This course will discuss the handling and simulation of control systems through the state space method, estimate dynamic characteristics,
and control system design methods through modern control theory.
This course will discuss the handling and simulation of control systems through the state space method, estimate dynamic characteristics,
and control system design methods through modern control theory. Specifically, equation of state will be introduced and its
relation to transfer functions will be explained. Then, the controllability and observability concepts based on coordinate
conversion will be introduced. After raising basic theories relating to control system stabilization, control system design
methods through modern control theory and several examples of application will be described.
- Students can understand of modern control theory.
- Students can design a control system based on state-space approach.
- Students can apply the control design theory to practical systems.
| Report | Examination | Total. | |
|---|---|---|---|
| 1. | 15% | 20% | 35% |
| 2. | 15% | 20% | 35% |
| 3. | 15% | 15% | 30% |
| Total. | 45% | 55% | - |
| Class schedule | HW assignments (Including preparation and review of the class.) | Amount of Time Required | |
|---|---|---|---|
| 1． | Equation of state and transfer functions | Exercises at the end of Chapter 8 | 100minutes |
| 2． | Equation of state solutions and state transitive matrix | Exercises at the end of Chapter 8 | 100minutes |
| 3． | Stability and discrimination of stability | Exercises at the end of Chapter 8 | 100minutes |
| 4． | Coordinate conversion and system equivalence | CExercises at the end of hapter 9 | 100minutes |
| 5． | Diagonal canonical form and controllability and observability | Exercises at the end of Chapter 9 | 100minutes |
| 6． | Controllability canonical form and observability canonical form and their applications | Exercises at the end of Chapter 9 | 100minutes |
| 7． | State feedback control and stabilization | Exercises at the end of Chapter 10 | 100minutes |
| 8． | Direct feedback control and root locus method | Exercises at the end of Chapter 10 | 100minutes |
| 9． | Stabilization through serial compensators | Exercises at the end of Chapter 10 | 100minutes |
| 10． | Stabilization by observers | Exercises at the end of Chapter 10 | 100minutes |
| 11． | Servo system design | Exercises at the end of Chapter 11 | 100minutes |
| 12． | Optimal regulator design | Exercises at the end of Chapter 11 | 100minutes |
| 13． | Kalman filter | Exercises at the end of Distributed material | 100minutes |
| 14． | Examples and applied design. Examination |
Explanation | 100minutes |
| Total. | - | - | 1400minutes |
1. The evaluation depends on the presentations in reading club format (30%), report (30%) and examination (40%).
2. 60 points (60%) implies that students can solve 60% of the exercises listed at the end of the chapters. And this implies the students can design the basic control systems based on state-space approach and can apply the control design theory to simple practical systems.
2. 60 points (60%) implies that students can solve 60% of the exercises listed at the end of the chapters. And this implies the students can design the basic control systems based on state-space approach and can apply the control design theory to simple practical systems.
| ways of feedback | specific contents about "Other" |
|---|---|
| Feedback in the class |
References:
1. Thomas Kailath 「Linear Systems 」Prentice-Hall
2. G.C. Goodwin and K.S. Sin, Adaptive Filtering Prediction and Control, Prentice-Hall
3. S. Sastry and M. Bodson, Adaptive Control Design and Analysis, Wiley-Interscience
4. V.I. Utkin, Sliding Modes in Control Optimization, Springer-Verlag
5. G.C. Goodwin, S.F. Graebe and M.E. Salgado, Control System Design, Pearson
1. Thomas Kailath 「Linear Systems 」Prentice-Hall
2. G.C. Goodwin and K.S. Sin, Adaptive Filtering Prediction and Control, Prentice-Hall
3. S. Sastry and M. Bodson, Adaptive Control Design and Analysis, Wiley-Interscience
4. V.I. Utkin, Sliding Modes in Control Optimization, Springer-Verlag
5. G.C. Goodwin, S.F. Graebe and M.E. Salgado, Control System Design, Pearson
Very important:
1. A very good knowledge on Linear Algebra is absolutely needed (rank/trace of matrix, determinant, eigenvalue, eigenvector, linear space, linear subspace, dimension of a linear space, change of basis, similarity transformation of a matrix, minimal polynomial, Smith normal form, Jordan normal form, orthogonal matrix, unitary matrix, Hermitian matrix, etc.).
Special attention: Very good knowledge on minimal polynomial, Smith normal form and Jordan normal form, orthogonal matrix, unitary matrix and Hermitian matrix is needed.
2. A very good knowledge on Differential Equations (Ordinary and Partial Differential Equations in High Dimensions) is absolutely needed.
1. A very good knowledge on Linear Algebra is absolutely needed (rank/trace of matrix, determinant, eigenvalue, eigenvector, linear space, linear subspace, dimension of a linear space, change of basis, similarity transformation of a matrix, minimal polynomial, Smith normal form, Jordan normal form, orthogonal matrix, unitary matrix, Hermitian matrix, etc.).
Special attention: Very good knowledge on minimal polynomial, Smith normal form and Jordan normal form, orthogonal matrix, unitary matrix and Hermitian matrix is needed.
2. A very good knowledge on Differential Equations (Ordinary and Partial Differential Equations in High Dimensions) is absolutely needed.
- Course that cultivates an ability for utilizing knowledge
- Course that cultivates a basic problem-solving skills
| Work experience | Work experience and relevance to the course content if applicable |
|---|---|
| N/A | N/A |
- 7.AFFORDABLE AND CLEAN ENERGY
- 9.INDUSTRY, INNOVATION AND INFRASTRUCTURE
Last modified : Thu Mar 19 04:05:13 JST 2026