Development of a Semi-definite Programming Weighted Sum Based Approach for Solving Stochastic Multi-objective Economic Dispatch Problems Incorporating CHP Units

This paper has presented a weighted sum based semidefinite programming (SDP) optimization technique for solving stochastic multi-objective economic dispatch (MOED) model that incorporates Combined Heat and Power (CHP) units. The stochastic multi-objective model was transformed into its deterministic equivalent through their expectation, with the assumption that involved random variables are normally distributed. The multi-objective problem was recast in matrix form as a SDP relaxation problem and subsequently solved with a MATLAB programming suite. The system inequality and equality constraints uncertainty were entered into YALMIP, which is a linear matrix inequality parser. Simulations were performed on modified IEEE 6 and 20 units’ networks with 2 CHP units. The efficiency of the proposed method is deter- mined by investigating reformulated problems in stochastic and deterministic models on power dispatch. The standard weighted sum method is utilized in generating the Pareto-optimal solution between two objectives’ functions. An optimal selection of control weight selection k 1 parameter that provides a better convergence property and moderately good extent of the Pareto distributions was empirically determined. The proposed SDP method performed well in accuracy of results and providing lower operational cost in the Pareto set produce

A Simulator for Testing Planar Upper Extremity Rehabilitation Robot Control Algorithms

In this study, we took advantage of the emergence of accurate biomechanical human hand models to develop a system in which the interaction between a human arm and a rehabilitation robot while performing a planar trajectory tracking task can be simulated. Seven biomechanical arm models were based on the 11-degree-of-freedom Dynamic Arm Simulation model and implemented in OpenSim. The model of the robot was developed in MatlabSimulink and interaction between the arm and robot models was achieved using the OpenSim API. The models were tested by simulating the performance of each model while moving the end effector of a simulated planar robot model through an elliptical trajectory with an eccentricity of 0.94. Without assistance from the robot, the average root-mean-square error (RMSE) for all subjects was 3.98 mm. With the simulated robot providing assistive torque, the average RMSE error reduced to 2.88 mm. The test was repeated after modifying the length of the robot links, and an average RMSE of 2.91 mm recorded. A single-factor ANOVA test revealed that there was no significant difference in the RMSE for the two different robot geometries (p-value = 0.479), revealing that the simulator was not sensitive to robot geometry