Tuning of Nonlinear PID Controller for TRMS Using Evolutionary Computation Methods

In this paper, the Twin rotor MIMO system (TRMS) is tuned by Nonlinear PID controller using Evolutionary Computation methods. The proposed Nonlinear PID controller, used to tune TRMS, improves the system performance with additional degrees of freedom. Evolutionary Computation methods such as Differential Search Algorithm (DSA), real coded Genetic Algorithm (RGA) with simulated binary crossover (SBX) and Particle Swarm optimization (PSO) and Gravitational Search Algorithm (GSA) are used to determine the optimal parameters of the proposed controller by minimizing Integral Square Error (ISE) for rotor response of TRMS. SIMULINK MATLAB software is used for simulating the system. The statistical performance of the controller is analysed among twenty independent trials by taking best, worst, mean and standard deviations of ISE. Simulation results reveal that TRMS system tuned by nonlinear PID controller using Particle Swarm optimization (PSO) is better than the other methods

Evolutionary algorithms based design of multivariable PID controller. Expert Syst Appl 2009; 36: 9159–9167

a b s t r a c t In this paper, performance comparison of evolutionary algorithms (EAs) such as real coded genetic algorithm (RGA), modified particle swarm optimization (MPSO), covariance matrix adaptation evolution strategy (CMAES) and differential evolution (DE) on optimal design of multivariable PID controller design is considered. Decoupled multivariable PI and PID controller structure for Binary distillation column plant described by Wood and Berry, having 2 inputs and 2 outputs is taken. EAs simulations are carried with minimization of IAE as objective using two types of stopping criteria, namely, maximum number of functional evaluations (Fevalmax) and Fevalmax along with tolerance of PID parameters and IAE. To compare the performances of various EAs, statistical measures like best, mean, standard deviation of results and average computation time, over 20 independent trials are considered. Results obtained by various EAs are compared with previously reported results using BLT and GA with multi-crossover approach. Results clearly indicate the better performance of CMAES and MPSO designed PI/PID controller on multivariable system. Simulations also reveal that all the four algorithms considered are suitable for off-line tuning of PID controller. However, only CMAES and MPSO algorithms are suitable for on-line tuning of PID due to their better consistency and minimum computation time

Optimal placement of mobile antenna in an urban area using evolutionary multiobjective optimization

The optimized placements of mobile antennas (MA) in an existing high traffic urban area are identified using evolutionary multiobjective optimization algorithms (EMOA). The design parameters such as (x, y) coordinates, transmitting power, height, and tilt are considered. The objectives are coverage and cost where as the inequality constraints are handover, traffic demand, and overlap. Modified NSGA-II (MNSGA-II) is preferred to improve the non dominated solutions. A detailed study is performed about physical and geometrical structure of propagation environment. Four different case studies are performed. The simulation results reveal that Hata–Okumura path loss model is more suited. MNSGA-II is able to determine optimal MA parameters for multiobjective case studies

Design of robust multi-loop PI controller for improved disturbance rejection with constraint on minimum singular value

Disturbance rejection performance optimization with constraints on robustness for a multivariable process is commonly encountered in industrial control applications. This paper presents the tuning of a multi-loop Proportional Integral (PI) controller method to enhance the performance of load disturbance rejection using evolutionary optimization. The proposed design methodology is formulated to minimize the load disturbance rejection response and the input control energy under the constraints of robust stability. The minimum singular value of multiplicative uncertainty is considered a multi-loop system robust stability indicator. Optimization is performed to achieve the same, or higher level than the most-explored Direct Synthesis (DS) based multi-loop PI controller, which is derived from a conventional criterion. Simulation analysis clearly proved that the proposed multi-loop PI controller tuning method gives better disturbance rejection, and either, the same or a higher level of robust stability when compared to the DS-based multi-loop PI controller

Unified design method of time delayed PI controller for first order plus dead-time process models with different dead-time to time constant ratio

The time delay element present in the PI controller brings dead-time compensation capability and shows improved performance for dead-time processes. However, design of robust time delayed PI controller needs much responsiveness for uncertainty in dead-time processes. Hence in this paper, robustness of time delayed PI controller has been analyzed for First Order plus Dead-Time (FOPDT) process model. The process having dead-time greater than three times of time constant is very sensitive to dead-time variation. A first order filter is introduced to ensure robustness. Furthermore, integral time constant of time delayed PI controller is modified to attain better regulatory performance for the lag-dominant processes. The FOPDT process models are classified into dead-time/lag dominated on the basis of dead-time to time constant ratio. A unified tuning method is developed for processes with a number of dead-time to time constant ratio. Several simulation examples and experimental evaluation are exhibited to show the efficiency of the proposed unified tuning technique. The applicability to the process models other than FOPDT such as high-order, integrating, right half plane zero systems are also demonstrated via simulation examples