Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is...
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ISBN:
(纸本)9789746724913
Accurate and effective parameter identification is an important engineering task in high performance control system design. One emerging approach to effectively identify such nonlinear or dynamic unknown parameters is to use Particle Swarm Optimization (PSO) algorithm. Linear Permanent Magnet (LPM) motor is a high performance actuator employed in many applications that require direct linear motion without mechanical transmission for high acceleration and accurate positioning. Therefore, accurate motor parameters are necessary to effectively control the LPM motors. This paper proposes a simple PSO based method with chirp inputs to identify the LPM motor's parameters. The simulations and experiments are conducted to verify the results and determine the effectiveness of the proposed method.
We propose an optimization-based framework to find multiple fixed length paths for multiple robots that satisfy the following constraints: (i) bounded curvature, (ii) obstacle avoidance, (iii) and collision avoidance....
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This paper discusses tracking control problem with a discrete-time multi-agent system with active leader and quantized communication constraints. For the active leader in a general linear form, we give a distributed d...
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ISBN:
(纸本)9787894631046
This paper discusses tracking control problem with a discrete-time multi-agent system with active leader and quantized communication constraints. For the active leader in a general linear form, we give a distributed design for each discrete-time agent in the leader tracking control problem and analyze the tracking convergence with the help of Riccati equation and common Lyapunov function when the communication channel is perfect. Then a stochastic quantization strategy is applied to model the information transmission in the agent coordination and the corresponding solution is also given, even if the interconnection topology is switching.
In order to reduce the computational a novel approach is proposed in which the generalized predictive control (GPC) algorithm is improved based on toeplitz matrix in this paper. The control algorithm proposed is simpl...
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In order to reduce the computational a novel approach is proposed in which the generalized predictive control (GPC) algorithm is improved based on toeplitz matrix in this paper. The control algorithm proposed is simplified by reconstructing the performance index. This approach has good adaptive ability and robustness with low-cost computation. The effectiveness and rapidity of this algorithm is demonstrated by the simulation results.
Two methods for capturing the basis weight variation from imaging measurements have been developed. The problem is to estimate basis weight variation from the optical transmittance measurement which contains mixed inf...
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ISBN:
(纸本)9781617387890
Two methods for capturing the basis weight variation from imaging measurements have been developed. The problem is to estimate basis weight variation from the optical transmittance measurement which contains mixed information of many quality parameters. The first method calibrates with the scanning basis weight measurement the model relating the light transmittance and basis weight, whereas the second method uses the scanning measurement for filtering and replacing the transmittance measurement when necessary. The performance of the methods is evaluated with a simulator developed to describe the quality variations and control of the paper web. The simulated transmittance image is generated assuming a linear effect of basis weight, moisture and ash content on transmittance. The measurement modes and control options of the simulator are also presented.
When a micro cantilever with a nanoscale tip is manipulated on a substrate with atomic roughness, e.g., pushing an atomic-scale sample or etching the surface of the substrate to draw desired patterns, the periodical l...
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The Hammerstein systems, consisting of a zero-memory nonlinearity followed by a linear dynamic function, exists universally in industrial, chemical, physical and biological systems. Thus an effective modelling method ...
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ISBN:
(纸本)9787894631046
The Hammerstein systems, consisting of a zero-memory nonlinearity followed by a linear dynamic function, exists universally in industrial, chemical, physical and biological systems. Thus an effective modelling method for Hammerstein systems is critical for both relevant scientific research and engineering applications. We propose a novel Hammerstein identification approach, in which a multi-channel mechanism is used to separate the coefficients of the linear and nonlinear blocks more completely. Compared with traditional single-channel identification algorithms, the present identification method can enhance the approximation accuracy remarkably under the weak condition on the persistent excitation (PE) condition of the inputs.
Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matri...
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ISBN:
(纸本)9787894631046
Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matrix inequalities (LMIs), guarantee the synchronized states to be global asymptotically stable. In addition, an interesting conclusion is reached that the chaotic synchronization in the coupled whole 3N-dimensional networks can be converted into that of 3-dimensional space.
Using the known periodicity of the given trajectory, we develop a new dynamical linearization method by introducing a concept of PPD, then present a new model-free periodic adaptive control approach (MFPAC) and its ex...
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Using the known periodicity of the given trajectory, we develop a new dynamical linearization method by introducing a concept of PPD, then present a new model-free periodic adaptive control approach (MFPAC) and its extension of higher-order learning control algorithm for a class of general nonlinear and non-affine discrete-time systems. It is model-free in nature and the controller design and analysis only depends on the I/O data of the dynamical system. The proposed MFPAC updates the PPD estimate values and the control signals periodically in a pointwise manner using the I/O data obtained at the corresponding points in previous periods, in the sequel achieves an asymptotic tracking convergence. A simulation example illustrates the feasibility and effectiveness of the proposed method.
In this work, we propose a simplified least squares formulation (SLSF) for dynamic material balancing in chemical processes, which are often described by differential-algebraic equations. We compare the SLSF with trad...
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In this work, we propose a simplified least squares formulation (SLSF) for dynamic material balancing in chemical processes, which are often described by differential-algebraic equations. We compare the SLSF with traditional techniques, such as steady state data reconciliation (SSDR) and Kalman filter (KF). We also modify the SLSF when its assumptions can't be totally satisfied in some practical settings. Using chemical systems examples, we demonstrate that the SLSF can well deal with the practical dynamic material balancing problems.
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