Fukiko Kawai

Parameter optimization of model predictive control using PSO

Among various control methods, model predictive control (MPC) becomes one of the major control strategies and has many successful applications. This paper presents an automatic tuning method of MPC using particle swarm optimization (PSO). One of the challenges in MPC is how the control parameters can be tuned for various target plants, and usage of PSO for automatic tuning is one of the solutions. The tuning problem of MPC is formulated as an optimization problem and PSO is applied as the optimization techniques. PSO is one of meta-heuristic methods which are known to search a global optimum at a relatively high ratio and with no use of a gradient. The numerical results for simple examples show the effectiveness of the proposed PSO-based automatic tuning method.

Automatic Tuning of Model Predictive Control Using Particle Swarm Optimization

This paper presents an automatic tuning method of model predictive control (MPC) using particle swarm optimization (PSO). Although conventional PID is difficult to treat constraints and future plant dynamics, MPC can treat this issues and practical control can be realized in various industrial problems. One of the challenges in MPC is how control parameters can be tuned for various target plants and usage of PSO for automatic tuning is one of the solutions. The numerical results show the effectiveness of the proposed PSO-based automatic tuning method

Automatic Tuning for Model Predictive Control: Can Particle Swarm Optimization find a better parameter?

This paper presents an automatic tuning method of model predictive control (MPC) using particle swarm optimization (PSO). Although it is difficult for unskilled control designers to tune MPC weight parameters, PSO can solve this issues and practical control can be realized in various industrial problems. One of the challenges in MPC is how control parameters can be tuned for various target plants and usage of PSO for automatic tuning is one of the solutions. The numerical results show the effectiveness of the proposed PSO-based automatic tuning method.

The ε constrained differential evolution approach for optimal operational planning of energy plants

This paper introduces optimal operational planning of energy plants via the ε constrained differential evolution. In order to generate optimal operational planning for energy plants, startup/shutdown status and/or input/output values of the facilities at each control interval should be determined. The problem can be formulated as a large-scale mixed-integer nonlinear problem (MINLP). Metaheuristics (MHs) is one of the solutions for MINLP. If the formulated MINLP has various equality and inequality constraints, it remains difficult to solve it without parameters tuning. In this paper, to overcome the difficulty, we propose an improved differential evolution approach using the ε constrained method for MINLP. Results show the effectiveness of the proposed method compared with conventional methods.

An Industrial Model Based Disturbance Feedback Control Scheme

Abstract This paper presents a model based disturbance feedback control scheme. Industrial process systems have been traditionally controlled by using relay and PID controller. However these controllers are affected by disturbances and model errors and these effects degrade control performance. The authors propose a new control method that can decrease the negative impact of disturbance and model errors. The control method is motivated by industrial practice by Fuji Electric. Simulation tests are examined with a conventional PID controller and the disturbance feedback control. The simulation results demonstrate the effectiveness of the proposed method comparing with the conventional PID controller.

PID control with robust disturbance feedback control

Disturbance Feedback Control (DFC) is a technique, originally proposed by Fuji Electric, for augmenting existing control systems with an extra feedback for attenuation of disturbances and model errors. In this work, we analyze the robustness and performance of a PID-based control system with DFC. A multiplicative uncertainty model is used to represent mismatch between a nominal model and the actual plant, and expressions for robust stability, nominal and robust performance are derived. We propose a simple grid-based search algorithm that can be used to find DFC gains to achieve robust stability and performance (if such gains exist). Finally, two different simulation case studies are evaluated and compared. Our numerical studies indicate that better performance can be achieved with the proposed method compared with a conservatively tuned PID controller and comparable performance can be achieved when compared with an H-infinity controller.

An LMI approach for robust design of disturbance feedback control

Disturbance Feedback Control (DFC) is a control technique that augments robustness of existing control systems with an extra feedback loop for the purpose of attenuation of disturbances and model errors. In this work, we propose a DFC design method based on output feedback control via Linear Matrix Inequalities (LMIs). A parametric uncertainty model is used to represent mismatches between a nominal model and the actual plant. LMIs are formulated for the control design using a linearizing change of variables, the bounded real lemma, and regional pole placement. Simulation results demonstrate that the proposed method improved the performance of the existing feedback loop.

Robust & anti-windup disturbance feedback control for water chiller systems

Disturbance Feedback Control (DFC) is a technique in which an existing controller is augmented with an additional loop. It was originally proposed by Fuji Electric in 1980, and has been applied in Factory Automation (FA). This paper proposes a robust DFC including the anti-windup controllers for process control. The proposed method is designed in two steps; firstly, the robust DFC without saturation is designed by Linear Matrix Inequality (LMI) approach, and then LMI technique are used again for stabilizing the closed loop system with anti-windup compensator. The simulation results for the water chiller system shows the improvements of control performances, and keeps stability of the system when the saturation blocks are introduced.