The Automatic Voltage Regulation (AVR) system which works within the synchronous generator[s] locally is defined as the closed loop control system that keeps the reactive power output at demanded value by adjusting exciter signal. Designing a proper control scheme for the AVR system to provide the desired level of voltage stability is an important research field. Nowadays, classic 1DOF PI-controller which takes into account only the load side disturbance is generally used in the AVR systems. In this study, to improve the robustness of this system towards the relatively severe disturbances caused from both load side and set point side, the 2DOF state feedback PI-controller which is tuned with a meta-heuristic optimization algorithm is proposed. Since only the error signal is minimized by using a simple cost function, this method can be applied simpler as independent to the system parameters, optimal coefficients are computed simpler. The superiority of the proposed controller is proved by applying stability, time-domain, frequency-domain and two different robustness analyses such as instantaneous and continuous disturbance analyses. It is observed from these analyses that the maximum overshoot and settling time obtained from the proposed control structure decrease more than a half. In addition, the immunity towards instantaneous and continuous disturbances significantly improve and the step responses in these cases stay in 2% band. At the end of the study, the implementation proposal related to the new control scheme is presented and interpreted in detail.

Robust 2DOF state-feedback PI-controller based on meta-heuristic optimization for automatic voltage regulation system.

Passengers are more susceptible to motion sickness (MS) than the drivers because during cornering, they tilt their heads according to lateral acceleration direction, while the drivers tilt their heads against it. During slalom driving, high lateral acceleration that resulted from inappropriate wheel’s turning will increase the severity level of MS as it contributes to a larger passenger’s head roll angle towards the lateral acceleration direction. Thus, for an autonomous vehicle, it is necessary to design a smooth lateral control to obtain appropriate wheel angle to prevent high lateral acceleration. This study proposes an inner-loop lateral control strategy which utilized head roll angle as the controlled variable to generate corrective wheel angle to reduce the lateral acceleration. Firstly, an estimation model of driver’s and passenger’s head roll angle is developed by radial basis function network method based on the correlation between lateral acceleration and occupant’s head roll angle. The driver’s and passenger’s models are considered as the reference and the controlled subject, respectively. Secondly, a fuzzy logic controller is adopted to generate corrective wheel angle based on the head roll angle responses. The reduction of the lateral acceleration caused by the corrective wheel angle minimized the passenger’s head roll angle and hence mitigated their MS level. Simulation results show 3.25% and 10.86% reduction of motion sickness incidence in a single lap and ten laps after the proposed control strategy is applied. It is expected that the proposed control strategy will contribute to the MS mitigation study in autonomous vehicle field.

Lateral control strategy based on head movement responses for motion sickness mitigation in autonomous vehicle

Two degree of freedom fractional PI scheme for automatic voltage regulation

Two wheeled inverted pendulum (TWIP) resembles many industrial as well as real life applications. TWIP is underactuated, nonlinear and unstable system. Therefore, it is widely used as benchmark for illustrating control concepts, theories, and algorithms that deal with these challenges. The main motivations of this paper are designing controllers that deal with lack of information that accompanying an inexpensive cheap TWIP and verified its stability, proper speed, robustness and smooth tracking. Consequently, intelligent technique instead of conventional ones that depends on mathematical models should be used. In this article hybrid controllers, consisting of fuzzy controllers and three mode controllers’ (PID), are developed. Two major techniques are used, Mamdani-Like Fuzzy and Fusion-Based function, to design five controllers. Moreover, dynamic indices and steady state indices are implemented to choose the most proper controllers among various designed ones. A new criterion is defined to measure steady state performance of oscillation. All controllers were tested in real-time to control the angle of the TWIP for stability and disturbance rejection. The experimental results showed that both strategies of Mamdani-Like Fuzzy and Fusion-Based fuzzy can control and balance adequately the TWIP, but the PD-Like fuzzy yielded more better performance.

