Can you suggest me some good book about control system algorithm (something a bit practical and hands-on)?
I hate teory, but i love algorithm that i can use in sw.
Well, you can't have the cake and eat it too. Control theory _is_ math, you won't get around that fact. Maybe that is one reason why there are not so many control e's around...
Also, practical control systems are much, much more than just "an algorithm" so only studying clever algorithms won't get you very far.
EDIT: I only now noted that your age is 17. While there is nothing wrong in that - we were all 17 once - you are unlikely to have studied the math needed to cover all of the subjects yet. So maybe this one is for later if you decide to continue on this track...Regarding books, if there is any possibility then get this (it is expensive as hell, but it will get you very, very far):
William S. Levine (ed):
The Control Handbook (3 parts) CRC Press
Control System Fundamentals ISBN 978-1-4200-7363-8
http://www.amazon.com/The-Control-Handbook-Second-Edition/dp/1420073621/ref=pd_sim_sbs_b_2 Control System Applications ISBN 978-1-4200-7360-7
http://www.amazon.com/The-Control-Handbook-Second-Edition/dp/1420073605/ref=pd_sim_sbs_b_4 Control System Advanced Methods ISBN 978-1-4200-7364-5
http://www.amazon.com/Control-Systems-Handbook-Second-Edition/dp/1420073648/ref=pd_sim_sbs_b_3This set of books will contain all the algorithms you are likely to ever need.
I inserted the contents list here (just because i can) so you can see the topics covered:
Fundamentals:SECTION I Mathematical Foundations
1 Ordinary Linear Differential and Difference Equations
2 The Fourier, Laplace, and z-Transforms
3 Matrices and Linear Algebra
4 Complex Variables
SECTION II Models for Dynamical Systems
5 Standard Mathematical Models
6 Graphical Models
SECTION III Analysis and Design Methods for Continuous-Time Systems
7 Analysis Methods
8 Stability Tests
9 Design Methods
SECTION IV Digital Control
10 Discrete-Time Systems
11 Sampled-Data Systems
12 Discrete-Time Equivalents of Continuous-Time Systems
13 Design Methods for Discrete-Time, Linear Time-Invariant Systems
14 Quantization Effects
15 Sample-Rate Selection
16 Real-Time Software for Implementation of Feedback Control
17 Programmable Controllers
SECTION V Analysis and Design Methods for Nonlinear Systems
18 Analysis Methods
19 Design Methods
Applications:SECTION I Automotive
1 Linear Parameter-Varying Control of Nonlinear Systems with Applications to Automotive and Aerospace Controls
2 Powertrain Control
3 Vehicle Controls
4 Model-Based Supervisory Control for Energy Optimization of Hybrid-Electric Vehicles
5 Purge Scheduling for Dead-Ended Anode Operation of PEM Fuel Cells
SECTION II Aerospace
6 Aerospace Real-Time Control System and Software
7 Stochastic Decision Making and Aerial Surveillance Control Strategies
8 Control Allocation
9 Swarm Stability
SECTION III Industrial
10 Control of Machine Tools and Machining Processes
11 Process Control in Semiconductor Manufacturing
12 Control of Polymerization Processes
13 Multiscale Modeling and Control of Porous Thin Film Growth
14 Control of Particulate Processes
15 Nonlinear Model Predictive Control for Batch Processes
16 The Use of Multivariate Statistics in Process Control
17 Plantwide Control
18 Automation and Control Solutions for Flat Strip Metal Processing
SECTION IV Biological and Medical
19 Model-Based Control of Biochemical Reactors
20 Robotic Surgery
21 Stochastic Gene Expression: Modeling, Analysis, and Identification
22 Modeling the Human Body as a Dynamical System: Applications
SECTION V Electronics
23 Control of Brushless DC Motors
24 Hybrid Model Predictive Control of the Boost Converter
SECTION VI Networks
25 The SNR Approach to Networked Control
26 Optimization and Control of Communication Networks
SECTION VII Special Applications
27 Advanced Motion Control Design
28 Color Controls: An Advanced Feedback System
