In this paper, we present a gain-scheduling distributed model predictive control (MPC) algorithm for polytopic uncertain systems subject to actuator saturation. A large-scale system is decomposed into subsystems and s...
In this paper, we present a gain-scheduling distributed model predictive control (MPC) algorithm for polytopic uncertain systems subject to actuator saturation. A large-scale system is decomposed into subsystems and sub-controllers are designed independently. An invariant set condition is provided and a min-max distributed MPC strategy is proposed based on the invariant set. The distributed MPC controller is determined by solving a linear matrix inequality (LMI) optimization problem. An iterative algorithm is provided to coordinate the sub-controllers. A numerical example is carried out to demonstrate the effectiveness of the proposed algorithm.
This paper investigates distributed leader-following swarm of heterogeneous multi-agent systems. Comparing with the existing works on leader-following swarm of homogeneous multi-agent systems, this paper is much more ...
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This paper investigates distributed leader-following swarm of heterogeneous multi-agent systems. Comparing with the existing works on leader-following swarm of homogeneous multi-agent systems, this paper is much more approaching the practical situation because the agents have different dynamics. We show that the heterogeneous followers will gather with a certain error lever under some assumptions and conditions. The stability properties have been proven by theoretical analysis and verified via numerical simulation. The stability of the heterogeneous multi-agent systems has been achieved based on matrix theory and the Lyapunov stability theorem. Numerical simulation is given to demonstrate the effectiveness of the theoretical result.
This paper investigates distributed leader-following swarm stability of heterogeneous multi-agent systems with periodically intermittent control. We assume that the agents in the network are nonidentical and the coupl...
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ISBN:
(纸本)9789881563835
This paper investigates distributed leader-following swarm stability of heterogeneous multi-agent systems with periodically intermittent control. We assume that the agents in the network are nonidentical and the coupling matrix is balanced. Each heterogeneous follower is assumed to obtain some information from the leader and the neighbors only on a series of periodically time intervals. We show that the system will be exponentially stable. The stability properties are proved via theoretical analysis and verified via numerical simulations. The stability of the heterogeneous multi-agent systems is proved based on matrix theory and the Lyapunov stability theorem. A numerical example is shown to demonstrate the effectiveness of the theoretical result.
This paper describes the three-dimensional motion control of a magnetic levitated object in an active electromagnetic levitation conveyance system. Generally, the magnetic levitation conveyance system is useful when w...
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ISBN:
(纸本)9781479905492
This paper describes the three-dimensional motion control of a magnetic levitated object in an active electromagnetic levitation conveyance system. Generally, the magnetic levitation conveyance system is useful when we convey products without qualitative degradation due to contact. However it is necessary to control the three-dimensional motion of the levitated object and it is difficult to measure the position. Therefore we propose how to estimate three-dimensional position without a position sensor. Four Hall elements are installed on the bottom of the electromagnet instead of the position sensor. A state observer estimates the three-dimensional position of the levitated object from the four Hall voltages and the current and the input voltage to the electromagnet. The three-dimensional motion controller uses a state-feedback control based on the estimated position. This controller has a large stability margin in order to compensate the modeliza-tion error. The validity of the proposed method is confirmed by experiment results.
This paper studies the global leader-following consensus problem for a multi-agent system using bounded controls. Both the agents and the leader are described by a chain of integrators of arbitrary length. A saturated...
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ISBN:
(纸本)9781479900305
This paper studies the global leader-following consensus problem for a multi-agent system using bounded controls. Both the agents and the leader are described by a chain of integrators of arbitrary length. A saturated linear feedback control law is constructed for each system in the group. These feedback laws use a multi-hop relay protocol, in which each agent obtains the information of other agents through multi-hop paths in the communication network, and the feedback gains are constructed from the adjacency matrix of the communication network. It is shown that global leader-following consensus is achieved under the feedback control laws we have constructed when the communication topology among follower agents is a strongly connected and detailed balanced directed graph and the leader is a neighbor of at least one follower. Simulation results are given to illustrate the theoretical results.
We consider control of a cooling system with several consumers that require cooling from a common source. The flow feeding coolant to the consumers can be controlled, but due to significant physical distances between ...
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ISBN:
(纸本)9781467357159
We consider control of a cooling system with several consumers that require cooling from a common source. The flow feeding coolant to the consumers can be controlled, but due to significant physical distances between the common source and the consumers, the coolant flow takes a non-negligible amount of time to travel to the consumers, giving rise to input-dependent state delays. We first present a simple bilinear model of the system, followed by a state feedback control design that is able to stabilize the system at a chosen equilibrium in spite of the delays. We also present a heuristic, performance-oriented improvement to the design. The strategy is illustrated with some simulation examples.
This paper introduces an intelligent evaluation method based on improved PSO-WNN (partiele swarm optimization-wavelet neural network) for speech denoising in high background noise. Firstly, by using Lyapunov stability...
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In this paper, we present an improved analytic method to the optimal trajectory generation of an autonomous underwater vehicle (AUV) in a dynamic environment. The proposed approach explicitly incorporates both the AUV...
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In this paper, we present an improved analytic method to the optimal trajectory generation of an autonomous underwater vehicle (AUV) in a dynamic environment. The proposed approach explicitly incorporates both the AUV kinematic and the geometric constraints due to dynamic obstacles and the terrain while rendering the near-shortest path by a performance index related to the path length. In particular, the proposed design is based on a family of parameterized trajectories determined by three adjustable parameters, which provides a unified way to reformulate the geometric constraints and performance index into a set of parameterized constraint equations. To that end, such a constrained optimization problem boils down to optimize those adjustable parameters, which can be analytically solved in the parameter space. The proposed solution enhances the methodologies of real-time path planning for robots in 3D environment. Simulation results verify the effectiveness of the proposed method.
A lot of work have been carried out to find the efficient algorithms for QoS-aware dynamic web service composition. The multi-objective multi-choice problem as an evolutive multi-dimension multi-objective 0-1 knapsack...
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ISBN:
(纸本)9780769547923
A lot of work have been carried out to find the efficient algorithms for QoS-aware dynamic web service composition. The multi-objective multi-choice problem as an evolutive multi-dimension multi-objective 0-1 knapsack problem (MMKP) can be reduced into the web service composition with multiple QoS constraints, while many approaches based on ant colony optimization (AOC) have been introduced in order for solving MMKP. This paper presents a novel QoS-aware dynamic web service composition optimization algorithm with improved AOC. The essence of the algorithm is that the problem of dynamic web service selection with QoS global optimality is transformed into a multi-objective multi-choice QoS-aware web services composition optimization (an evolutive MMKP), for the final purpose of our algorithm is to achieve Pareto Optimality.
In this paper, block-based compressive low-light-level imaging (BCL-imaging) is studied. To obtain larger measurement SNR (signal to noise ratio), instead of object pixels, linear combinations of pixels, referred to a...
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In this paper, block-based compressive low-light-level imaging (BCL-imaging) is studied. To obtain larger measurement SNR (signal to noise ratio), instead of object pixels, linear combinations of pixels, referred to as features, are collected. PCA and Hadamard features are studied. Measurement SNR and reconstruction error are analyzed to quantify BCL-imaging performance. Compared with conventional imaging, BCL-imaging presents better reconstruction quality. Between PCA and Hadamard projections, PCA has smaller reconstruction error. However, after sorting the projection vectors using measurement SNR, Hadamard can obtain similarly performance as PCA. Biased vector and dual-measurements are studied with experimental results for the implementation of both projections in the end of this paper.
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