Bacterial foraging-optimized PID control of a two-wheeled machine with a two-directional handling mechanism

Goher, Khaled; Fadlallah, Sulaiman O.

doi:10.1186/s40638-017-0057-3

Cited by 32 publications

(11 citation statements)

References 19 publications

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“…Although the above performance indices are generally applied as the criteria of designing PID controllers because evaluation is based on the frequency domain, they have many disadvantages such as the response result based on IAE and ISE having a long settling time and the derivation process of ITSE being complex [46], [47]. Therefore, [46], [47] proposed the new performance index given as Equation 8. It can be evaluated in the time domain by considering the transient response parameters, namely, the maximum overshoot (M p ), settling time (t s ), rise time (t r ) and steady state error (e ss ).…”

Section: Pid Controller and Objective Designmentioning

confidence: 99%

PID Controller Autotuning Design by a Deterministic Q-SLP Algorithm

Pongfai

Zhang

et al. 2020

IEEE Access

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The proportional integral and derivative (PID) controller is extensively applied in many applications. However, three parameters must be properly adjusted to ensure effective performance of the control system: the proportional gain (K P), integral gain (K I) and derivative gain (K D). Therefore, the aim of this paper is to optimize and improve the stability, convergence and performance in autotuning the PID parameter by using a deterministic Q-SLP algorithm. The proposed method is a combination of the swarm learning process (SLP) algorithm and Q-learning algorithm. The Q-learning algorithm is applied to optimize the weight updating of the SLP algorithm based on the new deterministic rule and closed-loop stabilization of the learning rate. To validate the global optimization of the deterministic rule, it is proven based on the Bellman equation, and the stability of the learning process is proven with respect to the Lyapunov stability theorem. Additionally, to demonstrate the superiority of the performance and convergence in autotuning the PID parameter, simulation results of the proposed method are compared with those based on the central position control (CPC) system using the traditional SLP algorithm, the whale optimization algorithm (WOA) and improved particle swarm optimization (IPSO). The comparison shows that the proposed method can provide results superior to those of the other algorithms with respect to both performance indices and convergence. INDEX TERMS Autotuning gain, central position control system, Q-learning algorithm, PID controller, swarm learning process algorithm, optimal control.

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Section: Pid Controller and Objective Designmentioning

confidence: 99%

PID Controller Autotuning Design by a Deterministic Q-SLP Algorithm

Pongfai

Zhang

et al. 2020

IEEE Access

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“…2, the vehicle's mathematical model is derived in order to relate the mechanical system's kinematics to the forces/torques applied to its links and to examine different model behaviours. The system equations of motion, details are provided in previous research that describes the system dynamics (Goher [52] ; Goher and Fadlallah [53,54] ), are demonstrated in the following highlycoupled differential equations:…”

Section: System Modellingmentioning

confidence: 99%

Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms

Goher

Fadlallah

2019

Int. J. Autom. Comput.

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This paper presents a novel five degrees of freedom (DOF) two-wheeled robotic machine (TWRM) that delivers solutions for both industrial and service robotic applications by enlarging the vehicle′s workspace and increasing its flexibility. Designing a twowheeled robot with five degrees of freedom creates a high challenge for the control, therefore the modelling and design of such robot should be precise with a uniform distribution of mass over the robot and the actuators. By employing the Lagrangian modelling approach, the TWRM′s mathematical model is derived and simulated in Matlab/Simulink®. For stabilizing the system′s highly nonlinear model, two control approaches were developed and implemented: proportional-integral-derivative (PID) and fuzzy logic control (FLC) strategies. Considering multiple scenarios with different initial conditions, the proposed control strategies′ performance has been assessed.

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“…Based on the study conducted by Goher and Fadlallah [ 25 ], the best optimized PID controller was the one optimized by IAE for the low percent overshoot and minimum settling time. MATLAB/Simulink model of the BFO-PID control method built to control the TWRM is illustrated in Fig.…”

Section: Control System Designmentioning

confidence: 99%

PID, BFO-optimized PID, and PD-FLC control of a two-wheeled machine with two-direction handling mechanism: a comparative study

Goher

Fadlallah

2018

Robot. Biomim.

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In this paper; three control approaches are utilized in order to control the stability of a novel five-degrees-of-freedom two-wheeled robotic machine designed for industrial applications that demand a limited-space working environment. Proportional–integral–derivative (PID) control scheme, bacterial foraging optimization of PID control method, and fuzzy logic control method are applied to the wheeled machine to obtain the optimum control strategy that provides the best system stabilization performance. According to simulation results, considering multiple motion scenarios, the PID controller optimized by bacterial foraging optimization method outperformed the other two control methods in terms of minimum overshoot, rise time, and applied input forces.

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Bacterial foraging-optimized PID control of a two-wheeled machine with a two-directional handling mechanism

Cited by 32 publications

References 19 publications

PID Controller Autotuning Design by a Deterministic Q-SLP Algorithm

PID Controller Autotuning Design by a Deterministic Q-SLP Algorithm

Control of a Two-wheeled Machine with Two-directions Handling Mechanism Using PID and PD-FLC Algorithms

PID, BFO-optimized PID, and PD-FLC control of a two-wheeled machine with two-direction handling mechanism: a comparative study

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