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H-infinity Performance Analysis of Singular Systems via Delta OperatorMethod |
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Xin-zhuang Dong, MINGQING XIAO(Southern Illinois University Carbondale, United States) |
| This paper investigates the problem of H-infinity performance analysis for singular systems through delta operator method. A novel admissibility condition is developed for singular delta operator systems. Based on the above result, two conditions are established for a singular delta operator system to be admissible with an H infinity performance. All of the conditions appeared in this paper are necessary and sufficient, characterized by a set of strict linear matrix inequalities whose feasible solutions can be obtained easily by matlab-LMI toolbox. |
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Robust PI compensators design for FOPDT systems with large uncertainty |
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Pedro Mercader, Alfonso Baños(University of Murcia, Spain) |
| This work presents a control design method to determine the parameters of a proportional integral (PI) compensator satisfying desired specifications on the gain and phase margins or, alternatively, an upper bound on the sensitivity transfer function, for a set of plants. The proposed approach is based on the translation of the desired specifications into the compensator parameter space, obtaining in such a way a feasible region where design specifications are met for each of the plant considered. To conclude, an example is given to illustrate the proposed method. |
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Adaptive Sliding Mode Control for Dual Missile |
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Seunghyun Kim, H. Jin Kim(Seoul National University, Republic of Korea) |
| This paper presents an adaptive sliding mode control for a dual-controlled missile with tail fins and reaction
jets. An RBF(Radial Basis Function) neural network is used to adaptively compensate for the uncertainties. The network
adaptation rule is derived from Lyapunov stability theory. It is shown that the proposed control design achieves uniformly
ultimate boundedness. The proposed controller is demonstrated by nonlinear missile dynamics and it shows a stable
response against uncertainty. |
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Linear Quadratic Evolution Algorithm Optimizer for Model Predictive Control at Model Uncertainty |
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Haitham Osman(King Khalid University, Saudi Arabia) |
| LQ Evolution Algorithm Optimizer for Model Predictive Control at Model Uncertainty
Haitham Osman (King Khalid University,Saudi Arabia)
This paper presents an evolution algorithm as a powerful optimisation technique for tuning Model Based Predictive Control (MBPC) at the implications of different levels of model uncertainties.
The multiobjective evaluation algorithms are capable to incorporate many objective functions that can meet simultaneously robust control design objective functions. These promising techniques are successfully implemented to stabilised MBPC at high model uncertainty |
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Modal Parametric Optimization of Control Laws with Special Structure |
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Evgeny I. Veremey, Margarita V. Sotnikova, Vladimir V. Eremeev, Maxim V. Korovkin(Saint Petersburg State University, Russian Federation) |
| The report is devoted to particular cases of optimization problems for dynamical systems with scalar control and external disturbance. The aim is to find optimal parameters of an output feedback controller having initially given structure. An admissible set of controllers is determined by the requirement to place the poles of linear closed-loop connection inside desirable regions on the complex left-half plane. Numerical algorithm is proposed to solve the posed problem using special multi-purposes structure of the controller. |
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Robust L2-L∞ Filtering for Uncertain Neutral Stochastic System with Markovian Jumping Parameters and Time Delay |
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Huasehng Tan, Mingang Hua(Hohai University, China) |
| The problem of robust L2-L∞ filter design of uncertain neutral stochastic systems with Markovian jumping parameters and time delay is discussed in this paper. The parameter uncertainties are assumed to be norm-bounded. Based on the Lyapunov-krasovskii theory and generalized Finsler lemma, a delay-dependent stability condition is obtained. The obtained result ensures the robust stochastic stability and a prescribed L2-L∞ performance level of the filtering error systems. Sufficient conditions for the existence of the designed l2-L∞ are formulated in terms of linear matrix inequalities(LMIs). |
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