8 research outputs found
LINEAR MATRIX INEQUALITY BASED PROPORTIONAL INTEGRAL DERIVATIVE CONTROL FOR HIGH ORDER PLANT
This study presents the application of Linear Matrix Inequalities (LMI) approach in designing a proportional integral derivative (PID) controller for a high order plant. This work also proposes practical steps in designing the robust controller. To cast this control design problem into the LMI framework, the transfer functions of the system with various payloads are obtained by carrying out nonlinear system identification. Subsequently, the dynamic model is represented into convex formulation which leads to the formulation of system requirement into LMIs representation that can accommodate the convex model. A set of robust PID gains is then obtained by solving the LMIs with desired specifications. For performance assessment, a PID controller is also designed using Ziegler Nichols (ZN) technique for all loading conditions. System responses namely hub angular position and deflection of both links of the flexible manipulator are evaluated in time and frequency domains. The performance of the LMI-PID controller is verified by comparing with the results using the ZN-PID controller in terms of time response specifications of hub angular position and level of deflection in time and frequency domains
Modelling and control of a two-link flexible manipulator using finite element modal analysis
This thesis focuses on Finite Element (FE) modeling and robust control of a two-link flexible manipulator based on a high resolution FE model and the system vibration modes. A new FE model is derived using Euler-Bernoulli beam elements, and the model is validated using commercial software Abaqus CAE. The frequency and time domain analysis reveal that the response of the FE model substantially varies with changing the number of elements, unless a high number of elements (100 elements in this work) is used. The gap between the complexity of the high order FE model capable of predicting dynamics of the multibody system, and suitability of the model for controller design is bridged by designing control schemes based on the reduced order models obtained using modal truncation/H8 techniques. Two reduced order multi-input multi-output modal control algorithms composed of a robust feedback controller along with a feed-forward compensator are designed. The first controller, Inversion-based Two Mode Controller (ITMC), is designed using a mixed-sensitivity H8 synthesis and a modal inversion-based compensator. The second controller, Shaping Two-Mode Controller (STMC), is designed with H8 loopshaping using the modal characteristics of the system. Stability robustness against unmodelled dynamics due to the model reduction is shown using the small gain theorem. Performance of the feedback controllers are compared with Linear Quadratic Gaussian designs and are shown to have better tracking characteristics. Effectiveness of the control schemes is shown by simulation of rest-to-rest maneuver of the manipulator to a set of desired points in the joint space. The ITMC is shown to have more precise tracking performance, while STMC has higher control over vibration of the tip, at the expense of more tracking errors
Nonlinear control for Two-Link flexible manipulator
Recently the use of robot manipulators has been increasing in many applications such as medical applications, automobile, construction, manufacturing, military, space, etc. However, current rigid manipulators have high inertia and use actuators with large energy consumption. Moreover, rigid manipulators are slow and have low payload-to arm-mass ratios because link deformation is not allowed. The main advantages of flexible manipulators over rigid manipulators are light in weight, higher speed of operation, larger workspace, smaller actuator, lower energy consumption and lower cost. However, there is no adequate closed-form solutions exist for flexible manipulators. This is mainly because flexible dynamics are modeled with partial differential