PID controller design of nonlinear systems using an improved particle swarm optimization approach

The objective of this paper is to design controller for non-linear power system using Direct Feedback Linearization technique to improve the transient stability and to achieve better voltage regulation. In case of fault in the power system, power angle and the terminal voltage are the parameters which are to be monitored. The simulation has been carried out taking different values of initial power angles and results were obtained for power angle and terminal voltage. To overcome the demerits of DFL-LQ optimal controller and DFL voltage regulator, co-ordinated controller is proposed. Simulation results show that transient stability of a power system under a large sudden fault has been improved by using co-ordinated controller.

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“…Metaheuristic optimization technique like GA, Tabu search, simulated annealing, bacteria foraging, particle swarm optimization. [8], [10] …”

Section: Controller Design Techniquesmentioning

confidence: 99%

Analysis and design of different controllers for non-linear power systems

Chaudhary

Singh

2013

IJET

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“…In the given block diagram M is the mass of cart, L is the half length of the pendulum, m is a mass of the pendulum, θ is the angle of the pendulum to its vertical axis at the stable condition and X is the position of the cart. Dynamics of the inverted pendulum with cart for the angular acceleration is proposed by Chang and Shih (2010). …”

Section: Inverted Pendulummentioning

confidence: 99%

Fuzzy-cuckoo controller for nonlinear system

Nema

Padhy

Prabhash

2017

IJSCC

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This paper presents the novel fuzzy-cuckoo controller for the nonlinear system. The scaling factor of the fuzzy logic controller (FLC) has determined by using nature inspired cuckoo search optimisation. Controller design using FLC is a model-free approach. Auto-tuning of the controller parameters have been done using cuckoo optimisation. In this design, Sugeno type's fuzzy inference system has used to design the controller for the improvement of system's performance, which takes less computational time. Sum of the integral square error (ISE) and maximum overshoot (M p ) have been taken as an objective function for optimisation purpose. Tracking problem of inverted pendulum and stability analysis of the Van der Pol oscillator (VDPO) have considered as an examples to validate the proposed design and real time experiment has also performed on single conical tank system.

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“…Chang and Shih [8] have developed an IPSO algorithm to tune the PID controller for a non linear inverted pendulum system. In this, an improved velocity updating equation is proposed to improve the algorithm convergence and it is given in Eqn .4.…”

Section: B Improved Pso Algorithmmentioning

confidence: 99%

“…Recent work utilises the heuristic procedures, such as Particle Swarm Optimization [6,7], Improved PSO [8], Bacterial Foraging Optimization [9,10], Hybrid algorithm [11,12], Bat Algorithm [13], Firefly Algorithm [14], Teaching Learning Based Optimization [15], etc.…”

Section: Introductionmentioning

confidence: 99%

Design of PID Controller for SISO and TITO Systems – A Study with Heuristic Algorithms

Manibharathi¹,

Kumar²,

Kumaran³

et al. 2017

IJET

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Keyword-PID controller, SISO system, MIMO system, Heuristic approaches, Performance analysis I. INTRODUCTION In chemical industry, most of the important processing units are highly non-linear in nature and for economical and/or safety reasons, these process loops to be operated in safe regions with the help of a PID controller [1][2][3]. Based on its operating region and its non-linearity, these loops can be modelled as SISO and MIMO systems. During the closed loop operation, optimized controller parameters for such systems are essential to minimize the waste and to maximize the production rate. Fine tuning the controller parameters for non-linear systems are highly complex than open loop stable systems. Hence, in recent years, heuristic algorithm assisted approaches are widely adopted by the researchers.

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PID controller design of nonlinear systems using an improved particle swarm optimization approach

Cited by 161 publications

References 8 publications

Analysis and design of different controllers for non-linear power systems

Analysis and design of different controllers for non-linear power systems

Fuzzy-cuckoo controller for nonlinear system

Design of PID Controller for SISO and TITO Systems – A Study with Heuristic Algorithms

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