Sina Dehghan

Bio: Sina Dehghan is an academic researcher from University of California, Merced. The author has contributed to research in topics: PID controller & Control theory. The author has an hindex of 3, co-authored 13 publications receiving 157 citations.

A review and evaluation of numerical tools for fractional calculus and fractional order controls

Abstract: In recent years, as fractional calculus becomes more and more broadly used in research across different academic disciplines, there are increasing demands for the numerical tools for the computation of fractional integration/differentiation, and the simulation of fractional order systems. Time to time, being asked about which tool is suitable for a specific application, the authors decide to carry out this survey to present recapitulative information of the available tools in the literature, in hope of benefiting researchers with different academic backgrounds. With this motivation, the present article collects the scattered tools into a dashboard view, briefly introduces their usage and algorithms, evaluates the accuracy, compares the performance, and provides informative comments for selection.

A review and evaluation of numerical tools for fractional calculus and fractional order control

Abstract: In recent years, as fractional calculus becomes more and more broadly used in research across different academic disciplines, there are increasing demands for the numerical tools for the computation of fractional integration/differentiation, and the simulation of fractional order systems. Time to time, being asked about which tool is suitable for a specific application, the authors decide to carry out this survey to present recapitulative information of the available tools in the literature, in hope of benefiting researchers with different academic backgrounds. With this motivation, the present article collects the scattered tools into a dashboard view, briefly introduces their usage and algorithms, evaluates the accuracy, compares the performance, and provides informative comments for selection.

Low-Cost Real-Time Vision Platform for Spatial Temperature Control Research Education Developments

Abstract: Temperature control is present in many industrial processes, making this skill mandatory for the control engineers. For this reason, different training temperature platforms have been created for this purpose. However, many of these platforms are expensive, require elaborate facility accommodations, and have higher heating and cooling times, making not suitable for teaching and training. This paper presents a low-cost educational platform for temperature control training. The platform employs a Peltier module as a heating element, which has lower heating and cooling time than other thermal system implementations. A low-cost real-time thermal camera is employed as a temperature feedback sensor instead of a standard thermal sensor. The control algorithm is developed in Matlab-Simulink and employs an Arduino board as hardware in the loop to manage the Peltier module. A temperature control experiment is performed to show that the platform is suitable for teaching and training experiences not only in the classroom but for engineers in the industry.

PID2018 Benchmark Challenge: Model Predictive Control With Conditional Integral Control Using A General Purpose Optimal Control Problem Solver - RIOTS

Abstract: This paper presents a multi-variable Model Predictive Control (MPC) based controller for the one-staged refrigeration cycle model described in the PID2018 Benchmark Challenge. This model represents a two-input, two-output system with strong nonlinearities and high coupling between its variables. A general purpose optimal control problem (OCP) solver Matlab toolbox called RIOTS is used as the OCP solver for the proposed MPC scheme which allows for straightforward implementation of the method and for solving a wide range of constrained linear and nonlinear optimal control problems. A conditional integral (CI) compensator is embedded in the controller to compensate for the small steady state errors. This method shows significant improvements in performance compared to both discrete decentralized control (C1) and multi-variable PID controller (C2) originally given in PID2018 Benchmark Challenge as a baseline. Our solution is introduced in detail in this paper and our final results using the overall relative index, $J$, are 0.2 over C1 and 0.3 over C2, respectively. In other words, we achieved 80% improvement over C1 and 70% improvement over C2. We expect to achieve further improvements when some optimized searching efforts are used for MPC and CI parameter tuning.

A Random Walk Down Wall Street

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Analytical solutions of electrical circuits described by fractional conformable derivatives in Liouville-Caputo sense

Abstract: In this paper, new analytical solutions for the RL, LC and RLC electric circuits considering conformable and β -derivatives of type Liouville-Caputo were analyzed. These solutions were obtained by iterating conformable and β -integrals. The fractional derivatives considered have properties similar to the classical fractional integrals and derivatives. Due to these operators depend on two parameters, we obtain a better detection of the memory. Novel fractional conformable β -derivatives in the Riemann-Liouville and the Liouville-Caputo sense are obtained. Numerical simulations of alternative models are presented for evaluating the effectiveness of these representations. Different source terms are introduced in the fractional conformable differential equations in Liouville-Caputo sense.