equations, which give rise to infinite dimensional dynamical systems that are, in general, not possible to represent exactly or efficiently on a computer which makes modeling a challenging task. In addition, if flexibility nature wasn\u27t considered, there will be calculation errors in the calculated torque requirement for the motors and in the calculated position of the end-effecter. As for the control task, it is considered as a complex task since flexible manipulators are non-minimum phase system, under-actuated system and Multi-Input/Multi-Output (MIMO) nonlinear system. This thesis focuses on the development of dynamic formulation model and three control techniques aiming to achieve accurate position control and improving dynamic stability for Two-Link Flexible Manipulators (TLFMs). LQR controller is designed based on the linearized model of the TLFM; however, it is applied on both linearized and nonlinear models. In addition to LQR, Backstepping and Sliding mode controllers are designed as nonlinear control approaches and applied on both the nonlinear model of the TLFM and the physical system. The three developed control techniques are tested through simulation based on the developed dynamic formulation model using MATLAB/SIMULINK. Stability and performance analysis were conducted and tuned to obtain the best results. Then, the performance and stability results obtained through simulation are compared. Finally, the developed control techniques were implemented and analyzed on the 2-DOF Serial Flexible Link Robot experimental system from Quanser and the results are illustrated and compared with that obtained through simulation
ΠΠ°ΠΏΡΠ΅Π΄Π½ΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠΈΠΌΠ° Ρ ΡΠΈΡΡΠ΅ΠΌΠΈΠΌΠ° Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ Π±ΠΎΡΠ±Π΅Π½ΠΈΡ Π°Π²ΠΈΠΎΠ½Π°
Π£ ΠΎΠ²ΠΎΡ Π΄ΠΎΠΊΡΠΎΡΡΠΊΠΎΡ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΡΡ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° Π½Π° ΡΠ΅ΠΌΡ ΡΠ°Π·Π²ΠΎΡΠ° Π½Π°ΠΏΡΠ΅Π΄Π½ΠΈΡ
Π°Π»Π³ΠΎΡΠΈΡΠ°ΠΌΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° Π·Π° Π΄Π²Π° ΡΠΈΡΡΠ΅ΠΌΠ° Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
Π±ΠΎΡΠ±Π΅Π½ΠΈΡ
Π°Π²ΠΈΠΎΠ½Π°-ΡΠ΅Π½ΡΡΠΈΡΡΠ³Π΅ Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° (ΡΠ΅Π½ΡΡΠΈΡΡΠ³Π΅) ΠΈ ΡΡΠ΅ΡΠ°ΡΠ° Π·Π° ΠΏΡΠΎΡΡΠΎΡΠ½Ρ Π΄Π΅Π·ΠΎΡΠΈΡΠ΅Π½ΡΠ°ΡΠΈΡΡ ΠΏΠΈΠ»ΠΎΡΠ° (Π£ΠΠΠ-Π°). ΠΠ²ΠΈ ΡΡΠ΅ΡΠ°ΡΠΈ ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°Π½ΠΈ ΠΊΠ°ΠΎ ΡΡΠΎΠΎΡΠ½ΠΈ (ΡΠ΅Π½ΡΡΠΈΡΡΠ³Π°) ΠΈ ΡΠ΅ΡΠ²ΠΎΡΠΎΠΎΡΠ½ΠΈ (Π£ΠΠΠ) ΡΠΎΠ±ΠΎΡΡΠΊΠΈ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠΈ (ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠΈ) ΡΠ° ΡΠΈΠ»ΠΈΠ½Π΄ΡΠΈΡΠ½ΠΈΠΌ Π·Π³Π»ΠΎΠ±ΠΎΠ²ΠΈΠΌΠ°.
ΠΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° ΠΈΠΌΠ°ΡΡ Π·Π° ΡΠΈΡ ΠΏΡΠΎΡΠΈΡΠΈΠ²Π°ΡΠ΅ ΠΈ ΠΏΡΠΎΠ΄ΡΠ±ΡΠΈΠ²Π°ΡΠ΅ Π½Π°ΡΡΠ½ΠΈΡ
ΡΠ°Π·Π½Π°ΡΠ° ΠΈ Π΄ΠΎΡΡΠΈΠ³Π½ΡΡΠ° Ρ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠ° ΠΈ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° ΡΠ°Π·ΠΌΠ°ΡΡΠ°Π½ΠΈΡ
ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ° Ρ ΡΠΈΡΡΠ΅ΠΌΠΈΠΌΠ° Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
Π±ΠΎΡΠ±Π΅Π½ΠΈΡ
Π°Π²ΠΈΠΎΠ½Π°, Π° ΠΊΠΎΡΠ° ΡΠ΅ ΠΌΠΎΠ³Ρ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠΈ ΠΈ Π½Π° ΡΠ΅ΡΠΈΡΡΠΊΠ΅ ΡΠΎΠ±ΠΎΡΡΠΊΠ΅ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ΅ Ρ ΠΎΠΏΡΡΠ΅ΠΌ ΡΠΌΠΈΡΠ»Ρ. Π£ ΠΎΠΊΠ²ΠΈΡΡ ΠΎΠ²Π΅ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠ΅ ΡΡ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΈ Π½ΠΎΠ²ΠΈ ΠΈ ΡΠ½Π°ΠΏΡΠ΅ΡΠ΅Π½ΠΈ ΠΏΠΎΡΡΠΎΡΠ΅ΡΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ ΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ Ρ Π΄ΠΎΠΌΠ΅Π½Ρ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΠΊΠ΅ ΡΠΎΠ±ΠΎΡΠ°, ΡΠ°Π·Π²ΠΎΡΠ° ΠΏΠ»Π°Π½Π΅ΡΠ° ΡΡΠ°ΡΠ΅ΠΊΡΠΎΡΠΈΡΠ΅, Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΠΎΠ³ ΠΈΠ·Π±ΠΎΡΠ° Π°ΠΊΡΡΠ°ΡΠΎΡΠ°, ΠΈ ΠΎΠ΄Π°Π±ΠΈΡΠ° ΠΏΡΠ°Π²ΠΈΠ»Π½Π΅ ΡΡΡΠ°ΡΠ΅Π³ΠΈΡΠ΅ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° ΠΊΡΠ΅ΡΠ°ΡΠ΅ΠΌ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½ΠΈΡ
ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ°.
