The instrumentation, i.e., sensors and actuators, in feedback control systems often contain nonlinearities, such as saturation, deadzone, quantization, etc. Standard synthesis techniques, however, assume that the actuators and sensors are linear. This technical note is intended to modify the LQR/LQG methodology into the so-called Instrumented LQR/LQG (referred to as ILQR/ILQG), which allows for...

We present a comparison of a LQR controller and Q-learning on a simulation of a triple inverted pendulum. While the LQR controller was able to balance the pendulum, Qlearning was unable due to memory and computing limitations. We examine the strengths and weaknesses of each method and compare their abilities.

M. Janga Reddy Department of Civil Engineering, Indian Institute of Technology Bombay, Mumbai 400076, India D. Nagesh Kumar (corresponding author) Department of Civil Engineering, Indian Institute of Science, Bangalore 560012, India E-mail: [email protected] Optimal allocation of water resources for various stakeholders often involves considerable complexity with several conflicting go...

A hybrid proportional double derivative and linear quadratic regulator (PD2-LQR) controller is designed for altitude (z) attitude (roll, pitch, yaw) control of a quadrotor vehicle. The derivation mathematical model the formulated based on Newton–Euler approach. An appropriate controller’s parameter must be obtained to obtain superior performance. Therefore, we exploit advantages nature-inspired...

A framework for the design and simulation of a building envelope and an HVAC system is presented. Building models are first captured in Modelica to leverage its rich building component library and then imported into Simulink to exploit its strong control design environment that enables efficient control design and implementation. Four controllers with different computational intensity are consi...

Reconfigurable Manufacturing System (RMS) justifies the need of hour by combining the high throughput of dedicated manufacturing system with the flexibility of flexible manufacturing systems. At the heart of RMS lies the Reconfigurable Machine Tools which are capable of performing multiple operations in its existing configurations and can further be reconfigured into more configurations which m...

The application of multi objective model predictive control approaches is significantly limited with computation time associated with optimization algorithms. Metaheuristics are general purpose heuristics that have been successfully used in solving difficult optimization problems in a reasonable computation time. In this work , we use and compare two multi objective metaheuristics, Multi-Object...

Software cost estimation is the process of predicting the effort required to develop a software system. The basic input for the software cost estimation is coding size and set of cost drivers, the output is Effort in terms of Person-Months (PM’s). Here, the use of support vector regression (SVR) has been proposed for the estimation of software project effort. We have used the COCOMO dataset and...

In this paper we compare the behaviour of the LQR solution for a finite platoon model with its infinite version. We give examples where these are similar and some where they are quite different. For the scalar case we obtain sufficient conditions for the LQR solutions to be similar by relating the Toeplitz approximations to circulant approximating systems.

Particle Swarm Optimization (PSO) has received increased attention in the optimization research community since its first appearance. Regarding multi-objective optimization, a considerable number of algorithms based on Multi-Objective Particle Swarm Optimizers (MOPSOs) can be found in the specialized literature. Unfortunately, no experimental comparisons have been made in order to clarify which...