This paper presents the application of a linear matrix inequalitiy tuning approach for the design of remote feedback controllers for power systems. In particular, the determined controllers are both robust and optimal for a wide range of operating conditions, This duality is assured through the application of the proposed tuning process. The controllers presented in this paper were conceived for and tested on a 4-machine test power system with regard to their ability to damp the inter-area oscillation present in the test system and to allow an increase in tie-line power flow without a loss of stability.
Tracking the maximum output power of a photovoltaic (PV) cell is an important problem to harvest more energy at different weather and load conditions. This paper presents the design and simulation of a robust direct adaptive controller (RDAC) for maximum power point tracking (MPPT) device based on boost converter topology. A mathematical model is developed, and a suitable RDAC is designed for MPPT device, and simulations are performed using MATLAB/Simulink to verify the controller’s robustness at varying operating conditions. The real-time irradiance and temperature data are used on an hourly basis to test the suggested MPPT adaptive controller for a typical sunny day in summer and winter. The simulation results show that the RDAC performs excellent tracking under varying conditions such as irradiance, temperature, load, boost converter inductance, and capacitance.
Conventional nonadjustable four-bar linkages can only generate the desired continuous paths approximately. With one link length adjustment, the whole desired continuous path can be generated precisely. In this paper, the length of the driven side link or coupler is adjusted to generate the desired continuous paths precisely. The linkage feasibility conditions and path generation flexibilities of the adjustable four-bar linkages are analyzed. The optimal synthesis model of adjustable four-bar linkages is established based on the required optimal link length adjustment when the desired continuous path is precisely generated. The global optimal solution is searched by a real-valued genetic algorithm in which the involved constraints are handled using the function penalty method. The effectiveness of the optimal synthesis approach proposed in the paper is verified by the demonstrated examples.
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