TAILIEUCHUNG - A new multiobjective performance criterion used in PID tuning optimization algorithms

In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions. | A new multiobjective performance criterion used in PID tuning optimization algorithms

• Toán học
• Multiobjective optimization
• Particle Swarm Optimization
• PID controller
• AVR system
• PID tuning optimization algorithms
• Multiobjective optimization in delivering pharmaceutical products
• Delivering pharmaceutical products
• Disrupted vehicle routing problem
• Improved multiobjective local search
• Variable neighborhood search
• Multiobjective programming
• Sum of ratio
• Multiobjective linear fractional programming
• Optimality and duality
• Saddle point criteria
• Nonsmooth semi infinite
• Generalized convexity
• Support functions
• D type I n set functions
• Duality results
• Multiobjective nonlinear fractional programming problem
• Optimization problems
• Substantial efficiency
• Scalarization function
• Stable problem
• Quasi substantial efficiency
• Multiobjective optimization problems
• Higher order η – bonvexity
• Strict minimizers
• Second order dualit
• Mond Weir type dual
• Non differentiable multiobjective optimization problem
• Information sciences
• Multiobjective combinatorial optimization problems
• Well spread set
• Well spread non dominated points
• State of the art
• Nonsmooth multiobjective programming
• Optimality conditions
• Mixed dualit
• Dynamic Optimization
• Neural Network
• Algorithm Convergence
• Ant Programming
• Green Manufacturing
• Colony Algorithms
• Electronic Engineering
• Distributed Generation
• Fuzzy decision
• Multi objective optimization
• Pareto solution
• Self adaptation genetic algorithm
• Optimizing turning process
• Genetic algorithm
• Pareto optimal
• Optimization solution
• báo cáo khoa học
• báo cáo hóa học
• công trình nghiên cứu về hóa học
• tài liệu về hóa học
• cách trình bày báo cáo
• Using Multiobjective
• Multicriteria Analysis
• Open AccessMeta Heuristic
• Optimization Techniques
• Heuristic Algorithms
• Geometric programming
• Max min operator
• Gravel box problem
• Fuzzy optimization technique
• Multiobjective problem
• Multi objective matrix game
• Fuzzy goal
• Max min solution
• Optimization problem
• Linear programming problem
• French nuclear fleet
• Sodium Fast Reactors
• Feet evolution scenarios
• CESAR depletion code
• CEA’s Nuclear Energy Division
• BMC Bioinformatics
• Microarray gene expression data
• Developmental biology
• Eigen gene
• Affirmation score