In the present paper, a linear complementarity method for a vehicle-bridge dynamic system considering separation and random roughness is established.
Solving a MC-TAP is computationally more intensive than a single class TAP for which a variety of methods such as Variational Inequality, Complementarity Method, Fixed-Points and Entropy Maximization, as well as origin-based (or bush based) methods have been proposed [84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94].
We predicted sRNA triggers for PHAS loci mainly based on sequence complementarity (see Methods for details).
A shape complementarity search method and a statistical method called 'grouping' were combined to evaluate and predict the affinity between various protein pairs with known structures.
Then the controller gain is achieved by using an extended cone complementarity linearization method.
An iterative algorithm is developed to compute the controller's parameters by means of the Cone Complementarity Linearization Method (CCLM).
Based on the cone complementarity linearization method [22], the controller and observer gains can be obtained by the following nonlinear minimization problem subject to (16): left { textstylebegin{array}l} operatorname{Min} {operatorname{Tr}(sum_{i=1}^{N}(P_{i}G_{i}))}, {bigl[}{scriptsizebegin{matrix} P_{i}&I cr ast&G_{i} end{matrix}}bigr]geq0, quad iin{1,2,ldots,N}.
Third, by resorting to the average dwell time approach and the free-weighting matrix technique, some sufficient criteria for the desired disturbance observer and the state feedback controller are established, and the corresponding solvability conditions using a cone complementarity linearization method are presented.
Based on this model, the necessary and sufficient condition on the stochastic stability of networked control system with random delays and actuator fault is given, and the corresponding dynamic output controller design procedure is proposed via the cone complementarity linearization method.
Then, criteria for the H∞ controller design are obtained by using the convexity properties of the matrix inequality and some other new analysis techniques, which are shown in terms of nonlinear matrix inequalities and can be solved by using a cone complementarity liberalization method.
