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Modern Control Theory by U A Bakshi, M V Bakshi Book Details
| Book Name | Modern Control Theory |
| Author | U A Bakshi, M V Bakshi |
| Category | Electronics & Communication Engineering, Electrical Engineering Books |
| Book Language | English |
| Publisher | Technical Publications |
| Pages | 387 |
| ISBN | 9350387530 |
| Country | India |
| Book Size | 13 MB |
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About Modern Control Theory by U A Bakshi, M V Bakshi Book
Modern Control Theory is a branch of control engineering that focuses on the analysis and design of control systems using advanced mathematical techniques and concepts. It evolved as a response to the increasing complexity and sophistication of control systems in various engineering applications, such as aerospace, manufacturing, robotics, and more. The traditional control methods, such as classical control theory based on Laplace transforms, were often limited in handling complex and nonlinear systems. Modern Control Theory aims to overcome these limitations by employing more advanced mathematical tools and approaches.
Key Concepts and Techniques in Modern Control Theory:
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State-Space Representation: In modern control theory, systems are often represented in the state-space domain, which involves describing a system's behavior in terms of its state variables and their dynamics. This representation allows for a more flexible and comprehensive analysis of system behavior.
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Transfer Functions and Frequency Domain Analysis: While state-space representation is a key aspect of modern control theory, frequency domain analysis using transfer functions is still relevant. Transfer functions provide insights into system behavior in terms of frequency response, stability, and performance.
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Controllability and Observability: These are important concepts in state-space representation. A system is said to be controllable if it can be steered from any initial state to any desired final state within a finite time. Observability, on the other hand, refers to the ability to estimate the entire state of the system from the available measurements.
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Full-State Feedback Control: Using the state-space representation, modern control theory allows for the design of control laws that use full information about the system's state for feedback control. This often leads to more accurate and robust control.
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Optimal Control: Optimal control theory seeks to find control strategies that optimize a certain performance index, such as minimizing energy consumption, maximizing system stability, or achieving desired tracking performance. Techniques like the Pontryagin's Maximum Principle and the Linear Quadratic Regulator (LQR) fall under this category.
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State Estimation and Kalman Filtering: When full-state information is not available due to sensor limitations or noise, techniques like the Kalman filter are used to estimate the true state of the system based on noisy measurements.
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Nonlinear Systems and Adaptive Control: Modern control theory also addresses nonlinear systems, where traditional methods might not be directly applicable. Adaptive control techniques aim to adjust control strategies based on changing system dynamics.
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Robust Control: Robust control methods deal with uncertainties in system parameters or external disturbances. They aim to design controllers that provide satisfactory performance even in the presence of uncertainties.
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Multivariable Control: Modern control theory extends to systems with multiple inputs and outputs, allowing for the coordination and interaction of various subsystems.
Overall, modern control theory provides powerful tools for the analysis, design, and implementation of control systems in various engineering applications, enabling engineers to achieve desired performance, stability, and robustness in complex systems.
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