ΠΡΠΈΠΊΠ°Π·Π°Π½ ΡΠ΅ ΠΊΠΎΠΌΠΏΠ»Π΅ΡΠ°Π½ ΠΏΠΎΡΡΡΠΏΠ°ΠΊ ΡΠ°Π·Π²ΠΎΡΠ° ΡΠΈΡΡΠ΅ΠΌΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° Π·Π° ΡΠ΅Π½ΡΡΠΈΡΡΠ³Ρ Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
Π±ΠΎΡΠ±Π΅Π½ΠΈΡ
Π°Π²ΠΈΠΎΠ½Π°, ΡΡΠΎΠΎΡΠ½ΠΎΠ³ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ° ΠΊΠΎΡΠΈ ΠΎΡΡΠ²Π°ΡΡΡΠ΅ ΠΈΠ·ΡΠ·Π΅ΡΠ½ΠΎ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΡΠΊΠΈ Π·Π°Ρ
ΡΠ΅Π²Π½Π΅ ΡΡΠ°ΡΠ΅ΠΊΡΠΎΡΠΈΡΠ΅, Π° ΠΊΠΎΡΠΈ ΡΠ΅ Π±Π°Π·ΠΈΡΠ° Π½Π° ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ°ΠΌΠ° Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ΠΎΠ³ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΡΠΊΠΎΠ³ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π°, ΠΊΠ°ΠΎ ΠΈ Π½Π° ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠ° ΡΠ΅Π°Π»ΠΈΡΡΠΈΡΠ½ΠΈΡ
ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΡ
Π΄Π΅ΡΠ΅Π½ΡΡΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΈΡ
ΠΈ ΡΠ΅Π½ΡΡΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄Π° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ°. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° Π·Π° ΡΠ΅Π½ΡΡΠΈΡΡΠ³Ρ ΡΡ ΠΏΡΠΈΠΌΠ΅ΡΠ΅Π½Π΅ ΠΈ Π½Π° ΡΠ΅ΡΠ²ΠΎΡΠΎΠΎΡΠ½ΠΈ ΡΡΠ΅ΡΠ°Ρ Π·Π° ΠΏΡΠΎΡΡΠΎΡΠ½Ρ Π΄Π΅Π·ΠΎΡΠΈΡΠ΅Π½ΡΠ°ΡΠΈΡΡ ΠΏΠΈΠ»ΠΎΡΠ°. ΠΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠ°, Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ Ρ ΠΎΠΊΠ²ΠΈΡΡ ΠΏΠ»Π°Π½Π΅ΡΠ° ΡΡΠ°ΡΠ΅ΠΊΡΠΎΡΠΈΡΠ΅, ΠΌΠ΅ΡΠΎΠ΄Π° ΠΈΠ·Π±ΠΎΡΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠΊΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ°, ΠΌΠ΅ΡΠΎΠ΄Π° ΡΠ΅Π°Π»ΠΈΡΡΠΈΡΠ½Π΅ ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ°, ΠΈ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΈΠ·Π±ΠΎΡΠ° Π°ΠΊΡΡΠ°ΡΠΎΡΠ° ΡΡ ΠΏΡΠΈΠΌΠ΅ΡΠΈΠ²Π΅ ΠΈ Π½Π° ΠΎΠΏΡΡΠΈ ΡΠ»ΡΡΠ°Ρ ΡΠΎΠ±ΠΎΡΡΠΊΠΎΠ³ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ° ΡΠ° Π²ΠΈΡΠ΅ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΠ»ΠΎΠ±ΠΎΠ΄Π΅
Advanced control algorithms for the manipulators within modern combat aircraft pilot training systems
