Adaptive Kalman Filtering Model Predictive Controller Design for Stabilizing and Trajectory Tracking of Inverted Pendulu
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ORIGINAL CONTRIBUTION
Adaptive Kalman Filtering Model Predictive Controller Design for Stabilizing and Trajectory Tracking of Inverted Pendulum Akshaya Kumar Patra1
Received: 11 August 2019 / Accepted: 5 September 2020 The Institution of Engineers (India) 2020
Abstract The goal of this manuscript is to formulate a Kalman Filtering Model Predictive Controller (KFMPC) for control of cart position, cart velocity, angular position, and angular velocity of pendulum within a stable range under model uncertainties and disturbances. For designing of the KFMPC, a 4th-order linearized structure of the inverted pendulum system is taken. In this strategy, the conventional model predictive controller is re-formulated with a state estimator based on the Kalman filtering strategy to update the control actions. The approval of the updated control execution of KFMPC is built up by comparative outcome examination with other well-known control techniques. The comparative results obviously expose the better action of the proposed strategy to monitor the system outcomes inside the steady range as far as accuracy, robustness, and stability. Keywords angular position IPS State estimator Laguerre functions Model predictive control
Introduction The IPS control problem is of paramount concern among other control problems due to under-actuated, nonlinear, and the non-minimum phase properties as discussed in [1–3]. Also, this IPS finds numerous industry-based applications like rockets, robots, guided missiles, different
& Akshaya Kumar Patra [email protected]; [email protected] 1
Department of Electrical, Electronics Engineering, ITER, Siksha ‘O’Anusandhan University, Bhubaneswar 751030, Odisha, India
crane structures, and a Segway or self-balancing vehicles with two wheels as reported in [4]. In the current work, owing to prominent control dynamics relevance, the IPS has been chosen by an adaptive control law after its proper testing and analysis. Around last thirty years, several strategies of control techniques are put forth and verified for AP control of pendulum within the range of stability. In the problems of IPS with measured AP-based variable gains of the controller, the strategies of control like switching PID and time discrete are implemented as explained in [5, 6]. The practical application of the abovementioned controllers is infeasible owing to limitations like the setting of the optimal gain variable with a lower robust control range and the necessity of the gain setting change according to the variation in the operating conditions. Among several other highlighted optimal control methods applied to limit the AP and AV of a pendulum are Fuzzy [7], LQR [8–10], neurocontrol [11], backstepping control [12], passivity control [13], state feedback control [14], Hinfinity control [15], sliding-mode (SM) control [16], fuzzy sliding-mode (FSM) control [17, 18], and BLQG control [19]. Although the AP and AV control of the IPS with improved accuracy by applying the aforementioned control methods has been quite effectiv
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