A Hybrid Control Approach Based on the Combination of PID Control with LQR Optimal Control

Abstract

Proportional Integral Derivative (PID) is the most popular controller that is commonly used in wide industrial applications due to its simplicity to realize and performance characteristics. This technique can be successfully applied to control the behavior of single-input single-output (SISO) systems. Extending the using of PID controller for complex dynamical systems has attracted the attention of control engineers. In the last decade, hybrid control strategies are developed by researchers using conventional PID controllers with other controller techniques such as Linear Quadratic Regulator (LQR) controllers. The strategy of the hybrid controller is based on the idea that the parameters of the PID controller are calculated using gain elements of LQR optimal controller. This chapter focuses on design and simulation a hybrid LQR-PID controller used to stabilize elevation, pitch and travel axes of helicopter system. An improvement in the performance of the hybrid LQR-PID controller is achieved by using Genetic Algorithm (GA) which, is adopted to obtain best values of gain parameters for LQR-PID controller.

Design of a novel intelligent adaptive fractional-order proportional-integral-derivative controller for mitigation of seismic vibrations of a building equipped with an active tuned mass damper

“…The careful selection of a suitable control algorithm plays a pivotal role in the effective implementation of a smart structure. This is because the control algorithm employed to regulate the control force has a substantial influence on the performance of control systems [25,26], Linear Quadratic Gaussian (LQG) [27], Instantaneous Optimal Control [2], Independent Modal Space Control [28], Bounded State Control [13], Generalized Feed-Back Control [29], Sliding Mode Control (SMC) [30], Wavelet-based control algorithm [31], H ∞ and H 2 [32], Open Loop Control [33], Clipping control [34], Direct Lyapunov control [35], Bang-bang control [36], Maximum Energy Dissipation [37], Fuzzy logic control [38,39], Neural network [40,41], and Instantaneous Optimal control [42] are the example of the well-known control strategies. According to previous studies, the classical proportional-integral-derivative (PID) controller has demonstrated efficacy [43,44].…”