Π£ ΠΎΠ²ΠΎΡ Π΄ΠΎΠΊΡΠΎΡΡΠΊΠΎΡ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠΈ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΡΡ ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° Π½Π° ΡΠ΅ΠΌΡ ΡΠ°Π·Π²ΠΎΡΠ° Π½Π°ΠΏΡΠ΅Π΄Π½ΠΈΡ
Π°Π»Π³ΠΎΡΠΈΡΠ°ΠΌΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° Π·Π° Π΄Π²Π° ΡΠΈΡΡΠ΅ΠΌΠ° Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
Π±ΠΎΡΠ±Π΅Π½ΠΈΡ
Π°Π²ΠΈΠΎΠ½Π°-ΡΠ΅Π½ΡΡΠΈΡΡΠ³Π΅ Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° (ΡΠ΅Π½ΡΡΠΈΡΡΠ³Π΅) ΠΈ ΡΡΠ΅ΡΠ°ΡΠ° Π·Π° ΠΏΡΠΎΡΡΠΎΡΠ½Ρ Π΄Π΅Π·ΠΎΡΠΈΡΠ΅Π½ΡΠ°ΡΠΈΡΡ ΠΏΠΈΠ»ΠΎΡΠ° (Π£ΠΠΠ-a). ΠΠ²ΠΈ ΡΡΠ΅ΡΠ°ΡΠΈ ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°Π½ΠΈ ΠΊΠ°ΠΎ ΡΡΠΎΠΎΡΠ½ΠΈ (ΡΠ΅Π½ΡΡΠΈΡΡΠ³Π°) ΠΈ ΡΠ΅ΡΠ²ΠΎΡΠΎΠΎΡΠ½ΠΈ (Π£ΠΠΠ) ΡΠΎΠ±ΠΎΡΡΠΊΠΈ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠΈ (ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠΈ) ΡΠ° ΡΠΈΠ»ΠΈΠ½Π΄ΡΠΈΡΠ½ΠΈΠΌ Π·Π³Π»ΠΎΠ±ΠΎΠ²ΠΈΠΌΠ°.
ΠΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π° ΠΈΡΡΡΠ°ΠΆΠΈΠ²Π°ΡΠ° ΠΈΠΌΠ°ΡΡ Π·Π° ΡΠΈΡ ΠΏΡΠΎΡΠΈΡΠΈΠ²Π°ΡΠ΅ ΠΈ ΠΏΡΠΎΠ΄ΡΠ±ΡΠΈΠ²Π°ΡΠ΅ Π½Π°ΡΡΠ½ΠΈΡ
ΡΠ°Π·Π½Π°ΡΠ° ΠΈ Π΄ΠΎΡΡΠΈΠ³Π½ΡΡΠ° Ρ ΠΎΠ±Π»Π°ΡΡΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠ° ΠΈ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° ΡΠ°Π·ΠΌΠ°ΡΡΠ°Π½ΠΈΡ
ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ° Ρ ΡΠΈΡΡΠ΅ΠΌΠΈΠΌΠ° Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
Π±ΠΎΡΠ±Π΅Π½ΠΈΡ
Π°Π²ΠΈΠΎΠ½Π°, Π° ΠΊΠΎΡΠ° ΡΠ΅ ΠΌΠΎΠ³Ρ ΠΏΡΠΈΠΌΠ΅Π½ΠΈΡΠΈ ΠΈ Π½Π° ΡΠ΅ΡΠΈΡΡΠΊΠ΅ ΡΠΎΠ±ΠΎΡΡΠΊΠ΅ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ΅ Ρ ΠΎΠΏΡΡΠ΅ΠΌ ΡΠΌΠΈΡΠ»Ρ. Π£ ΠΎΠΊΠ²ΠΈΡΡ ΠΎΠ²Π΅ Π΄ΠΈΡΠ΅ΡΡΠ°ΡΠΈΡΠ΅ ΡΡ ΡΠ°Π·Π²ΠΈΡΠ΅Π½ΠΈ Π½ΠΎΠ²ΠΈ ΠΈ ΡΠ½Π°ΠΏΡΠ΅ΡΠ΅Π½ΠΈ ΠΏΠΎΡΡΠΎΡΠ΅ΡΠΈ ΠΌΠ΅ΡΠΎΠ΄ΠΈ ΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈ Ρ Π΄ΠΎΠΌΠ΅Π½Ρ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΠΊΠ΅ ΡΠΎΠ±ΠΎΡΠ°, ΡΠ°Π·Π²ΠΎΡΠ° ΠΏΠ»Π°Π½Π΅ΡΠ° ΡΡΠ°ΡΠ΅ΠΊΡΠΎΡΠΈΡΠ΅, Π°Π΄Π΅ΠΊΠ²Π°ΡΠ½ΠΎΠ³ ΠΈΠ·Π±ΠΎΡΠ° Π°ΠΊΡΡΠ°ΡΠΎΡΠ°, ΠΈ ΠΎΠ΄Π°Π±ΠΈΡΠ° ΠΏΡΠ°Π²ΠΈΠ»Π½Π΅ ΡΡΡΠ°ΡΠ΅Π³ΠΈΡΠ΅ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° ΠΊΡΠ΅ΡΠ°ΡΠ΅ΠΌ ΠΏΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½ΠΈΡ
ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ°.
ΠΡΠΈΠΊΠ°Π·Π°Π½ ΡΠ΅ ΠΊΠΎΠΌΠΏΠ»Π΅ΡΠ°Π½ ΠΏΠΎΡΡΡΠΏΠ°ΠΊ ΡΠ°Π·Π²ΠΎΡΠ° ΡΠΈΡΡΠ΅ΠΌΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° Π·Π° ΡΠ΅Π½ΡΡΠΈΡΡΠ³Ρ Π·Π° ΡΡΠ΅Π½Π°ΠΆΡ ΠΏΠΈΠ»ΠΎΡΠ° ΡΠ°Π²ΡΠ΅ΠΌΠ΅Π½ΠΈΡ
Π±ΠΎΡΠ±Π΅Π½ΠΈΡ
Π°Π²ΠΈΠΎΠ½Π°, ΡΡΠΎΠΎΡΠ½ΠΎΠ³ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ° ΠΊΠΎΡΠΈ ΠΎΡΡΠ²Π°ΡΡΡΠ΅ ΠΈΠ·ΡΠ·Π΅ΡΠ½ΠΎ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΡΠΊΠΈ Π·Π°Ρ
ΡΠ΅Π²Π½Π΅ ΡΡΠ°ΡΠ΅ΠΊΡΠΎΡΠΈΡΠ΅, Π° ΠΊΠΎΡΠΈ ΡΠ΅ Π±Π°Π·ΠΈΡΠ° Π½Π° ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ°ΠΌΠ° Π΄Π΅ΡΠΈΠ½ΠΈΡΠ°Π½ΠΎΠ³ ΠΊΠΈΠ½Π΅ΠΌΠ°ΡΠΈΡΠΊΠΎΠ³ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠΊΠΎΠ³ ΠΌΠΎΠ΄Π΅Π»Π°, ΠΊΠ°ΠΎ ΠΈ Π½Π° ΠΌΠ΅ΡΠΎΠ΄Π°ΠΌΠ° ΡΠ΅Π°Π»ΠΈΡΡΠΈΡΠ½ΠΈΡ
ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΈΡ
Π΄Π΅ΡΠ΅Π½ΡΡΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΈΡ
ΠΈ ΡΠ΅Π½ΡΡΠ°Π»ΠΈΠ·ΠΎΠ²Π°Π½ΠΈΡ
ΠΌΠ΅ΡΠΎΠ΄Π° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ°. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ ΡΠΏΡΠ°Π²ΡΠ°ΡΠ° Π·Π° ΡΠ΅Π½ΡΡΠΈΡΡΠ³Ρ ΡΡ ΠΏΡΠΈΠΌΠ΅ΡΠ΅Π½Π΅ ΠΈ Π½Π° ΡΠ΅ΡΠ²ΠΎΡΠΎΠΎΡΠ½ΠΈ ΡΡΠ΅ΡΠ°Ρ Π·Π° ΠΏΡΠΎΡΡΠΎΡΠ½Ρ Π΄Π΅Π·ΠΎΡΠΈΡΠ΅Π½ΡΠ°ΡΠΈΡΡ ΠΏΠΈΠ»ΠΎΡΠ°. ΠΡΠ΅Π΄ΡΡΠ°Π²ΡΠ΅Π½Π΅ ΠΌΠ΅ΡΠΎΠ΄Π΅ ΠΌΠΎΠ΄Π΅Π»ΠΎΠ²Π°ΡΠ°, Π°Π»Π³ΠΎΡΠΈΡΠΌΠΈ Ρ ΠΎΠΊΠ²ΠΈΡΡ ΠΏΠ»Π°Π½Π΅ΡΠ° ΡΡΠ°ΡΠ΅ΠΊΡΠΎΡΠΈΡΠ΅, ΠΌΠ΅ΡΠΎΠ΄Π° ΠΈΠ·Π±ΠΎΡΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠΊΠΎΠ³ ΡΠΈΡΡΠ΅ΠΌΠ°, ΠΌΠ΅ΡΠΎΠ΄Π° ΡΠ΅Π°Π»ΠΈΡΡΠΈΡΠ½Π΅ ΡΠΈΠΌΡΠ»Π°ΡΠΈΡΠ΅ ΠΏΠ΅ΡΡΠΎΡΠΌΠ°Π½ΡΠΈ ΡΠΈΡΡΠ΅ΠΌΠ° ΡΠΏΡΠ°Π²ΡΠ°ΡΠ°, ΠΈ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΈΠ·Π±ΠΎΡΠ° Π°ΠΊΡΡΠ°ΡΠΎΡΠ° ΡΡ ΠΏΡΠΈΠΌΠ΅ΡΠΈΠ²Π΅ ΠΈ Π½Π° ΠΎΠΏΡΡΠΈ ΡΠ»ΡΡΠ°Ρ ΡΠΎΠ±ΠΎΡΡΠΊΠΎΠ³ ΠΌΠ°Π½ΠΈΠΏΡΠ»Π°ΡΠΎΡΠ° ΡΠ° Π²ΠΈΡΠ΅ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΡΠ»ΠΎΠ±ΠΎΠ΄Π΅.In this doctoral dissertation, a research considering development of the advanced control algorithms for two modern combat aircraft pilot training systems-Centrifuge Motion Simulator (centrifuge) and Spatial Disorientation Trainer (SDT) is presented. These devices are modeled and controlled as 3DoF (centrifuge) and 4DoF (SDT) robot manipulators with rotational axes.
The presented research aims to broaden and deepen scientific knowledge and achievements in the field of modeling and control of the considered modern combat aircraft pilot training systems, that can also be applied to Π° general serial robot manipulator. A new and an improved existing methods and models have been derived in the field of robot kinematics, trajectory planning, an adequate drive selection and control strategy choice.
A complete development process of a control system for the centrifuge, which is a manipulator that performs a highly challenging motion, based on simulations of the defined kinematic and dynamic models, as well as on realistic simulations of the proposed decentralized and centralized control methods, is presented. The control methods proposed for the centrifuge are also applied to the 4DoF SDT.
The modeling methods, the trajectory planning algorithms, the control system design and simulation methods, and the drive selection strategies, presented here for the considered manipulators within modern combat aircraft pilot training systems, are also applicable within the general robot manipulatorβs domain
Adaptive Control
Adaptive control has been a remarkable field for industrial and academic research since 1950s. Since more and more adaptive algorithms are applied in various control applications, it is becoming very important for practical implementation. As it can be confirmed from the increasing number of conferences and journals on adaptive control topics, it is certain that the adaptive control is a significant guidance for technology development.The authors the chapters in this book are professionals in their areas and their recent research results are presented in this book which will also provide new ideas for improved performance of various control application problems