# ADVANCED CONTROL OF SOLAR PLANTS

###

# E.F. Camacho, M. Berenguel, F.R. Rubio

# Springer, London 1997

### DUE JULY 1997. C.296PP. HARD. ISBN 3-540-76144-6. L32.50

### A simulation software package for the ACUREX distributed solar collector
field (nonlinear distributed parameter model for simulation purposes described
in the book) can be obtained by contacting the authors or by clicking in the
following options:
- C VERSION.
- NOW FOR SIMULINK
1.3b!

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# ADVANCED CONTROL OF SOLAR PLANTS

### Preface

### List of figures

### List of tables

### Glossary

### 1. Introduction

1.1 The control of solar collector fields
1.2 Trends in process control

1.3 Modelling and Identification

1.4 Adaptive Control

1.5 Model-based Predictive Control (MPC)

1.6 Robust control, frequency domain control and optimal control

1.7 Artificial Intelligence Techniques

### 2. Description and dynamic models of the plant

2.1 Plant description
2.2 Objective of the control system

2.3 Data acquisition system

2.4 Dynamic simulation models of the field

2.5 Analysis of the dynamic response of the plant

2.6 Linear plant models

### 3. Basic control schema

3.1 Feedforward control
3.2 Fixed Ziegler-Nichols rule based PID controllers

3.3 Backup controller

3.4 Fine-tuned PID controller

### 4. Basic structures of adaptive control

4.1 Parameter estimation
algorithm
4.2 Supervisory levels

4.3 Adaptive Ziegler-Nichols rule based PID controllers

4.4 Pole-placement adaptive PI controller

4.5 Simulation analysis of PID controllers

4.6 Plant results with adaptive PI controllers

### 5. Model-based predictive control strategies

5.1 Generalized predictive
control (GPC)
5.2 Constrained generalized predictive control

5.3 Adaptive generalized predictive control

5.4 Robust adaptive model predictive control with bounded uncertainties

5.5 Gain scheduling generalized predictive control

5.6 GPC scheme with nonlinear prediction of the free response

### 6. Frequency domain control and robust optimal control

6.1 Adaptive
frequency domain internal model control
6.2 Linear Quadratic Gaussian Optimal Control (LQG)

### 7. Heuristic fuzzy logic control

7.1 Fuzzy logic inference scheme
7.2 Incremental fuzzy PI control (IFPIC)

7.3 Fuzzy logic controller (FLC)

### 8. Summary and concluding remarks

8.1 Performance indexes
8.2 Fixed PID controller

8.3 Adaptive GPC controller

8.4 Robust adaptive GPC controller

8.5 Gain scheduling GPC controller

8.6 Nonlinear GPC controller

8.7 Frequency domain adaptive IMC controller

8.8 Robust LQG/LTR controller

8.9 Heuristic incremental fuzzy PI controller (IFPIC)

8.10 Heuristic fuzzy logic controller (FLC)

8.11 Conclusions

### References

### Index