This paper presents a parallel elite genetic algorithm (PEGA) and its application to global path planning for autonomous mobile robots navigating in structured environments. PEGA, consisting of two EGAs along with migration operator, takes advantages maintaining better population diversity, inhibiting premature convergence, keeping parallelism comparison conventional GAs. initial feasible generated from the PEGA planner is then smoothed using cubic B-spline technique, order construct...

This paper presents an adaptive control using radial-basis-function neural networks (RBFNNs) for a two-wheeled self-balancing scooter. A mechatronic system structure of the scooter driven by two dc motors is briefly described, and its mathematical modeling incorporating frictions between wheels motion surface derived. By decomposing overall into subsystems (yaw mobile inverted pendulum), one proposes controllers RBFNN to achieve yaw control. The performance merit proposed are exemplified...

An adaptive predictive control with recurrent neural network prediction for industrial processes is presented. The law integral action derived based on the minimization of a modified performance criterion. stability and steady-state closed-loop system are well studied. Numerical simulations reveal that proposed gives satisfactory tracking disturbance rejection two illustrative nonlinear systems time-delay. Experimental results temperature variable-frequency oil-cooling process show efficacy...

The paper presents an adaptive dimming technique to reduce backlight power consumption and enhance image contrast for global applications. proposed consists of two new algorithms: algorithm enhancement algorithm. backlight-dimming obtains appropriate 0% 50% reduction depending on characteristics the data. not only reduces adverse effect saving, but also improves 20.75% ratio average. Numerous simulation results are used illustration effectiveness merits technique. Experimental conducted show...

In this paper, an intelligent leader-following consensus formation control method using recurrent neural networks (RNNs) is presented for a team of uncertain small-size unmanned helicopters (SSUHs). After brief description the dynamic model each SSUH by set multivariable fourth-order state equations, leader-follower multi-SSUH system with virtual leader modeled directed graph theory. An adaptive approach proposed to fly together all follower SSUHs in RNN online learn uncertainties, tracking,...

This paper develops a novel system hardware structure and systematic digital signal processing algorithms for self-localization of an autonomous mobile robot by fusing dead-reckoning ultrasonic measurements. The multisensorial (DR) subsystem is established based on the optimal filtering first heading readings from magnetic compass, rate-gyroscope two encoders mounted wheels, thereby computing dead-reckoned location estimate. localization consists one transmitter radio-frequency (RF)...

This paper introduces a novel hardware system structure and systematic digital signal processing algorithms for the automatic localization of an autonomous mobile robot by merging dead-reckoning ultrasonic measurements. The multisensorial (DR) subsystem is based on optimal filtering that merges heading readings from magnetic compass, rate-gyroscope, two encoders mounted wheels to compute dead-reckoned location estimate. consists one transmitter radio-frequency (RF) controlled switch at known...

This paper presents an embedded adaptive robust controller for trajectory tracking and stabilization of omnidirectional mobile platform with parameter variations uncertainties caused by friction slip. Based on a dynamic model the platform, to achieve point stabilization, tracking, path following is synthesized via backstepping approach. then implemented into high-performance field-programmable gate array chip using hardware/software codesign technique system-on-a-programmable-chip design...

Control systems education often needs to design interesting hands-on exercises that keep students interested in the control theory presented lectures. These include system modeling, analyses, controller syntheses, implementation, experimentation, and performance evaluation of a system. This paper presents an pedagogical tool, self-balancing human transportation vehicle (HTV), for teaching feedback concepts undergraduate electrical, mechatronic, mechanical engineering environments. Such tool...

This paper presents a coarse-grain parallel deoxyribonucleic acid (PDNA) algorithm for optimal configurations of an omnidirectional mobile robot with five-link robotic arm. efficient PDNA is proposed to search the global optimum redundant inverse kinematics problem minimal movement, thereby showing better population diversity and avoiding premature convergence. Moreover, pipelined hardware implementation, hardware/software co-design, System-on-a-Programmable-Chip (SoPC) technology on...

This paper develops a multivariable self-tuning predictive control for improving set-point tracking performance, disturbance rejection, and robustness of temperature system an extruder barrel in plastic injection molding process. The stochastic discrete-time mathematical model is built its unknown parameters are identified by using the recursive least-squares estimation method. derived based on minimization generalized performance criterion. A real-time algorithm proposed then implemented...

This paper presents an adaptive decoupling temperature control for extrusion barrel in a plastic injection molding process. After establishing stochastic polynomial matrix model of the system, corresponding system representation was then developed. The design derived based on minimization generalized predictive performance criterion. set-point tracking, disturbance rejection, and robustness capabilities proposed method can be improved by appropriate adjustments to tuning parameters criterion...

This paper presents methodologies and technologies for ultrasonic localization pose tracking of an autonomous mobile robot (AMR) by using a fuzzy adaptive extended information filtering (FAEIF) scheme. A novel system, which consists two transmitters three receivers, is proposed to estimate both the static dynamic position orientation AMR. FAEIF presented improve estimation accuracy robustness while system lacks sufficient complete models or process measurement noise varies with time. Static...

This paper proposes a novel adaptive predictive Proportional-Integral-Derivative (PID) controller utilizing an output recurrent fuzzy broad learning systems (ORFBLS) for Multiple-Input Multiple-Output (MIMO) digital control systems, aiming to effectively adapt changing setpoints and dynamic environments. The proposed controller, MIMO ORFBLS-APPID in short, is extend the application of ORFBLS as adjustment mechanism PID gains parameters, where gain matrices are automatically tuned over time...

Abstract This paper presents an adaptive Lyapunov‐based controller with integral action for small‐scale helicopters carrying out airdrop missions. The proposed is designed via backstepping. Unlike the approximate modeling approaches, where coupling effect of helicopter neglected, method developed according to a complete dynamic model such that closed‐loop system guaranteed be globally ultimately bounded. Two numerical simulations airdrops are conducted exemplify merits controller. Through...