Castillo and Adnan Fatih Kocamaz
Appl. Syst. Innov. 2019, 2(2), 14; https://doi.org/10.3390/asi2020014 - 24 Apr 2019
Cited by 8 | Viewed by 4062
Abstract
Motion control of mobile robots in a cluttered environment with obstacles is an important problem. It is unsatisfactory to control a robot’s motion using traditional control algorithms in a complex environment in real time. Gaze tracking technology has brought an important perspective to [...] Read more.
Motion control of mobile robots in a cluttered environment with obstacles is an important problem. It is unsatisfactory to control a robot’s motion using traditional control algorithms in a complex environment in real time. Gaze tracking technology has brought an important perspective to this issue. Gaze guided driving a vehicle based on eye movements supply significant features of nature task to realization. This paper presents an intelligent vision-based gaze guided robot control (GGC) platform that uses a user-computer interface based on gaze tracking enables a user to control the motion of a mobile robot using eyes gaze coordinate as inputs to the system. In this paper, an overhead camera, eyes tracking device, a differential drive mobile robot, vision and interval type-2 fuzzy inference (IT2FIS) tools are utilized. The methodology incorporates two basic behaviors; map generation and go-to-goal behavior. Go-to-goal behavior based on an IT2FIS is more soft and steady progress in data processing with uncertainties to generate better performance. The algorithms are implemented in the indoor environment with the presence of obstacles. Experiments and simulation results indicated that intelligent vision-based gaze guided robot control (GGC) system can be successfully applied and the IT2FIS can successfully make operator intention, modulate speed and direction accordingly. Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
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34 pages, 422 KiB  
Article
Using Dual Double Fuzzy Semi-Metric to Study the Convergence
by Hsien-Chung Wu
Appl. Syst. Innov. 2019, 2(2), 13; https://doi.org/10.3390/asi2020013 - 11 Apr 2019
Cited by 1 | Viewed by 2152
Abstract
Convergence using dual double fuzzy semi-metric is studied in this paper. Two types of dual double fuzzy semi-metric are proposed in this paper, which are called the infimum type of dual double fuzzy semi-metric and the supremum type of dual double fuzzy semi-metric. [...] Read more.
Convergence using dual double fuzzy semi-metric is studied in this paper. Two types of dual double fuzzy semi-metric are proposed in this paper, which are called the infimum type of dual double fuzzy semi-metric and the supremum type of dual double fuzzy semi-metric. Under these settings, we also propose different types of triangle inequalities that are used to investigate the convergence using dual double fuzzy semi-metric. Full article
(This article belongs to the Special Issue Fuzzy Decision Making and Soft Computing Applications)
16 pages, 1072 KiB  
Article
Model-Free Robotic Architecture with Task-Multiplexer and Discrete-Time Adaptive Control
by Chidentree Treesatayapun
Appl. Syst. Innov. 2019, 2(2), 12; https://doi.org/10.3390/asi2020012 - 08 Apr 2019
Viewed by 2608
Abstract
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer unit. With only the [...] Read more.
Robotic systems equipped with a task-multiplexer unit are considered as a class of unknown non-linear discrete-time systems, where the input is a command voltage of the driver unit and the output is the feedback signal obtained by the multiplexer unit. With only the input and output data available, an equivalent identification is formulated by a multi-input fuzzy rule emulated network. An online-learning algorithm is proposed to tune all adjustable parameters by using convergence analysis. Using the equivalent model, a controller is developed when the convergence of the tracking error and internal signals can be guaranteed. An experimental system validates the performance of the proposed scheme. Furthermore, the comparative results are also included, to demonstrate the advantage of the proposed controller. Full article
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