A quadcopter control system is a fundamentally difficult and challenging problem because its dynamics modelling highly nonlinear, especially after accounting for the complicated aerodynamic effects. Plus, variables are interdependent coupled in nature. There six controllers studied analysed this work which (1) Proportional–Integral–Derivative (PID), (2) Proportional-Derivative (PD), (3) Linear ...

In this article, we discuss the design and implementation of a receding horizon control (RHC) which will be used to represent the control for the baroreceptor loop in the human cardiovascular system (CVS). This control will be applied to a model of the CVS developed in a previous work by Kappel and Peer. In that earlier work, a linear quadratic control strategy (LQR) was implemented to represen...

Design of power system stabilizer using Linear Quadratic Regulator (LQR) technique. Designs that ignore noise in a plant are likely to fail when implemented in actual conditions. Presence of the noise, which results in LQR output oscillating with very small magnitude. This type of unwanted noisy output is eliminated using Linear Quadratic Gaussian (LQG) Regulator. This paper presents techniques...

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...

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...

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 ...

Although it is well known that fuzzy learning controller is powerful for nonlinear systems, it is very difficult to apply a learning method if they are unstable. An unstable system diverges for impulse input. This divergence makes it difficult to learn the rules unless we can find the initial rules to make the system stable prior to learning. Therefore, we introduced LQR(Linear Quadratic Regula...

Linear Quadratic Regulator (LQR) is an optimal multivariable feedback control approach that minimizes the excursion in state trajectories of a system while requiring minimum controller effort. The behaviour of a LQR controller is determined by two parameters: state and control weighting matrices. These two matrices are main design parameters to be selected by designer and greatly influence the ...