This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the...
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ISBN:
(纸本)9781467355322
This paper presents a new method based on the polytopic linear differential inclusion and the robust mixed H2/∞ filtering for the design of the nonlinear filter with non-Gaussian noises. The main goal is to solve the problems of the complexity and large calculation number in the general nonlinear filter and the filtering design problem for systems with the non-Gaussian noises. The noises considered in the paper involve two different kinds of noises: white noises and energy bounded noises. Differing from the linearization in most nonlinear filters, the estimation error system for the nonlinear system is represented by an uncertain polytopic linear model, based on which, the rectification equations for the predicted errors are designed following the robust mixed H2/∞ filtering. The state estimates for the nonlinear system are given through updating the predictions by the rectified quantities, where, the state predicted quantities of the nonlinear system are gained by the prediction equation of the EKF. The evident advantage of the new filter is the filter coefficients of the rectification equation are constant, without the need to evaluate the Jacobian matrixes. As a result, the calculation number for the new filter is decreased much and the real-time performance of the new filter is much better than the EKF, though the accuracy is a little decline. Its effectiveness is demonstrated by using an example and the statistics result of the calculation number for the filters in the example.
Networked controlsystems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communications while still keepin...
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ISBN:
(纸本)9781467374439
Networked controlsystems(NCSs) are facing a great challenge from the limitation of network communication resources. Event-triggered control(ETC) is often used to reduce the amount of communications while still keeping a satisfactory performance of the system, by transmitting the state measurements only when an event-triggered condition is met. However,some network-induced problems would happen inevitably, such as communication delay. The delay can degrade the control performance significantly and can even lead to instability. In this paper, we study an NCS considering both ETC and time-varying delay, which is rare in the literature. We formulate the system as a discretized piecewise linear system with exponential uncertainty. Then the model is embedded in a polytopic approximation with better structure suitable for stability *** conditions are derived in terms of linear matrix inequalities(LMIs). Finally, the developed method is illustrated by a numerical example.
Autonomous vehicles have attracted considerable attention in the research community and industry due to their potential benefits to unmanned driving and assisted driving. This paper addresses the problem of designing ...
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ISBN:
(纸本)9781467355322
Autonomous vehicles have attracted considerable attention in the research community and industry due to their potential benefits to unmanned driving and assisted driving. This paper addresses the problem of designing lateral control law and the strategy of determining the giving speed for autonomous vehicles. An improved method of calculating lateral offset and angle error based on multiple look-ahead distances is proposed to reduce the impact of noise in reference path data on the lateral control system. Multiple fuzzy inference engines are used to design the steering controller and determine the given driving speed including forward and backward to deal with both simple and complex reference paths. Satisfactory simulation and experimental results have been obtained for different reference paths including a path with U-turn task in which backward driving is needed.
This paper investigates the attitude tracking control problem of reentry vehicle with modeling inaccuracies and external disturbances. An improved nonsingular terminal sliding mode control method is presented, and a f...
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ISBN:
(纸本)9781509009107
This paper investigates the attitude tracking control problem of reentry vehicle with modeling inaccuracies and external disturbances. An improved nonsingular terminal sliding mode control method is presented, and a faster convergence rate is obtained in comparison with the conventional nonsingular terminal sliding mode control(NTSM). By the proposed control strategy, the possible singularity during the control phase is avoided, and robustness is also guaranteed. Simulation is made for a reentry vehicle in the condition aerodynamic parameters and atmospheric density are perturbed. The results show the effectiveness of the proposed strategies.
An optimal time-varying sliding mode controller based on SDRE approach is proposed in this paper for re-entry vehicle attitude control in the presence of parametric uncertainties and external disturbances. Firstly, an...
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ISBN:
(纸本)9781467355339
An optimal time-varying sliding mode controller based on SDRE approach is proposed in this paper for re-entry vehicle attitude control in the presence of parametric uncertainties and external disturbances. Firstly, an optimal time-varying sliding surface is obtained through the minimization of a given performance index function and the philosophy of time-varying sliding mode control. Subsequently, a discontinuous control law is designed for guaranteeing the existence of the sliding mode throughout the entire response of the system. Therefore, the global robustness can be ensured. Simulation example is finally given to illustrate the effectiveness of the proposed controller.
This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear *** existing optimal state feedback control,the control input of the optimal parallel control is introduced int...
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This paper studies the problem of optimal parallel tracking control for continuous-time general nonlinear *** existing optimal state feedback control,the control input of the optimal parallel control is introduced into the feedback ***,due to the introduction of control input into the feedback system,the optimal state feedback control methods can not be applied *** address this problem,an augmented system and an augmented performance index function are proposed ***,the general nonlinear system is transformed into an affine nonlinear *** difference between the optimal parallel control and the optimal state feedback control is analyzed *** is proven that the optimal parallel control with the augmented performance index function can be seen as the suboptimal state feedback control with the traditional performance index ***,an adaptive dynamic programming(ADP)technique is utilized to implement the optimal parallel tracking control using a critic neural network(NN)to approximate the value function *** stability analysis of the closed-loop system is performed using the Lyapunov theory,and the tracking error and NN weights errors are uniformly ultimately bounded(UUB).Also,the optimal parallel controller guarantees the continuity of the control input under the circumstance that there are finite jump discontinuities in the reference ***,the effectiveness of the developed optimal parallel control method is verified in two cases.
A chaotic particle swarm optimization (CPSO) algorithm is proposed by introducing chaos state into the original Particle Swarm optimization (PSO) which aims to solving the flaws of easy plunging into local optimum and...
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ISBN:
(纸本)9781467355339
A chaotic particle swarm optimization (CPSO) algorithm is proposed by introducing chaos state into the original Particle Swarm optimization (PSO) which aims to solving the flaws of easy plunging into local optimum and losing search ability in the last period for the fast particle velocity decrease. CPSO algorithm takes advantage of the ergodicity, randomicity, and regularity of chaos to make chaotic searching for the global extremun at the same time with the particle swarm optimization. This algorithm synthesizes the high efficiency of global optimization of PSO algorithm and the ergodicity and randomicity of local search of chaotic algorithm. This paper utilizes aforementioned algorithm to identify the Bouc-Wen hysteresis model for piezoelectric ceramic actuators (PCA). The experimental results show that the model identified by CPSO algorithm has better performance than that by PSO algorithm.
The control problem of spacecraft eigenaxis maneuver in the presence of parametric uncertainty and external disturbance is addressed in this paper. Modified Rodrigues parameters (MRPs) are utilized as the attitude p...
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ISBN:
(纸本)9781467355339
The control problem of spacecraft eigenaxis maneuver in the presence of parametric uncertainty and external disturbance is addressed in this paper. Modified Rodrigues parameters (MRPs) are utilized as the attitude parameters for the non-redundancy. An eigenaxis maneuver control law with feedback and feed-forward terms is presented for the nominal system. The transient response of close loop system can be adjusted according to an approximate second order system. To improve the robustness, integral sliding mode (ISM) technique is adopted to reject undesirable effects and track nominal trajectory. The resulting controller can perform the eigenaxis maneuver in the presence of parametric uncertainty and external disturbance while possess good system performance. The effectiveness of the proposed method is demonstrated by simulation results.
In this work, we use the approach based on observers such as the neural observer in order to introduce the diagnosis of nonlinear systems. There are different techniques for training the neural networks. Among these t...
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