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We present a Nonlinear Model Predictive Control (NMPC) algorithm for real-time control of large-scale river networks in delta areas. The algorithm consists of an iterative, finite-horizon optimization of the system over a short-term control horizon. The underlying set of nonlinear internal process models represents relevant physical phenomena such as flow routing in the river network, and the dynamics...
PID control has been largely applied in the industry process control because of its robustness and easy realization, But it is very difficult to tune the three parameters of PID controller, which often leads to oscillation and overshoot of the controlled object. Due to no repetition and random of chaos dynamics, a method to search for PID controller parameters based on chaos variable is proposed according...
A model of a flexible manipulator is developed with considering the geometrical nonlinearity and the effect of gravity. The model can be divided into a flexible dynamic subsystem and a rigid dynamic subsystem, and a decomposed dynamic control (DDC) including flexible dynamic control and rigid dynamic control is proposed for a controller design of the flexible manipulator. The flexible dynamic control...
On-ramp control is the most effective and extensive way to improve freeway capacity. A proportional-integral (PI) control method based on ant colony optimization (ACO) is proposed to regulate the number of vehicles entering a freeway entrance point. First, a macroscopic traffic flow model is established. Then the basic principles of ant colony algorithm are formulated and the steps of ACO algorithm...
Nonlinear model predictive control (NMPC) needs to solve optimal control problems (OCPs) instantaneously so that new input can be applied in time. Computational delay, which may destroy the stability of the closed-loop, usually arises in the solution procedure of non-convex and nonlinear OCP with differential equations as its constraints. The traditional termination criteria for optimization algorithms...
According to the Lagrange equation, the mathematical model for the double inverted pendulum is first presented. For the fuzzy controller, the dimension of input varieties of fuzzy controller is depressed by designing a fusion function using optimization control theory, and it can reduce the rules of fuzzy sharply, `rule explosion' problem is solved. The result shows that the LQR-Fuzzy logic controller...
Based on the developed nonlinear dynamic equations of a quadrotor (named as Qball-X4) UAV (Unmanned Aerial Vehicle), attitude and trajectory tracking control designs based on an inner/outer loop control structure has been proposed in this paper. Feedback linearization is designed to control the attitude stability in inner loop, traditional PID is designed to follow trajectory in accordance with pre-planned...
In this study we develop a feedback controller for a four wheeled autonomous mobile robot. The purpose of the controller is to guarantee robust performance of an aggressive maneuver (90 degrees turn) at high velocity (about 10 m/s) on a loose surface (dirty road). To tackle this highly nonlinear control problem, we employ multi-objective evolutionary algorithms to explore and optimize the parameters...
This article aderesses aspects of the a-priori computation of the Fisher information matrix. The aim of the type of Fisher matrix discussed is the experiment design for parameter estimation of nonlinear state space models. A definition for the sampling of experiments is stated, which is convenient for software implementation. Both, measurement samples that belong to a coherent sequence and samples...
The paper presents an example of a linear, parameter varying (LPV) controller synthesis for a generic nonlinear missile. It is based on obtaining a parameter dependent Ljapunov function, in order to ensure stability of the system. The LPV model of the missile is constructed by means of Jacobian linearization at fixed parameter values. Performance requirements of the control system are specified in...
Underwater vehicles present a difficult control-system design due to their nonlinear dynamics, uncertain models, and the presence of disturbances that are difficult to measure or estimate. A multivariable design based on backstepping jointly with a simple optimization algorithm, that minimizes the energy consumption, is able to carry out the control of this system taking into account the uncertainties...
It is always a hard work to optimize the parameters of auto disturbance rejection controller (ADRC) because of its too many parameters. An optimization method for designing the submarine course ADRC based on the Nonlinear Control Design (NCD) block set of Matlab was proposed. The chief algorithm of ADRC and characters of the NCD block set were referred in briefly too. It was pointed out that there...
A novel multi-loop nonlinear Internal Model Control (IMC) strategy is developed for MIMO systems under the Partial Least Squares (PLS) framework, which automatically decomposes the MIMO process into several univariate systems in the latent space. The ARX-neural network (ARX-NN) model is incorporated in the PLS subspace and identified via optimizing two parameter sets so that the plant-model mismatch...
The paper discusses the quadratic neural unit (QNU) and highlights its attractiveness for industrial applications such as for plant modeling, control, and time series prediction. Linear systems are still often preferred in industrial control applications for their solvable and single solution nature and for the clarity to the most application engineers. Artificial neural networks are powerful cognitive...
The subspace identification problem of rare earth extraction process, which is based on nonlinear state-space models, is considered in this paper. The nonlinear part of the system model is approximated by the radial basis functions. The parameters are estimated in two steps. Firstly, The system matrices are determined by subspace identification method. Secondly, the parameters of the radial basis...
Fuel optimization of fixed time hard rendezvous problem is studied. Optimal fuel is calculated by indirect and direct approaches respectively. The indirect approach is based on primer vector theory, and primer vector of transfer orbit is calculated and improved. A nonlinear optimization model is formulated for the problem of multiple-impulse rendezvous optimizing by direct approach, and the optimal...
Efficiency optimization control of salient pole permanent magnet synchronous motor (PMSM) based on maximum ratio of torque to current is presented. From basic equations of PMSM in reference frame, the method of maximum ratio of torque to current was derived using maximum principle. Then, based on the Least Squares Support Vector Machine (LSSVM), modeling of LSSVM controller of maximum ratio of torque...
This paper addresses a general theoretical framework of optimal control problems (OCPs) associated with the conventional sliding mode dynamics. We deal with a class of constrained OCPs governed by nonlinear affine control systems and propose some numerically stable approximations to the sophisticated dynamical optimization problem. The above-mentioned structure of the state equations makes it also...
The depth control problem is described and addressed for a small autonomous underwater vehicle in this paper. Based on the nonlinear model of AUV in vertical plane, the paper established a mathematical model of AUV's depth motion in vertical plane by linearizing the model at a specified operating point. An optimal integral-sliding-mode controller was designed for the AUV depth control system by constructing...
The paper presents a nonlinear control strategy for single-phase active power filter applying exact feedback linearization theory, since this technique has been successfully applied to other area of power electronic. Using the state-space average modeling method, a nonlinear affine mode of single-phase shunt active power filter is set up. It is testified that the model is satisfied with the condition...
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