The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times s...
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Usually when modeling a real process the effects of nonlinearities must be taken into account. A road traffic sector is one such process. Considering it from a macroscopic point of view, the sector is modeled both as ...
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This paper is concerned with the design of a dynamic multivariable PID control for multi input multi output (MIMO) process. Four multivariable PID control schemes using Davison, Penttinen-Koivo, Maciejowski and a comb...
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ISBN:
(纸本)9781467357661
This paper is concerned with the design of a dynamic multivariable PID control for multi input multi output (MIMO) process. Four multivariable PID control schemes using Davison, Penttinen-Koivo, Maciejowski and a combined method were applied. The controller parameters for all control strategies were designed based on dynamic condition using singularly perturbed system. The purpose of the study is to investigate the effectiveness in the performance of dynamic control based on different multivariable PID control strategies. To attain the best result, numerous tuning parameters were tested. The simulation results show the significance of the study whereby the proposed dynamic MPID control scheme shows better improvement in control tuning of nonlinear system.
Research into conventional therapy and motor learning theory provides evidence that the intensity of practice of a task and feedback are important for iterative control of health care. Iterative learning control (ILC)...
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Research into conventional therapy and motor learning theory provides evidence that the intensity of practice of a task and feedback are important for iterative control of health care. Iterative learning control (ILC) is one model-based approach to stroke rehabilitation that has progressed to a program of clinical trials, which constitute the first major stage towards the eventual transfer into practice. ILC exploits the repeating nature of the patients' tasks to improve performance by learning from past experience as compared with other approaches employed to control FES. ILC is able to respond to physiological changes in the system, such as spasticity and the presence of a patient's voluntary effort by updating the control input using data collected over previous attempts at the task. ILC can also closely regulate the amount of stimulation supplied, ensuring that minimum assistance is provided, promoting the patient's maximum voluntary contribution to the task completion.
Usually when modeling a real process the effects of nonlinearities must be taken into account. A road traffic sector is one such process. Considering it from a macroscopic point of view, the sector is modeled both as ...
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Usually when modeling a real process the effects of nonlinearities must be taken into account. A road traffic sector is one such process. Considering it from a macroscopic point of view, the sector is modeled both as a nonlinear and as a linearized process. An 110 model is proposed and a RST control algorithm is used to ensure the imposed performances for the closed loop system. The robustness of the system is obtained by determining the modulus margin and based upon it the admissible nonlinearities are analyzed in order to determine the limits between which the system maintains its stability.
In the paper the first order sensitivity analysis is performed for a class of optimal control problems for time delay parabolic-hyperbolic equations. A singular perturbation of geometrical domain of integration is int...
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In the paper the first order sensitivity analysis is performed for a class of optimal control problems for time delay parabolic-hyperbolic equations. A singular perturbation of geometrical domain of integration is introduced in the form of a circular hole. The Steklov-Poincaré operator on a circle is defined in order to reduce the problem to regular perturbations in the truncated domain. The optimality system is differentiated with respect to the small parameter and the directional derivative of the optimal control is obtained as a solution to an auxiliary optimal control problem.
In many practical applications, constraints are often present on, for example, the magnitudes of the control inputs. Recently, based on a novel successive projection framework, two constrained iterative learning contr...
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In many practical applications, constraints are often present on, for example, the magnitudes of the control inputs. Recently, based on a novel successive projection framework, two constrained iterative learning control (ILC) algorithms were developed with different convergence properties and computational requirements. This paper investigates the effectiveness of these two methods experimentally on a gantry robot facility, which has been extensively used to test a wide range of linear model based ILC algorithms. The results obtained demonstrate the effectiveness of the algorithms in solving one form of the general constrained ILC problem.
In many practical applications, constraints are often present on, for example, the magnitudes of the control inputs. Recently, based on a novel successive projection framework, two constrained iterative learning contr...
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The paper considers design of Robustly Feasible Model Predictive controller which achieves recursive robust feasibility of the generated control actions when applied to nonlinear network systems with state constraint ...
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