Algorithms Pid Controller 2019 (11 results)

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

Hardback. Condition: New.

Hardback. Condition: New.

Condition: New. Print on Demand.

Condition: New. Print on Demand.

Condition: New. PRINT ON DEMAND.

Hardcover. Condition: new. Hardcover. The reprint focuses on advanced PID controller-tuning algorithms in addition to conventional approaches based on mathematical controlled system analysis. Stavrov and al. proposed an improved version of a conventional PID controller based on a quadratic error model. De Moura Oliveira et al. proposed a PSO technique for PID controller design. Alimohammadi et al. introduced a multi-loop Model Reference Adaptive Control, leveraging a NARX model as the reference model, which was integrated with a Fractional Order PID. Alekseeva proposed a PD Steering Controller utilizing the predicted position on tracks for autonomous vehicles driven on slippery roads. A Neural PID controller for Unmanned Aerial Vehicles was presented by Avila et al., based on a Multilayer Perceptron trained with an Extended Kalman Filter. A study of six types of multi-loop model reference (ML-MR) control structures and design schemes for PID control loops is presented by Alagoz and al. Smeresky, Rizzo and Sands explore and analyze deterministic artificial intelligence composed of self-awareness statements along with a novel, optimal learning algorithm. Radac and Lala suggest a solution for the Output Reference Model tracking control problem, based on approximate dynamic programming and the Value Iteration (VI) algorithm for controller learning. A Kalman-Filter-Based tension control system for industrial Roll-to-Roll system is also presented by Hwang et al. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The reprint focuses on advanced PID controller-tuning algorithms in addition to conventional approaches based on mathematical controlled system analysis. Stavrov and al. proposed an improved version of a conventional PID controller based on a quadratic error model. De Moura Oliveira et al. proposed a PSO technique for PID controller design. Alimohammadi et al. introduced a multi-loop Model Reference Adaptive Control, leveraging a NARX model as the reference model, which was integrated with a Fractional Order PID. Alekseeva proposed a PD Steering Controller utilizing the predicted position on tracks for autonomous vehicles driven on slippery roads. A Neural PID controller for Unmanned Aerial Vehicles was presented by Avila et al., based on a Multilayer Perceptron trained with an Extended Kalman Filter. A study of six types of multi-loop model reference (ML-MR) control structures and design schemes for PID control loops is presented by Alagoz and al. Smeresky, Rizzo and Sands explore and analyze deterministic artificial intelligence composed of self-awareness statements along with a novel, optimal learning algorithm. Radac and Lala suggest a solution for the Output Reference Model tracking control problem, based on approximate dynamic programming and the Value Iteration (VI) algorithm for controller learning. A Kalman-Filter-Based tension control system for industrial Roll-to-Roll system is also presented by Hwang et al.…

Buch. Condition: Neu. Algorithms for PID Controller 2019 | Buch | Englisch | 2025 | MDPI AG | EAN 9783725848157 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.