29 The Construction of Portfolios of Financial Assets: An Application of Optimal Stochastic Control
30 Earthquake Response Control for Civil Structures
31 Quantum Estimation and Control
32 Motion Control of Marine Craft
33 Control of Unstable Oscillations in Flows
34 Modeling and Control of Air Conditioning and Refrigeration System
Advanced Methods:SECTION I Analysis Methods for MIMO Linear Systems
1 Numerical and Computational Issues in Linear Control and System Theory
2 Multivariable Poles, Zeros, and Pole-Zero Cancellations
3 Fundamentals of Linear Time-Varying Systems
4 Balanced Realizations, Model Order Reduction, and the Hankel Operator
5 Geometric Theory of Linear Systems
6 Polynomial and Matrix Fraction Descriptions
7 Robustness Analysis with Real Parametric Uncertainty
8 MIMO Frequency Response Analysis and the Singular Value Decomposition
9 Stability Robustness to Unstructured Uncertainty for Linear Time Invariant Systems
10 Trade-Offs and Limitations in Feedback Systems
11 Modeling Deterministic Uncertainty
SECTION II Kalman Filter and Observers
12 Linear Systems and White Noise
13 Kalman Filtering
14 Riccati Equations and Their Solution
15 Observers
SECTION III Design Methods for MIMO LTI Systems
16 Eigenstructure Assignmen
17 Linear Quadratic Regulator Control
18 H2 (LQG) and H? Control
19 1 Robust Control: Theory, Computation, and Design
20 The Structured Singular Value (?) Framework
21 Algebraic Design Methods
22 Quantitative Feedback Theory (QFT) Technique
23 Robust Servomechanism Problem
24 Linear Matrix Inequalities in Contro
25 Optimal Contro
26 Decentralized Control
27 Decoupling
28 Linear Model Predictive Control in the Process Industries
SECTION IV Analysis and Design of Hybrid Systems
29 Computation of Reach Sets for Dynamical Systems
30 Hybrid Dynamical Systems: Stability and Stabilization
31 Optimal Control of Switching Systems via Embedding into Continuous Optimal Control Problem
SECTION V Adaptive Control
32 Automatic Tuning of PID Controllers
33 Self-Tuning Contro
34 Model Reference Adaptive Control
35 Robust Adaptive Control
36 Iterative Learning Control
SECTION VI Analysis and Design of Nonlinear Systems
37 Nonlinear Zero Dynamics
38 The Lie Bracket and Control
39 Two Timescale and Averaging Methods
40 Volterra and Fliess Series Expansions for Nonlinear Systems
41 Integral Quadratic Constraints
42 Control of Nonholonomic and Underactuated Systems
SECTION VII Stability
43 Lyapunov Stability
44 Input–Output Stability
45 Input-to-State Stability
SECTION VIII Design
46 Feedback Linearization of Nonlinear Systems
47 The Steady-State Behavior of a Nonlinear System
48 Nonlinear Output Regulation
49 Lyapunov Design
50 Variable Structure, Sliding-Mode Controller Design
51 Control of Bifurcations and Chaos
52 Open-Loop Control Using Oscillatory Inputs
53 Adaptive Nonlinear Control
54 Intelligent Control
55 Fuzzy Control
56 Neural Control
SECTION IX System Identification
57 System Identification
SECTION X Stochastic Control
58 Discrete Time Markov Processes
59 Stochastic Differential Equations
60 Linear Stochastic Input–Output Models
61 Dynamic Programming
62 Approximate Dynamic Programming
63 Stability of Stochastic Systems
64 Stochastic Adaptive Control for Continuous-Time Linear Systems
65 Probabilistic and Randomized Tools for Control Design
66 Stabilization of Stochastic Nonlinear Continuous-Time Systems
SECTION XI Control of Distributed Parameter Systems
67 Control of Systems Governed by Partial Differential Equations
68 Controllability of Thin Elastic Beams and Plates
69 Control of the Heat Equation
70 Observability of Linear Distributed-Parameter Systems
71 Boundary Control of PDEs: The Backstepping Approach
72 Stabilization of Fluid Flows
SECTION XII Networks and Networked Controls
73 Control over Digital Networks
74 Decentralized Control and Algebraic Approaches
75 Estimation and Control across Analog Erasure Channels
76 Passivity Approach to Network Stability Analysis and Distributed Control Synthesis