This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the ...This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the first step, a direct neural model(DNM)is used to learn the behavior of the system, then, an inverse neural model(INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation(BP) algorithm. In this work, the sliding mode-backpropagation(SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best configuration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the effectiveness of the proposed control strategy.展开更多
The quadrotor unmanned aerial vehicle is a great platform for control systems research as its nonlinear nature and under-actuated configuration make it ideal to synthesize and analyze control algorithms. After a brief...The quadrotor unmanned aerial vehicle is a great platform for control systems research as its nonlinear nature and under-actuated configuration make it ideal to synthesize and analyze control algorithms. After a brief explanation of the system, several algorithms have been analyzed including their advantages and disadvantages: PID, Linear Quadratic Regulator (LQR), Sliding mode, Backstepping, Feedback linearization, Adaptive, Robust, Optimal, L1, H∞, Fuzzy logic and Artificial neutral networks. The conclusion of this work is a proposal of hybrid systems to be considered as they combine advantages from more than one control philosophy.展开更多
Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be reg...Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem.展开更多
In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator tempera...In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator temperatures of FCCU in order to compare their performances. Control design was formulated as optimization problem to minimize infinity norm of weighted sensitivity functions subject to μ-interaction measure bound on diagonal complementary functions of the closed loop system. The optimization problem was solved using augmented Lagrangian genetic algorithm. Simulation results show that simultaneous and independent designs give good response with less overshoot and with no oscillation. Bound on μ-interaction measure is satisfied for both designs meaning that their nominal stabilities are guaranteed;however, it is marginal for simultaneous design. Simultaneous design outperforms independent design in term of robust performance while independent design gives the best performance in terms of robust stability. Sequential design gives the worst performance out of the three designs.展开更多
A feedforward approach for generating near time optimal controller for flexible spacecraft rest-to-rest maneuvers is presented with the objective insensitivity to modeling errors, parameter uncertainty and minimizing ...A feedforward approach for generating near time optimal controller for flexible spacecraft rest-to-rest maneuvers is presented with the objective insensitivity to modeling errors, parameter uncertainty and minimizing the residual energy of the flexible modes. The perturbation estimation of flexible appendages to the rigid-hub is accomplished simply via compare the output of real plant with the reference model, and the approach is based on combine this estimation with the bang-bang control for the rigid-hub modes through analysis the basic constraint and the additional constraint, i.e. zero coupling torque and zero coupling torque derivative for general two orders system and three orders system with considerate attitude acceleration mode near time optimal controls. These time optimal controls with control constraints and state constraints leads to forming a boundary-value problem, and resolved the problem using an iterative numerical algorithm. The near time optimal control with perturbation estimation shows a good robust to parameter uncertainty and can suppress the vibration and minimizing the residual energy. The capability of this approach is demonstrated through a numerical example in detail.展开更多
针对BP-PID控制器的控制性能受参数初值影响大、易陷入局部极值、对噪声敏感,且低信噪比条件下控制稳定性差等问题,提出了一种基于改进果蝇优化算法(Improved Fruit Fly Optimization Algorithm,IFOA)和径向基神经网络-卡尔曼滤波(Radia...针对BP-PID控制器的控制性能受参数初值影响大、易陷入局部极值、对噪声敏感,且低信噪比条件下控制稳定性差等问题,提出了一种基于改进果蝇优化算法(Improved Fruit Fly Optimization Algorithm,IFOA)和径向基神经网络-卡尔曼滤波(Radial Basis Function Network-Kalman Filter,RBF-KF)的噪声稳健BP-PID控制方法。首先提出了一种IFOA随机搜索算法对BP-PID初值进行全局寻优,自动获得全局最优解,提升系统控制精度。然后利用所提RBF-KF对观测数据进行滤波平滑,降低量测和控制噪声对系统的影响,提升低信噪比条件下的控制稳定性。基于某智能车车速控制真实数据开展试验,结果表明,所提方法相对于传统方法控制精度提升超过50%,控制稳定性提升超过60%,并且在低信噪比条件下优势更加明显,更适合实际工程应用场景。展开更多
In this paper, an integral-type robust mode following control for Plants with uncertainparameters and nonlinear factors is introduced. An genetic algorithm is also designed for obtaining thecontrol gains. Finally, som...In this paper, an integral-type robust mode following control for Plants with uncertainparameters and nonlinear factors is introduced. An genetic algorithm is also designed for obtaining thecontrol gains. Finally, some numerical examples are provided to illustrate the validity and efficiency ofthe proposed method.展开更多
文摘This work deals with robust inverse neural control strategy for a class of single-input single-output(SISO) discrete-time nonlinear system affected by parametric uncertainties. According to the control scheme, in the first step, a direct neural model(DNM)is used to learn the behavior of the system, then, an inverse neural model(INM) is synthesized using a specialized learning technique and cascaded to the uncertain system as a controller. In previous works, the neural models are trained classically by backpropagation(BP) algorithm. In this work, the sliding mode-backpropagation(SM-BP) algorithm, presenting some important properties such as robustness and speedy learning, is investigated. Moreover, four combinations using classical BP and SM-BP are tested to determine the best configuration for the robust control of uncertain nonlinear systems. Two simulation examples are treated to illustrate the effectiveness of the proposed control strategy.
