The main objective of this paper is to design a robust multi-objective H2/H∞ delayed feedback controller for load frequency control of a multi-area interconnected power system by taking into account all theoretical and practical constraints. To achieve more precise modelling and analysis, the limitation of valve position, governor, and transmission delay are considered to guarantee of LFC system’s stability in practical applications. The nonlinear delayed system is approximated by the Takagi–Sugeno fuzzy model. Then, a parallel distributed compensation scheme is utilized for designing the control system of the overall system. The proposed multi-objective and robust H2/H∞ controller simultaneously minimizes the H2 and H∞ control performance indexes. Finally, simulation results verify the robustness and effectiveness of the proposed scheme in dealing with the impact of load disturbances, model uncertainties, transmission time delays, and nonlinearities in the model.

This paper presents a polynomial based optimal trajectory planning for an omni-directional mobile robot in presence of static obstacles with considering a limitation on velocity and acceleration of the robot. First, optimal trajectory planning problem is formulated as an optimal control problem which minimize a cost function of states and control efforts respect to constraints of the problem. To solve this optimal control problem, a state parameterization method is used. In fact, state variables of system are approximated by polynomial functions of time with unknown coefficients. Thus optimal control problem converts to a constraint optimization problem which is too easier than original optimal control problem. Then the polynomials coefficients are computed such that satisfy all the problem requirements and constraints. Simulation results show effectiveness of the proposed method under different situations.

In this paper we address the problem of finding trajectory for Omni-directional mobile robots. The objective of the trajectory planning is moving the robot from its initial position to a final position in the presence of static obstacles while minimizing a quadratic index of performance. Along the trajectory, the robot requires to observe certain velocity and acceleration limitations. This problem can be formulated as a constraint nonlinear optimal control problem. To solve this problem, we employ direct method of numerical solution in which the trajectories are parameterized by parametric polynomial functions. By this transforming, the main optimal control problem converts to a nonlinear programming problem (NLP) by lower computational cost. To solve the NLP and obtaining the trajectories, we utilize a new approach with too small run time. The performance and effectiveness of the proposed method are tested in simulations.