Applying multi-objective particle swarm optimization (MOPSO) algorithm to multi-objective design of multimachine power system stabilizers (PSSs) is presented in this paper. The proposed approach is based on MOPSO algorithm to search for optimal parameter settings of PSS for a wide range of operating conditions. Moreover, a fuzzy set theory is developed to extract the best compromise solution. T...

This study presents a Linear Quadratic Optimal (LQR) controller design for an inverted pendulum on a cart using the Artificial Bee Colony (ABC) algorithm. Main design parameters of the linear quadratic regulator are the weighting matrices. Generally, selecting weighting matrices is managed by trial and error since there exists no apparent connection between these weights and time domain require...

A new hybrid multi-objective, multivariable optimizer utilizing Strength Pareto Evolutionary Algorithm (SPEA), Non-dominated Sorting Differential Evolution (NSDE), and Multi-Objective Particle Swarm (MOPSO) has been created and tested. The optimizer features automatic switching among these algorithms to expedite the convergence of the optimal Pareto front in the objective function(s) space. The...

This paper presents the application of modified form of Particle Swarm Optimization as an optimization technique to the reconfiguration of electric distribution systems. The intended reconfiguration is an optimization and decision-making process which considers the maximization of the number of loads supplied associated to the minimization of the number of closed switches. A novel selection reg...

A multi-objective particle swarm optimization (MOPSO) approach is presented for generating Pareto-optimal solutions for reservoir operation problems. This method is developed by integrating Pareto dominance principles into particle swarm optimization (PSO) algorithm. In addition, a variable size external repository and an efficient elitist-mutation (EM) operator are introduced. The proposed EM-...

In this paper, the optimal power flow (OPF) problem is augmented to account for the costs associated with the loadfollowing stability of a power network. Load-following stability costs are expressed through the linear quadratic regulator (LQR). The power network is described by a set of nonlinear differential algebraic equations (DAEs). By linearizing the DAEs around a known equilibrium, a line...

AbstrAct: Muti-objective optimization deals with the simultaneous optimization of two or more conflicting objective functions in real-life systems. This paper deals with the multi-objective optimization in service systems. The goal of service systems is to provide cost-efficient service to customers, while at the same time, reducing the customer waiting time for service. In general, a low cost ...

The tuning of Linear Quadratic regulator (LQR) controllers is a challenge for researchers and plant operators. This paper presents a optimization and comparison of time response specification between Traditional ZN Tuning & Modified ZN Tuning controllers with Linear Quadratic Regulator (LQR) for a speed control of a separately excited DC motor. The goal is to determine which control strategy de...

In this paper we investigate the finite horizon linear quadratic regulation (LQR) problem for a linear continuous time system with time-varying delay in control input and a quadratic criterion. We assume that the time-varying delay is of a known upper bound, then the LQR problem is transformed into the optimal control problem for systems with multiple input channels, each of which has single co...

طلتخملا رطيسملل ميمصت مدقي ثحبلا اذه نا LQR/H-infinity .ةدكؤملا ريغو تاريغتملا ةددعتم ةمظنلأل مت ةفلك ةلاد ىلع ادامتعا ةعجارلا ةيذغتلا ةلاح تباوثل ىلثملا ميقلا داجيا ضرغل يئيزجلا دشحلا ةيلثما ةقيرط مادختسا تاددحم نيب طيلخ نع ةرابع يه ةحرتقملا ةفلكلا ةلاد نا.ةحرتقم LQR و H-infinity حرتقملا رطيسملا نا. ريغتملا ةددعتم ةمظنلأا ضوعي نا ةياع ةءافكبو عيطتسي رطيسملا ةوق تابثا ضرغل .ةيدكؤملا مدع دوجوب ...