: Energy is a fundamental quantity in nature and is conserved due to the first law of thermodynamics.Actuators, necessarily, add energy into the system or remove energy from the system. Sensors remove energy from the system in order to measure some variable of interest. All control algorithms employing feedback,must measure at least one physical variable of the system to be controlled. Furthermore, all control algorithms must have at least one actuator in order to control the system. Hence, by proxy, all control algorithms affect the energy of the system. Two key ideas in energy shaping are: Energy Balancing and Power Shaping. Other control algorithms can be justify; MARGIN: 0cm 0cm 3pt; unicode-bidi: embed; DIRECTION: ltr" Optimization is a mathematical technique that concerns the finding of maxima or minima of functions in some feasible region. There is no business or industry which is not involved in solving optimization problems. A variety of optimization techniques compete for the best solution. Particle Swarm Optimization (PSO) is a relatively new, modern, and powerful method of optimization that has been empirically to perform well on many of these optimization problems. This thesis aims of this algorithm to find best solution in full search space. In this thesis an idea to optimum the energy based controller is proposed. In this report, it is proposed that aims to optimize the energy-based controller with a simple objective function. This method deal to fastest response, desired convergence properties, and reduced the Oscillations of system. Keywords: energy shaping, passivity-based control, interconnection and damping assignment, Pumping-Damping controller, Particle Swarm Optimization, artificial intelligence, evolutionary Computational.
