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Iterative Learning control (ILC) is a powerful control concept that iteratively improves the behaviors of processes that are repetitive in nature. A new and systematic frequency-domain approach of the PD iterative learning control has been presented based upon frequency domain of continuous model. For design specifications, including the convergence margin and cut-off frequency which is determined...
Differential Evolution (DE) which has been focused on computation intelligence is a new swarm intelligent algorithm by simulating intelligence of population after GA and PSO etc. It is more robust and efficient. Because the differential degree of individuals is minimized in the last, the diversity of population will be reduced and DE will converge ahead of schedule. It is well known that simulated...
In order to make full use of the advantages of both parametric and non-parametric models simultaneously, a kind of semi-parametric support vector machine (SVM) was proposed by combining a non-parametric SVM model and a parametric linear basis function model. The semi-parametric SVM was used to estimate the Q values of continuous-state-discontinuous-action pairs in an on-line manner so as to generalize...
To improve the accuracy of clustering classification, the Chaos Genetic Algorithm was proposed. In this algorithm, the ergodic property of chaos phenomenon is used to optimize the initial population, so it can accelerate the convergence of Genetic Algorithms. Chaotic systems are sensitive to initial condition system parameters. In order to escape from local optimums, the chaos operator was applied...
As a new model of intelligent computing, ant colony optimization (ACO) is a great success on combinatorial optimization problems, however, but research is relatively less in solving problems on continuous space optimization. Based on the mechanism and mathematical model of ant colony algorithm, mutation operation is introduced. The global and local updating rules of ant colony algorithm are improved...
According to the problem on calculating the synthetic exponent characterizing the whole performance of radar engine by using the synthetic weighted method, the weights of every parameter are difficult to be determined. To solve this problem, a method of determining the weights of every parameter by adaptive genetic algorithm is presented. The synthetic exponent gained by AGA is more sensitive and...
This paper investigates the problem of robust H∞ control for linear time-delay singular systems with linear fractional parametric uncertainties. By linear matrix inequality approach, a sufficient condition is given for the existence of a memory state feedback controller, which guarantees that the closed-loop systems are admissible with an H∞ norm bound γ for all admissible uncertainties. Meanwhile,...
The celebrated Redheffer's theorem on linear fractional transformations is rederived in this paper using an algebraic state-space approach based on a generalization of the ARE bounded real lemma recently obtained. This state-space derivation is easier to check and more constructive than the original one and is able to reveal interesting connections between the theorem and some system theory concepts...
This paper is concerned with the design problem of non-fragile H-infinity controller for discrete-time descriptor systems. The controller gain variations are assumed to be time-invariant and norm-bounded appearing in the controller coefficients. Sufficient conditions for the existence of a static state feedback H-infinity controller with additive uncertainty and multiplicative uncertainty are obtained...
The integrated control model of active suspension and electrical power steering system was established. General uncertainties which can cause vehicle unstable were considered. An integrated controller for both active suspension and electric power steering system of vehicle was constructed based on μ control theory. The μ control law minimized an objective function (H2 norm) for a given controller...
Robust fault-tolerant H∞ control against actuator failures and/or sensor failures is investigated for a class of uncertain descriptor systems via dynamical compensators. Based on H∞ theory, sufficient conditions for the existence of dynamical compensators are derived. The dynamical compensators guarantee that the closed-loop descriptor systems are admissible and maintain certain H∞ norm performance...
The problem of reliable H2 static output feedback controller design against actuator faults for continuous-time systems with polytopic type uncertainty is addressed based on parameter-dependent Lyapunouv function approach. Sufficient conditions for reliable H2 static output feedback controller designs are derived via adding auxiliary variables and given in terms of solutions to a set of linear matrix...
Long time delay is a very common phenomenon encountered in process industry and it is difficult to control by conventional methods. To solve this problem, a decentralized predictive control method is presented. According to the structure of the process industry with long time-delay, it can be decomposed into a series of short dead-time problems. In order to further overcome the effect of dead-time,...
An optimization method of predictive function control (PFC) parameters that based on modified differential evolution (DE) is provided. Differential evolution is a new evolutionary computation technology and exhibits good performance on optimization. Differential evolution algorithm as a relatively new evolutionary computation technique has a good optimization. Therefore, the modified differential...
In view of the 1st-order dynamic process with the disturbance of ARIMA(0,1,1), the effect of special cause is analyzed and an economic design of integrating SPC and APC based on quality statistical properties is given. Through this method the operating cost is minimum and the required statistical properties are thought concurrently. These research results may provide some theoretical basis for the...
MPCs have been widely applied in industrial process control field because of the excellent control effect. The classic MPCs, which are all based on linear predictive models, are unfit for the strong-nonlinearity control systems. In these cases, NMPCs must be constructed if a model predictive controller wants to be used. Nonlinear predictive model is the foundation of NMPC, and should be established...
Model predictive controllers have been widely applied in refinery and chemical plant. The process model plays an important role in the performance assessment of model predictive control. In this work, a methodology is adopted for the diagnosis of model-plant mismatch (MPM) based on closed-loop operating data in the DMC system. The problem of MPM is transformed into the effectiveness of the model....
The text aims at the harmonic pollution and powerless of the electronic network caused by inverter. Based on the foundation of power device IEGT and dual-PWM three-level inverter characteristics, the contrast of the rectifier three-pulse PWM modulate mode and the triangle PWM modulate mode is given. As a result, IEGT dual-PWM three-level inverter possesses the characteristics such as the good input...
In this paper, we investigate fast distributed consensus problems of a network of second-order dynamic agents. A consensus protocol which considers the average information of the agents' states in a certain time interval is proposed. Based on the frequently-domain analysis and matrix theory, the sufficient conditions for the second-order multi-agent system converging to a fast stationary consensus...
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