文摘The quadrotor unmanned aerial vehicle is a great platform for control systems research as its nonlinear nature and under-actuated configuration make it ideal to synthesize and analyze control algorithms. After a brief explanation of the system, several algorithms have been analyzed including their advantages and disadvantages: PID, Linear Quadratic Regulator (LQR), Sliding mode, Backstepping, Feedback linearization, Adaptive, Robust, Optimal, L1, H∞, Fuzzy logic and Artificial neutral networks. The conclusion of this work is a proposal of hybrid systems to be considered as they combine advantages from more than one control philosophy.
文摘Non-linearity and parameter time-variety are inherent properties of lateral motions of a vehicle. How to effectively control intelligent vehicle (IV) lateral motions is a challenging task. Controller design can be regarded as a process of searching optimal structure from controller structure space and searching optimal parameters from parameter space. Based on this view, an intelligent vehicle lateral motions controller was designed. The controller structure was constructed by T-S fuzzy-neural network (FNN). Its parameters were searched and selected with genetic algorithm (GA). The simulation results indicate that the controller designed has strong robustness, high precision and good ride quality, and it can effectively resolve IV lateral motion non-linearity and time-variant parameters problem.
文摘In this work, three decentralized control configuration designs—independent, sequential and simultaneous designs—were used in multivariable feedback configurations for PI control of the riser and regenerator temperatures of FCCU in order to compare their performances. Control design was formulated as optimization problem to minimize infinity norm of weighted sensitivity functions subject to μ-interaction measure bound on diagonal complementary functions of the closed loop system. The optimization problem was solved using augmented Lagrangian genetic algorithm. Simulation results show that simultaneous and independent designs give good response with less overshoot and with no oscillation. Bound on μ-interaction measure is satisfied for both designs meaning that their nominal stabilities are guaranteed;however, it is marginal for simultaneous design. Simultaneous design outperforms independent design in term of robust performance while independent design gives the best performance in terms of robust stability. Sequential design gives the worst performance out of the three designs.
文摘A feedforward approach for generating near time optimal controller for flexible spacecraft rest-to-rest maneuvers is presented with the objective insensitivity to modeling errors, parameter uncertainty and minimizing the residual energy of the flexible modes. The perturbation estimation of flexible appendages to the rigid-hub is accomplished simply via compare the output of real plant with the reference model, and the approach is based on combine this estimation with the bang-bang control for the rigid-hub modes through analysis the basic constraint and the additional constraint, i.e. zero coupling torque and zero coupling torque derivative for general two orders system and three orders system with considerate attitude acceleration mode near time optimal controls. These time optimal controls with control constraints and state constraints leads to forming a boundary-value problem, and resolved the problem using an iterative numerical algorithm. The near time optimal control with perturbation estimation shows a good robust to parameter uncertainty and can suppress the vibration and minimizing the residual energy. The capability of this approach is demonstrated through a numerical example in detail.
文摘针对BP-PID控制器的控制性能受参数初值影响大、易陷入局部极值、对噪声敏感,且低信噪比条件下控制稳定性差等问题,提出了一种基于改进果蝇优化算法(Improved Fruit Fly Optimization Algorithm,IFOA)和径向基神经网络-卡尔曼滤波(Radial Basis Function Network-Kalman Filter,RBF-KF)的噪声稳健BP-PID控制方法。首先提出了一种IFOA随机搜索算法对BP-PID初值进行全局寻优,自动获得全局最优解,提升系统控制精度。然后利用所提RBF-KF对观测数据进行滤波平滑,降低量测和控制噪声对系统的影响,提升低信噪比条件下的控制稳定性。基于某智能车车速控制真实数据开展试验,结果表明,所提方法相对于传统方法控制精度提升超过50%,控制稳定性提升超过60%,并且在低信噪比条件下优势更加明显,更适合实际工程应用场景。
文摘In this paper, an integral-type robust mode following control for Plants with uncertainparameters and nonlinear factors is introduced. An genetic algorithm is also designed for obtaining thecontrol gains. Finally, some numerical examples are provided to illustrate the validity and efficiency ofthe proposed method.
