Modal phase matching (MPM) is a widely used phase matching technique in AlxGa1−xAs and other χ(2) nonlinear waveguides for efficient wavelength conversions. The use of a non-fundamental spatial mode compensates the m...
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Electric vehicles (EVs) will play a vital role in the future's transportation systems since this technology is promising for environment, energy security, and improved fuel economy. EVs have huge potential of serv...
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Assistive robots have been grown in recent years and joints' moving pattern is one of the important issues in these robots. The predefined trajectory for the robot brings some stability difficulties for the users....
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ISBN:
(数字)9781728158150
ISBN:
(纸本)9781728158167
Assistive robots have been grown in recent years and joints' moving pattern is one of the important issues in these robots. The predefined trajectory for the robot brings some stability difficulties for the users. This paper introduces a systematic way to produce an optimal gait for the controller of the lower extremity exoskeleton. This optimal gait producing strategy releases us from the exhausting procedure of walking pattern capture in different paces which requires various devices and motion analysis lab. A feedback-controlled system is defined which enables us to change walking parameters during steps with a smooth walking pattern which is of vital importance for the patients in these kinds of robots. This goal has been achieved by solving an optimal control problem, and the cost function of this optimization problem is obtained thorough walking limitations. Implementation on the Exoped robot verifies the performance of the proposed walking trajectory planning method in this paper.
This paper investigates the robust stability and stabilization analysis of interval fractional-order systems with time-varying delay. The stability problem of such systems is solved first, and then using the proposed ...
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Numerical P systems(for short, NP systems) are distributed and parallel computing models inspired from the structure of living cells and economics. Enzymatic numerical P systems(for short, ENP systems) are a variant o...
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Numerical P systems(for short, NP systems) are distributed and parallel computing models inspired from the structure of living cells and economics. Enzymatic numerical P systems(for short, ENP systems) are a variant of NP systems, which have been successfully applied in designing and implementing controllers for mobile robots. Since ENP systems were proved to be Turing universal, there has been much work to simplify the universal systems, where the complexity parameters considered are the number of membranes, the degrees of polynomial production functions or the number of variables used in the *** the number of enzymatic variables, which is essential for ENP systems to reach universality, has not been investigated. Here we consider the problem of searching for the smallest number of enzymatic variables needed for universal ENP systems. We prove that for ENP systems as number acceptors working in the all-parallel or one-parallel mode, one enzymatic variable is sufficient to reach universality; while for the one-parallel ENP systems as number generators, two enzymatic variables are sufficient to reach *** results improve the best known results that the numbers of enzymatic variables are 13 and 52 for the all-parallel and one-parallel systems, respectively.
In this paper, a fixed-order procedure is presented utilizing convex optimization and linear matrix inequalities (LMIs) to control a quarter car uncertain active suspension system. Our purpose is to design a low-order...
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ISBN:
(数字)9781728158150
ISBN:
(纸本)9781728158167
In this paper, a fixed-order procedure is presented utilizing convex optimization and linear matrix inequalities (LMIs) to control a quarter car uncertain active suspension system. Our purpose is to design a low-order robust controller that keeps the desired design specifications besides the simplicity of the implementation. In our model, the system is influenced by the non-linear disturbance of the road surface, and the polytopic uncertainty model for state matrices of the system is utilized to cover the uncertainties of the model and the delay caused by the dynamic of the system. In this paper, a specific form of a positive definite matrix is used to overcome the complexity of rank minimization constraints. The proposed controller is considered with the most general state-space representation of linear systems which can be resulted by solving appropriate LMI constraints utilizing available efficient solving methods. Our proposed controller benefits from the dynamic property, independency of all individual states of the system, being of arbitrary order, and robustness against model uncertainty simultaneously. Eventually, a simulation example is presented to illustrate the correctness and effectiveness of the proposed method and obtained results for different orders that are compared with each other and also with that of a similar full-order method.
Interconnected system between computation and physical process (Cyber-Physical Systems) has been widely used in industrial processes. In CPS-based industrial process, sensors, controllers, and actuators are connected ...
Interconnected system between computation and physical process (Cyber-Physical Systems) has been widely used in industrial processes. In CPS-based industrial process, sensors, controllers, and actuators are connected into a communication network. The communication network may introduce delay time uncertainties due to shared resources and load traffic in the network. Furthermore, the nonlinear time-varying characteristic of batch distillation column may causes another uncertainties to take into account in control system design. Parameter model and delay process uncertainty is introduced due to linearized system approximation that unmodeled high-frequency dynamics. The dynamic uncertainty on both I/O channel are also introduced to the system uncertainty. In this paper, robust PI and PID controller using AMIGO method with appropriate weighting function is designed to guarantee robust stability spesification of batch distillation column. The impact of system uncertainties to closed-loop system performances such as peak overshoot and integral error is investigated. MATLAB/Simulink simulation is used to validate the methods before its implementation in CPS-based batch distillation column. Based on simulation, the proposed robust PI/PID controller can guarantee robust stability of system compared to conventional PID controller. Furthermore, the robust PI/PID controller can improve closed-loop system performances compared to conventional PID.
Previous work has shown that adversarial learning can be used for unsupervised monocular depth and visual odometry (VO) estimation, in which the adversarial loss and the geometric image reconstruction loss are utilize...
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Data-driven modeling methods are widely used in industrial processes as the foundation of control and *** selection of optimal variable set plays an important role in model *** order to enhance the model prediction ac...
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Data-driven modeling methods are widely used in industrial processes as the foundation of control and *** selection of optimal variable set plays an important role in model *** order to enhance the model prediction accuracy,a partial mutual information(PMI) method was proposed to select the optimal variable *** were used to validate the effectiveness of PMI ***,PMI method was applied to select main influencing factors of NOx emission of coal-fired boiler and the selection results were used as inputs of three different data-driven *** comparison between the models with or without variable selection was *** results showed that the PMI method enhanced the model prediction accuracy and avoided the over-fitting problem.
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