Real-time Mamdani-like fuzzy and fusion-based fuzzy controllers for balancing two-wheeled inverted pendulum

This paper presents the design of a fuzzy tracking controller for balancing and velocity control of a Two-Wheeled Inverted Pendulum (TWIP) mobile robot based on its Takagi-Sugino (T-S) fuzzy model, fuzzy Lyapunov function and non-parallel distributed compensation (non-PDC) control law. The T-S fuzzy model of the TWIP mobile robot was developed from its nonlinear dynamical equations of motion. Stabilization conditions in a form of linear matrix inequalities (LMIs) were derived based on the T-S fuzzy model of the TWIP mobile robot, a fuzzy Lyapunov function and a non-PDC control law. Based on the derived stabilization conditions and the T-S fuzzy model of the TWIP mobile robot, a state feedback velocity tracking controller was then proposed for the TWIP mobile robot. The balancing and velocity tracking performance of the proposed controller was investigated via simulations. The simulation result shows the effectiveness of the proposed control scheme.

https://www.beei.org/index.php/EEI/article/download/1594/1141

Velocity control of a two-wheeled inverted pendulum mobile robot: a fuzzy model-based approach

This paper reports the first attempt to tune gain values in proportional-integral-derivative (PID) controllers using an optimizer called simulated Kalman filter (SKF) algorithm. Compared to another well-established optimizer, such as particle swarm optimization (PSO), the SKF algorithm is a relatively new optimizer and most importantly, the SKF algorithm has not been applied to parameter tuning of PID controller. A finding based on automatic voltage regulator system suggests that the SKF algorithm has promising potentials to be a good tuning method in PID controller.

An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system

Designing a control strategy of two-wheeled wheelchair is a very challenging task due to the unstable and highly nonlinear system. In the paper the system is modeled by mimicking a double-link inverted pendulum concept and the mathematical equations is derived using Euler-Lagrange method. Then the state-space representation is applied to the Simulink block diagram in Matlab. The control parameter of the system is compared between trial-and-error method and Particle Swarm Optimization (PSO) algorithm. This strategy is to find the optimal value for the system to get better performance. The system will be simulated using Fuzzy Logic Control (FLC) and FLC-PSO using Matlab/Simulink environment. Simulation results show that the FLC-PSO is better than FLC in terms of overshoot and settling time.

Two-wheeled wheelchair stabilization control using fuzzy logic controller based particle swarm optimization

In this paper, an Interval Type-2 Fuzzy Logic Control (IT2FLC) is proposed to control a two-wheeled wheelchair system which mimics double-links inverted pendulum and known as highly nonlinear, unstable and complex system. The control structures of the two-wheeled wheelchair is based on IT2FLC for balancing and maintaining stability of two-wheeled wheelchair system in the upright position. This paper is aimed to develop a 3-Dimensional (3D) model of two-wheeled wheelchair using a SimWise 4D (SW4D) software, which replace a complex mathematical representation that is obtained using long equation and derivation. The movement of the system is visualized using the SW4D as it is integrated with Matlab Simulink. Simulation results show that the IT2FLC give a good performance in term of tilt angle at zero degree in the upright position.

Two-wheeled wheelchair stabilization using interval type-2 fuzzy logic controller

In this paper, an Interval Type-2 Fuzzy Logic Control (IT2FLC) is proposed to control a stabilization of two-wheeled wheelchair system with moving payload. The two-wheeled wheelchair system is similarly with double-links inverted pendulum system but with additional of movable payload up to 0.3 m to reach a higher level of height. Thus, this two-wheeled wheelchair configuration becomes more complex, unstable and highly nonlinear system. The 300 N concentrated force is applied at the back of the wheelchair seat in two conditions; in the initial condition before the payload is lifted and in the maximum height of the payload to test the robustness of the controller. SimWise 4D (SW4D) software is used to develop a 3-Dimensional (3D) model of the two-wheeled wheelchair, which replaces a complex mathematical representation. The SW4D is used to visualize the movement of the system as it is integrated with Matlab Simulink. IT2FLC will be compared with Fuzzy Logic Control Type 1 (FLCT1) and the simulation results show that the IT2FLC give a good performance in term of angular position of both links in the upright position and maintain stable.

Normaniha Abdul Ghani

Papers

An application of simulated Kalman filter optimization algorithm for parameter tuning in proportional-integral-derivative controllers for automatic voltage regulator system

Two-wheeled wheelchair stabilization control using fuzzy logic controller based particle swarm optimization

Two-wheeled wheelchair stabilization using interval type-2 fuzzy logic controller

Stabilization of Two-wheeled Wheelchair with Movable Payload Based Interval Type-2 Fuzzy Logic Controller