The exponential stabilization problem of a class of linear systems with actuator saturation is addressed in this paper. In an approach different from the previous results where the continuous controllers are used all ...
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(纸本)9781467355339
The exponential stabilization problem of a class of linear systems with actuator saturation is addressed in this paper. In an approach different from the previous results where the continuous controllers are used all the time, here the periodically intermittent control is proposed to ensure the exponential stability of the closed-loop systems. An exponential stability criterion is suggested using the contractive invariant ellipsoid as an estimate of the domain of attraction. In addition, the exponential convergence rate is explicitly given. The feedback controller can also be designed by regarding the feedback gain as an additional variable. A numerical example is presented to illustrate the effectiveness of our theoretical analysis.
This paper studies the output tracking problem for a class of planar systems with some given transient performance constraints which are determined by the overshoot and the settling time. The problem of switched stati...
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This paper studies the output tracking problem for a class of planar systems with some given transient performance constraints which are determined by the overshoot and the settling time. The problem of switched static output feedback tracking with output constraints (SSOFTOC) is proposed and solved for the first time. The static output feedback controllers and a so-called conic switching law are designed under which the output of the closed-loop switched system can track the step signal asymptotically without violating the transient performance constraints. Furthermore, an optimal weighted transient performance is obtained by solving a nonlinear programming problem. Finally, a numerical example and an application to aircraft turbofan engine are given to illustrate the effectiveness and the applicability of the proposed method.
This paper focuses on the admissibility condition for fractional-order singular system with order α∈(0, 1). The definitions of regularity, impulse-free and admissibility are given first, then a sufcient and necessar...
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This paper focuses on the admissibility condition for fractional-order singular system with order α∈(0, 1). The definitions of regularity, impulse-free and admissibility are given first, then a sufcient and necessary condition of admissibility for fractional-order singular system is established. A numerical example is included to illustrate the proposed condition.
A novel adaptive data driven control strategy is proposed for general discrete nonlinear systems. The controller is designed based on the Simultaneous Perturbation Stochastic Approximation (SPSA) method, and is constr...
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A novel adaptive data driven control strategy is proposed for general discrete nonlinear systems. The controller is designed based on the Simultaneous Perturbation Stochastic Approximation (SPSA) method, and is constructed through use of a Function Approximator (FA), which is fixed as a neural network here. In this novel approach, the parametric estimation is designed to be adaptive, which greatly improves the control ability. The proposed control strategy is finally applied to solve nonlinear tracking problems for discrete-time nonlinear systems. The feasibility and effectiveness of the proposed adaptive data driven control strategy is well demonstrated through Simulation comparison tests.
In this paper, an autopilot system for the quadrotor unmanned aerial vehicle (UAV) is developed by utilizing a digital signal processor (DSP) as the on-board micro-control unit (MCU). The hardware setup and the softwa...
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In this paper, an autopilot system for the quadrotor unmanned aerial vehicle (UAV) is developed by utilizing a digital signal processor (DSP) as the on-board micro-control unit (MCU). The hardware setup and the software are also developed for the autonomous flight control of the UAV. The main design procedure includes the controller board design, brushless DC motor driver design, sensor data processing software design, and flight control algorithm design. The control algorithm is developed based on the inner loop and outer loop control method. Proportional Derivative (PD) controllers are proposed for the attitude dynamics (inner loop) and position dynamics (outer loop) respectively. Autonomous hovering control is achieved via the control of roll angle, pitch angle, yaw angle and altitude of the UAV. Experiments results are included to demonstrate the hovering control performance.
To provide a safe and efficient test for the autonomous control design of the unmanned helicopter, a 3 degree-of-freedom (DOF) helicopter testbed is developed in this paper. The testbed uses a small electric hobby hel...
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To provide a safe and efficient test for the autonomous control design of the unmanned helicopter, a 3 degree-of-freedom (DOF) helicopter testbed is developed in this paper. The testbed uses a small electric hobby helicopter as the main body, a digital signal processsor (DSP) is employed as the on-board micro control unit (MCU) for the attitude control of the helicopter, a micro attitude and heading reference system (AHRS) is utilized as the main on-board sensor for attitude states feedback and a Bluetooth module is mounted on the testbed to provide realtime wireless communication between the helicopter and the ground control station (GCS). This paper investigates the servo actuators coordinated control method with separate channel of the new-style electric helicopter, which is named as electronic collective-cyclic pitch mixing (ECCPM). A modified digital incremental PID control algorithm which is free of servo actuators saturation issue is proposed for the attitude control of the helicopter. Finally, experiment results are provided to verify the testbed and control design.
Adaptive dynamic programming (ADP) is a novel approximate optimal control scheme, which has recently become a hot topic in the field of optimal control. As a standard approach in the field of ADP, a function approxima...
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Adaptive dynamic programming (ADP) is a novel approximate optimal control scheme, which has recently become a hot topic in the field of optimal control. As a standard approach in the field of ADP, a function approximation structure is used to approximate the solution of Hamilton-Jacobi-Bellman (HJB) equation. The approximate optimal control policy is obtained by using the offline iteration algorithm or the online update algorithm. This paper gives a review of ADP in the order of the variation on the structure of ADP scheme, the development of ADP algorithms and applications of ADP scheme, aiming to bring the reader into this novel field of optimization technology. Furthermore, the future studies are pointed out.
The class of isotherm lumped process systems with constant overall mass in each of its balance volumes is considered in this paper. It is shown that the convection and transfer mechanisms can be described by a mass ac...
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The class of isotherm lumped process systems with constant overall mass in each of its balance volumes is considered in this paper. It is shown that the convection and transfer mechanisms can be described by a mass action law chemical reaction network (MAL CRN) with only linear kinetics where the in- and outflow terms are represented using the zero complex. This gives rise to a convection and transfer reaction sub-graph that connects atomic complexes consisting of the components in the balance volumes of the system. The real chemical reactions in each of the balance volumes can be described by their own CRNs, where the chemical reaction sub-graphs may be disconnected from the convection and transfer reaction sub-graph when nonlinear reactions occur. In the case of chemical reactions with a finite number of steady state points, the underlying linear dynamical system enables us to construct a dynamically similar linear overall reaction graph for the whole process system. The resulting overall reaction graph can be used for structural stability analysis by applying its graph theoretical properties.
In this paper,the reachable set estimation problem is studied for a class of dynamic neural networks subject to polytopic *** problem addressed here is to find a set as small as possible to bound the states starting f...
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In this paper,the reachable set estimation problem is studied for a class of dynamic neural networks subject to polytopic *** problem addressed here is to find a set as small as possible to bound the states starting from the origin by inputs with peak *** maximal Lyapunov functional is proposed to derive a sufficient condition for the existence of a non-ellipsoidal bound to estimate the states of neural *** is theoretically shown that this method is superior to the traditional one based on the common Lyapunov ***,two examples illustrate the advantages of our proposed result.
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