Tuning of fractional order PID with master-slave stochastic multi-parameter divergence optimization method

Robotic manipulators have been widely used in industries, mainly to move tools into different specific positions. Thus, it has become necessary to have accurate knowledge about the tool position using forward kinematics after accessing the angular locations of limbs. This paper presents a simulation study in which an encoder attached to the limbs gathers information about the angular positions. The measured angles are applied to the Kalman Filter (KF) and its variants for state estimation. This work focuses on the use of fractional order controllers with a Two Degree of Freedom Serial Flexible Links (2DSFL) and Two Degree of Freedom Serial Flexible Joint (2DSFJ) and undertakes simulations with noise and a square wave as input. The fractional order controllers fit better with the system properties than integer order controllers. The KF and its variants use an unknown and assumed process and measurement noise matrices to predict the actual data. An optimisation problem is proposed to achieve reasonable estimations with the updated covariance matrices.

Download Full-text

Optimal solution of the fractional order breast cancer competition model

Scientific Reports ◽

10.1038/s41598-021-94875-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

H. Hassani ◽

J. A. Tenreiro Machado ◽

Z. Avazzadeh ◽

E. Safari ◽

S. Mehrabi

Keyword(s):

Breast Cancer ◽

Fractional Order ◽

Legendre Polynomials ◽

Numerical Experiments ◽

Optimal Solution ◽

Optimization Method ◽

Competition Model ◽

Basis Functions ◽

Cell Populations ◽

Operational Matrices

AbstractIn this article, a fractional order breast cancer competition model (F-BCCM) under the Caputo fractional derivative is analyzed. A new set of basis functions, namely the generalized shifted Legendre polynomials, is proposed to deal with the solutions of F-BCCM. The F-BCCM describes the dynamics involving a variety of cancer factors, such as the stem, tumor and healthy cells, as well as the effects of excess estrogen and the body’s natural immune response on the cell populations. After combining the operational matrices with the Lagrange multipliers technique we obtain an optimization method for solving the F-BCCM whose convergence is investigated. Several examples show that a few number of basis functions lead to the satisfactory results. In fact, numerical experiments not only confirm the accuracy but also the practicability and computational efficiency of the devised technique.

Download Full-text

Central Tunicate Swarm NFOPID-Based Load Frequency Control of the Egyptian Power System Considering New Uncontrolled Wind and Photovoltaic Farms

Energies ◽

10.3390/en14123604 ◽

2021 ◽

Vol 14 (12) ◽

pp. 3604

Author(s):

Hady H. Fayek ◽

Panos Kotsampopoulos

Keyword(s):

Power System ◽

Fractional Order ◽

Frequency Control ◽

Optimization Techniques ◽

Load Frequency Control ◽

The Novel ◽

Operating Condition ◽

Load Frequency ◽

Non Linear ◽

Fractional Order Pid

This paper presents load frequency control of the 2021 Egyptian power system, which consists of multi-source electrical power generation, namely, a gas and steam combined cycle, and hydro, wind and photovoltaic power stations. The simulation model includes five generating units considering physical constraints such as generation rate constraints (GRC) and the speed governor dead band. It is assumed that a centralized controller is located at the national control center to regulate the frequency of the grid. Four controllers are applied in this research: PID, fractional-order PID (FOPID), non-linear PID (NPID) and non-linear fractional-order PID (NFOPID), to control the system frequency. The design of each controller is conducted based on the novel tunicate swarm algorithm at each operating condition. The novel method is compared to other widely used optimization techniques. The results show that the tunicate swarm NFOPID controller leads the Egyptian power system to a better performance than the other control schemes. This research also presents a comparison between four methods to self-tune the NFOPID controller at each operating condition.

Download Full-text