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This paper presents an optimal control of a HIV stochastic model through drug therapy. The model shows the effect of anti-retrovirus drugs in different stages of infection. The optimal controller is achieved by Genetic Algorithm (GA). In this paper we find appropriate efficacies of a drug that minimize the virus particles for a deterministic model and stochastic model. To design the optimal stochastic...
Optimal control has been a very attractive and desirable feature for many dynamic and static systems, An effective online technique for finite-horizon nonlinear control problem is offered in this paper. The idea of the proposed technique is to combine the differential State Dependent Riccati equation filter algorithm and the finite-horizon SDRE technique. Genetic algorithm is used to calculate the...
The flexible variable-speed control system of rod pumping well is designed to increase the oil production speed and to reduce both the rod stress and motor energy consumption by changing the motor drive speed rapidly during a stroke cycle. This paper establishes a flexible variable-speed control model as well as the optimization algorithm for rod pumping well. The optimal motor speed profile is determined...
In this paper, in view of the research achievements of domestic and oversea researchers, the energy-saving manipulation strategies are designed for the train operation between stations by using the genetic algorithm, which synthesize the knowledge of train traction calculation and the characteristic of locomotive traction and braking. The energy-saving control strategy is based on the train maximum...
This work suggests a hybrid approach combined with a conventional method and a metaheuristic to study the problem of constrained optimal control of nonlinear switched systems. The first method is based on the Pontryagin Maximum Principle associated with the Lagrange multipliers method while satisfying the KKT conditions. Concerning the second method, it uses the Genetic Algorithms. Finally, this approach...
In this paper an optimal control method for parafoil system homing planning is introduced, which includes multi-phase homing arrangement, optimal homing path calculation using genetic algorithm(GA), and Bezier curves based path planning for parafoil terminal guidance to deal with the situation of variable glide ratios. L1 nonlinear algorithm is adopted to make trajectory tracking. Comparison simulations...
This paper investigates the efficiency of optimization algorithms to adjust the fractional order PIλDμ controller parameters. We used genetic algorithms (GA) to minimize an error function defined in the time-domain, between the system output response and the system step input (where the gap is the error in response to step unit set point). This optimization is denoted step optimization. The optimization...
The ongoing trend of increasing product individualization requires more flexible solutions in production systems. Modular robots address this demand since they can be assembled in different ways from a given set of modules. One of the reasons why modular robots are not yet successfully introduced in the market is that it is not clear how to assemble modules such that the robot will be able to achieve...
This paper presents an approach for co-state initialization which is a crucial step in solving minimum-time low-thrust trajectory optimization problems using indirect optimal control numerical methods. Indirect methods used in determining the optimal space trajectories result in two-point boundary value problems which are typically solved by single- or multiple-shooting methods. Accurate initialization...
An Unmanned aerial vehicle (UAV) guidance law is addressed as an optimal regulator (LQR) problem. An adaptive optimal path following nomenclature is derived and defined. The state weighting matrix of the LQR is defined in term of intrinsic parameter error thereby enabling the guidance law to regulate the UAV disturbance errors effectively. The state weighing matrix is tuned using a genetic algorithm...
The lightweight, integrated, and high performance motor-wheel driven electric vehicle is clean, energy saving, and safe, and has the potential to form the ideal electric vehicle for the future. This paper proposes an optimal fuzzy neural network braking control strategy to determine the allocation of the front and rear regenerative braking torque and friction braking torque for the independent four...
This paper addresses the problem of the hierarchical manpower system control in the restructuring process. The restructuring case study is described where eight topmost ranks are considered. The desired and actual structure of the system is given by the actual numbers of men in a particular rank. The system was modelled in the dicrete state space with state elements and flows representing the recruitment,...
Our work focuses mainly on the optimal control issues for switched nonlinear systems. In fact, we are interested, especially, in studying some cases in which we obtain a pre-specified string of active subsystems. Besides, we suggest Genetic Algorithm approach in order to obtain the optimal switching instants. We intend mainly to reduce the cost function according to the previously-mentioned instants.
In designing an optimal composite nonlinear feedback (CNF) controller, the parameter estimation of linear feedback gain and nonlinear gain parameters are important to produce the best output response. An optimization algorithm is designed to minimize the time consuming to get the best parameter. To design an optimal method, Multi Objective Genetic Algorithm (MOGA) is utilized to optimize the CNF controller...
This paper describes an application of Artificial Bee Colony (ABC) to load frequency control (LFC) in single, two and multi-area interconnected power systems. The proposed ABC algorithm is used to obtain the optimal values of the proportional-integral-derivation (PID) controller parameters based load frequency control (LFC). The principal function of the LFC loop is to control the frequency and active...
In this paper AI techniques arc applied to the production of air-to-air missile guidance laws. A Genetic Algorithm (GA) is used as a numerical optimisation tool to optimise neural network based guidance laws. Traditionally techniques including Optimal Control Theory, Feedback Linearisation and Differential Game Theory have been applied to the problem. Using Genetic Algorithms one can incorporate constraints,...
Recently, in (Hatzikos and Owens, 2002b) and (Hatzikos and Owens, 2002a) it was explored whether or not Genetic Algorithm (GAs) based approach can be used in the context of norm-optimal Iterative Learning Control (ILC). It turned out the answer was positive for both linear and nonlinear plant models. However, this approach is still immature in the sense that it can produce very ‘noisy’ intermediate...
A non-linear model of a Rolls-Royce turbo machine's rotor supported by active magnetic bearings (AMBs) is presented. A multiobjective genetic algorithm (MOGA) is used as a search and optimisation tool for designing AMB controllers. The H∞ loop-shaping design is used to guarantee the stability and robustness of the controller, and a MOGA is used to select weighting function structure and parameters...
A significant problem in aircraft performance is the presence of turbulent flows over the surfaces of major components such as the aircraft body, wings and engine nacelles. Turbulence significantly increases the overall drag on the aircraft and therefore incurs the penalty of reduced performance and increased fuel demand. A possible solution is to delay the transition from laminar to turbulent flow...
The study investigates optimal policies for determining price of the product under the influence of reworking during production. A mathematical model is proposed using optimal control theory for profit maximization, which determines the optimal pricing strategies. Moreover, we have considered reworking of imperfect items being produced during the machine shifts from in-control state to out-control...
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