Signals and Control Systems

Smain FEMMAM, Director of research (HDR).

• Preface ixChapter 1 Control, Servo-mechanisms and System Regulation 11.1. Introduction 11.1.1. Generalities and definitions 11.1.2. Control law synthesis 51.1.3. Comprehension and application exercises 71.2. Process control 111.2.1. Correction in the frequency domain 111.2.2. Phase advance controller and PD controller 121.2.3. Phase delay controller and integrator compensator 141.2.4. Proportional, integral and derivative (PID) control 171.3. Some application exercises 231.3.1. Identification of the transfer function and control 231.3.2. PI control 301.3.3. Phase advance control 331.4. Some application exercises 361.5. Application 1: stabilization of a rigid robot with pneumatic actuator 391.5.1. Conventional approach 411.6. Application 2: temperature control of an oven 511.6.1. Modeling and identification study 51Chapter 2 System Process Control 552.1. Introduction 552.2. Modeling 552.2.1. Introduction 552.3. Governability, controllability and observability 562.3.1. Characteristic polynomial, minimal polynomial and Cayley–Hamilton theorem 562.3.2. Governability or controllability 562.3.3. Observability 632.3.4. Observer 682.3.5. Observer for state reconstruction 692.3.6. Minimal state–space representation 762.4. State feedback, control by poles placement and stability 792.4.1. State feedback control 792.4.2. Poles placement and stabilizability 802.4.3. Finite-time response for a discrete system, deadbeat response 832.4.4. Use of observers in control: separation principle 852.5. Linear quadratic (LQ) control 862.5.1. Linear quadratic regulator 892.6. Optimal control (LQ) 902.7. Comprehension and application exercises 94Chapter 3 Actuators: Modeling and Analysis 1173.1. Introduction: electric, hydraulic and pneumatic actuators 1173.1.1. Representation methods for physical systems 1183.1.2. Modeling of a few constituents of physical systems 1203.2. Transmission chains, actuators and sensors 1263.2.1. Electric actuators in robotics 1263.2.2. Motor speed torque characteristic 1313.2.3. Dynamic behavior or transient behavior 1313.2.4. Electric systems motor load 1343.3. Pneumatic actuators 1373.3.1. Pneumatic system modeling 1373.3.2. Frictions model 1453.4. Hydraulic actuators 1493.4.1. System description 1493.4.2. Mechanical model 1513.4.3. Hydraulic actuator model 1523.5. Application exercises 155Chapter 4 Digital Control and Polynomial Approach 1614.1. Introduction to digital control 1614.1.1. Digital controller synthesis by transposition 1624.1.2. Euler’s transposition 1644.1.3. Choice of the sampling period (Shannon’s theorem) 1704.2. PID controller synthesis and its equivalent digital RST 1714.2.1. Standard controllers 1714.2.2. Study of digital PIDs 1724.2.3. Digital RST controller synthesis 1784.2.4. Choice of poles and zeros to compensate 1794.2.5 Computation of polynomials R, S and T 1804.2.6. Additional objectives for synthesis 1814.3. Digital control by poles placement 1824.3.1. Choice of the sampling period 1834.4. Diophantine, Bézout, greatest common divisor, least common multiple and division 1834.4.1. Polynomial arithmetic 1834.4.2. Diophantine equation ax + by = c and Bachet–Bézout theorem 1844.4.3. Bézout’s identity 1854.4.4. Greatest common divisor 1854.4.5. Least common multiple 1854.5. A few comprehension and application exercises 186Chapter 5 NAO Robot 1935.1. Introduction 1935.2. Home care project 1945.2.1. Choregraphe software 1945.2.2. Nao Matlab SDK research 1995.2.3. Nao and home care 2065.2.4. The actions to be made 2075.3. Details of the various programs 2085.3.1. Ask for news 2085.3.2. CallFirefighters box 2125.3.3. CallNeighbor box 2135.3.4. CallFamily box 2155.3.5. Collision detection 2155.3.6. Special actions: waking-up 2165.3.7. Morning hygiene 2205.3.8. Gymnastics 2215.3.9. Nurse call 2255.3.10. Memory game 2275.3.11. Drugs reminder 2325.3.12. Reading 2335.3.13. Listening to music 2355.3.14. Multiplication game 2395.3.15. Nao’s dance 2435.3.16. Memory game 2455.3.17. Detect person on the ground 2475.3.18. At any time 2515.4. Conclusion 2535.4.1. Nao’s limitations and possible improvements 253Chapter 6 Application Problems with Solutions 2556.1. Exercise 6.1: car suspension 2556.1.1. Modeling 2566.1.2. Analysis 2576.2. Exercise 6.2: electromechanical system 2596.2.1. Modeling 2606.2.2. Analysis 2626.3. Exercises: identification and state–space representation 2636.3.1. Exercise 6.3 2636.3.2. Exercise 6.4 2656.3.3. Exercise 6.5 2686.3.4. Exercise 6.6 2706.3.5. Exercise 6.7 2766.4. Exercises: observation and control of nonlinear systems 2786.4.1. Exercise 6.8 2786.4.2. Exercise 6.9 2806.4.3. Exercise 6.10 2886.4.4. Exercise 6.11 2916.4.5. Exercise 6.12 2936.4.6. Exercise 6.13 2966.4.7. Exercise 6.14 3006.4.8. Exercise 6.15 300Bibliography 307Index 313